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Posted to commits@tvm.apache.org by tq...@apache.org on 2022/12/05 02:07:11 UTC
[tvm-site] branch asf-site updated: deploying docs (apache/tvm@3a81aef40bca9479d4a691b3a80e42b01f3f8a0d)
This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/tvm-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new e6c3a7c5db deploying docs (apache/tvm@3a81aef40bca9479d4a691b3a80e42b01f3f8a0d)
e6c3a7c5db is described below
commit e6c3a7c5db0db1d93656620b0dd5a222887bb088
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Mon Dec 5 02:07:04 2022 +0000
deploying docs (apache/tvm@3a81aef40bca9479d4a691b3a80e42b01f3f8a0d)
---
docs/_images/sphx_glr_micro_train_001.png | Bin 337505 -> 324216 bytes
docs/_images/sphx_glr_micro_train_thumb.png | Bin 23675 -> 23634 bytes
.../how_to/compile_models/from_darknet.rst.txt | 2 +-
.../how_to/compile_models/from_mxnet.rst.txt | 2 +-
.../how_to/compile_models/from_oneflow.rst.txt | 2 +-
.../how_to/compile_models/from_pytorch.rst.txt | 2 +-
.../how_to/compile_models/from_tensorflow.rst.txt | 2 +-
.../compile_models/sg_execution_times.rst.txt | 22 +-
.../deploy_models/deploy_model_on_adreno.rst.txt | 7 +-
.../deploy_models/deploy_model_on_android.rst.txt | 2 +-
.../deploy_object_detection_pytorch.rst.txt | 4 +-
.../deploy_models/deploy_prequantized.rst.txt | 6 +-
.../deploy_prequantized_tflite.rst.txt | 4 +-
.../how_to/deploy_models/deploy_quantized.rst.txt | 2 +-
.../deploy_models/deploy_ssd_gluoncv.rst.txt | 4 +-
.../deploy_models/sg_execution_times.rst.txt | 22 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 2 +-
.../how_to/extend_tvm/sg_execution_times.rst.txt | 8 +-
.../how_to/extend_tvm/use_pass_instrument.rst.txt | 16 +-
.../optimize_operators/opt_conv_cuda.rst.txt | 2 +-
.../optimize_operators/opt_conv_tensorcore.rst.txt | 2 +-
.../how_to/optimize_operators/opt_gemm.rst.txt | 16 +-
.../optimize_operators/sg_execution_times.rst.txt | 8 +-
.../sg_execution_times.rst.txt | 14 +-
.../tune_conv2d_layer_cuda.rst.txt | 11 +-
.../tune_network_cuda.rst.txt | 4 +-
.../tune_network_x86.rst.txt | 4 +-
.../tune_sparse_x86.rst.txt | 80 +-
.../tune_with_autotvm/sg_execution_times.rst.txt | 4 +-
.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 1140 ++++++++++----------
.../work_with_microtvm/micro_autotune.rst.txt | 16 +-
.../work_with_microtvm/micro_pytorch.rst.txt | 4 +-
.../how_to/work_with_microtvm/micro_train.rst.txt | 18 +-
.../work_with_microtvm/sg_execution_times.rst.txt | 12 +-
.../work_with_relay/sg_execution_times.rst.txt | 8 +-
.../how_to/work_with_schedules/intrin_math.rst.txt | 2 +-
.../work_with_schedules/sg_execution_times.rst.txt | 16 +-
.../how_to/work_with_schedules/tensorize.rst.txt | 2 +-
.../tutorials/autotvm/sg_execution_times.rst.txt | 4 +-
.../frontend/deploy_classification.rst.txt | 2 +-
.../tutorials/frontend/deploy_detection.rst.txt | 2 +-
.../tutorials/frontend/sg_execution_times.rst.txt | 6 +-
.../tutorials/optimize/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/sg_execution_times.rst.txt | 6 +-
.../tutorial/auto_scheduler_matmul_x86.rst.txt | 11 +-
docs/_sources/tutorial/autotvm_matmul_x86.rst.txt | 20 +-
docs/_sources/tutorial/autotvm_relay_x86.rst.txt | 59 +-
.../tutorial/cross_compilation_and_rpc.rst.txt | 2 +-
docs/_sources/tutorial/intro_topi.rst.txt | 2 +-
docs/_sources/tutorial/sg_execution_times.rst.txt | 26 +-
.../tutorial/tensor_expr_get_started.rst.txt | 46 +-
docs/commit_hash | 2 +-
docs/how_to/compile_models/from_darknet.html | 2 +-
docs/how_to/compile_models/from_mxnet.html | 2 +-
docs/how_to/compile_models/from_oneflow.html | 16 +-
docs/how_to/compile_models/from_pytorch.html | 11 +-
docs/how_to/compile_models/from_tensorflow.html | 2 +-
docs/how_to/compile_models/sg_execution_times.html | 22 +-
.../deploy_models/deploy_model_on_adreno.html | 3 +-
.../deploy_models/deploy_model_on_android.html | 2 +-
.../deploy_object_detection_pytorch.html | 48 +-
docs/how_to/deploy_models/deploy_prequantized.html | 9 +-
.../deploy_models/deploy_prequantized_tflite.html | 4 +-
docs/how_to/deploy_models/deploy_quantized.html | 2 +-
docs/how_to/deploy_models/deploy_ssd_gluoncv.html | 36 +-
docs/how_to/deploy_models/sg_execution_times.html | 22 +-
.../extend_tvm/bring_your_own_datatypes.html | 2 +-
docs/how_to/extend_tvm/sg_execution_times.html | 8 +-
docs/how_to/extend_tvm/use_pass_instrument.html | 16 +-
docs/how_to/optimize_operators/opt_conv_cuda.html | 2 +-
.../optimize_operators/opt_conv_tensorcore.html | 2 +-
docs/how_to/optimize_operators/opt_gemm.html | 16 +-
.../optimize_operators/sg_execution_times.html | 8 +-
.../sg_execution_times.html | 14 +-
.../tune_conv2d_layer_cuda.html | 7 +-
.../tune_with_autoscheduler/tune_network_cuda.html | 4 +-
.../tune_with_autoscheduler/tune_network_x86.html | 4 +-
.../tune_with_autoscheduler/tune_sparse_x86.html | 80 +-
.../tune_with_autotvm/sg_execution_times.html | 4 +-
.../how_to/tune_with_autotvm/tune_conv2d_cuda.html | 1140 ++++++++++----------
docs/how_to/work_with_microtvm/micro_autotune.html | 16 +-
docs/how_to/work_with_microtvm/micro_pytorch.html | 5 +-
docs/how_to/work_with_microtvm/micro_train.html | 16 +-
.../work_with_microtvm/sg_execution_times.html | 12 +-
.../how_to/work_with_relay/sg_execution_times.html | 8 +-
docs/how_to/work_with_schedules/intrin_math.html | 2 +-
.../work_with_schedules/sg_execution_times.html | 16 +-
docs/how_to/work_with_schedules/tensorize.html | 2 +-
.../api/doxygen/data__type_8h_source.html | 8 +-
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docs/reference/api/doxygen/dilate_8h_source.html | 2 +-
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docs/reference/api/doxygen/metadata_8h_source.html | 2 +-
docs/reference/api/doxygen/ndarray_8h_source.html | 2 +-
docs/reference/api/doxygen/nn_2bnn_8h_source.html | 2 +-
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docs/reference/api/doxygen/object_8h_source.html | 2 +-
.../api/doxygen/packed__func_8h_source.html | 64 +-
.../reference/api/doxygen/reduction_8h_source.html | 2 +-
.../api/doxygen/runtime_2module_8h_source.html | 2 +-
docs/reference/api/doxygen/stmt_8h_source.html | 2 +-
.../api/doxygen/stmt__functor_8h_source.html | 30 +-
.../api/doxygen/strided__slice_8h_source.html | 4 +-
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docs/reference/api/doxygen/tir_2ir_8h_source.html | 2 +-
docs/reference/api/doxygen/tir_2op_8h.html | 8 +-
docs/reference/api/doxygen/tir_2op_8h_source.html | 32 +-
.../doxygen/tir_2op__attr__types_8h_source.html | 2 +-
docs/reference/api/doxygen/topi_2nn_8h_source.html | 4 +-
.../api/doxygen/topi_2transform_8h_source.html | 4 +-
docs/reference/api/python/auto_scheduler.html | 4 +-
.../api/typedoc/classes/bytestreamreader.html | 12 +-
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docs/reference/api/typedoc/classes/dldatatype.html | 12 +-
docs/reference/api/typedoc/classes/dldevice.html | 10 +-
.../reference/api/typedoc/classes/environment.html | 12 +-
docs/reference/api/typedoc/classes/ffilibrary.html | 20 +-
.../api/typedoc/classes/graphexecutor.html | 16 +-
docs/reference/api/typedoc/classes/instance.html | 40 +-
docs/reference/api/typedoc/classes/memory.html | 34 +-
docs/reference/api/typedoc/classes/module.html | 10 +-
docs/reference/api/typedoc/classes/ndarray.html | 22 +-
.../api/typedoc/classes/packedfunccell.html | 6 +-
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docs/reference/api/typedoc/classes/scalar.html | 6 +-
.../api/typedoc/classes/webgpucontext.html | 12 +-
docs/reference/api/typedoc/enums/argtypecode.html | 30 +-
.../api/typedoc/enums/aynccallbackcode.html | 4 +-
.../api/typedoc/enums/dldatatypecode.html | 8 +-
.../api/typedoc/enums/rpcserverstate.html | 12 +-
docs/reference/api/typedoc/enums/sizeof.html | 18 +-
docs/reference/api/typedoc/index.html | 112 +-
.../api/typedoc/interfaces/disposable.html | 2 +-
.../api/typedoc/interfaces/functioninfo.html | 6 +-
.../api/typedoc/interfaces/libraryprovider.html | 4 +-
docs/searchindex.js | 2 +-
.../vta/tutorials/autotvm/sg_execution_times.html | 4 +-
.../tutorials/frontend/deploy_classification.html | 2 +-
.../vta/tutorials/frontend/deploy_detection.html | 2 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 6 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 7 +-
docs/tutorial/autotvm_matmul_x86.html | 20 +-
docs/tutorial/autotvm_relay_x86.html | 273 +++--
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/sg_execution_times.html | 30 +-
docs/tutorial/tensor_expr_get_started.html | 46 +-
157 files changed, 2045 insertions(+), 2270 deletions(-)
diff --git a/docs/_images/sphx_glr_micro_train_001.png b/docs/_images/sphx_glr_micro_train_001.png
index cdece017f1..58230570fb 100644
Binary files a/docs/_images/sphx_glr_micro_train_001.png and b/docs/_images/sphx_glr_micro_train_001.png differ
diff --git a/docs/_images/sphx_glr_micro_train_thumb.png b/docs/_images/sphx_glr_micro_train_thumb.png
index 3ea3b2a601..c7f45c5bc4 100644
Binary files a/docs/_images/sphx_glr_micro_train_thumb.png and b/docs/_images/sphx_glr_micro_train_thumb.png differ
diff --git a/docs/_sources/how_to/compile_models/from_darknet.rst.txt b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
index db3fea7f7e..7dadadabe7 100644
--- a/docs/_sources/how_to/compile_models/from_darknet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
@@ -315,7 +315,7 @@ The process is no different from other examples.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 10.168 seconds)
+ **Total running time of the script:** ( 1 minutes 11.752 seconds)
.. _sphx_glr_download_how_to_compile_models_from_darknet.py:
diff --git a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
index 3b8dd8aea7..a425f6ee50 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -115,7 +115,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip4df2b424-93b8-4131-9de0-6c69c9785930 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipad99cdc3-9bdb-4914-a4b4-f33edf155ba6 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
diff --git a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
index 2ee89cd762..400e61b680 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -116,7 +116,7 @@ Load a pretrained OneFlow model and save model
.. code-block:: none
Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
-
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77%|#######7 | 32.0M/41.5M [00:00<00:00, 39.0MB/s]
87%|########7 | 36.1M/41.5M [00:00<00:00, 39.5MB/s]
97%|#########6| 40.2M/41.5M [00:01<00:00, 34.6MB/s]
100%|##########| 41.5M/41.5M [00:01<00:00, 38.7MB/s]
+
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79%|#######9 | 32.8M/41.5M [00:00<00:00, 48.9MB/s]
92%|#########2| 38.3M/41.5M [00:00<00:00, 51.4MB/s]
100%|##########| 41.5M/41.5M [00:00<00:00, 44.5MB/s]
diff --git a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
index 0e5f7ba140..cb96176c57 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -98,7 +98,7 @@ Load a pretrained PyTorch model
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
-
0%| | 0.00/44.7M [00:00<?, ?B/s]
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76%|#######6 | 34.1M/44.7M [00:00<00:00, 46.6MB/s]
93%|#########2| 41.5M/44.7M [00:00<00:00, 55.0MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 56.3MB/s]
+
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32%|###2 | 14.3M/44.7M [00:00<00:00, 142MB/s]
62%|######2 | 27.9M/44.7M [00:00<00:00, 92.7MB/s]
86%|########5 | 38.3M/44.7M [00:00<00:00, 83.1MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 68.9MB/s]
diff --git a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
index fe78ad4a8c..2595783748 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -416,7 +416,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 11.071 seconds)
+ **Total running time of the script:** ( 1 minutes 13.893 seconds)
.. _sphx_glr_download_how_to_compile_models_from_tensorflow.py:
diff --git a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
index ccb057f05f..ee16cfb7a3 100644
--- a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
@@ -5,26 +5,26 @@
Computation times
=================
-**05:40.684** total execution time for **how_to_compile_models** files:
+**05:49.535** total execution time for **how_to_compile_models** files:
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:11.071 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:13.893 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:10.168 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:11.752 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 00:45.262 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 00:47.345 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:31.272 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:32.784 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:28.243 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:29.055 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:25.879 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:26.278 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:25.755 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:25.495 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:22.251 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:22.531 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:18.356 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:17.956 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.427 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.446 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
index 2c95e214c1..36855acf57 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
@@ -723,18 +723,13 @@ well as provides information about the model's performance
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 3348.4568 3345.1975 3361.9201 3344.0796 5.4964
+ 2547.1204 2547.1048 2554.2133 2542.3841 3.3906
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 0.780 seconds)
-
-
.. _sphx_glr_download_how_to_deploy_models_deploy_model_on_adreno.py:
.. only:: html
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
index e52c6a9f54..5a09cb0b35 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_android.rst.txt
@@ -433,7 +433,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.2571 16.4238 16.8795 15.6466 0.3999
+ 16.0696 15.9438 16.8597 15.8614 0.3103
diff --git a/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt b/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
index a5045a3a7e..4fa1bb93b3 100644
--- a/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
@@ -127,7 +127,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=MaskRCNN_ResNet50_FPN_Weights.COCO_V1`. You can also use `weights=MaskRCNN_ResNet50_FPN_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
-
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+
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/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torch/nn/functional.py:3897: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
for i in range(dim)
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torchvision/models/detection/anchor_utils.py:124: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
@@ -296,7 +296,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 3 minutes 11.704 seconds)
+ **Total running time of the script:** ( 3 minutes 16.695 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_object_detection_pytorch.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
index aebc8e3e38..3e02491b48 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -236,7 +236,7 @@ training. Other models require a full post training calibration.
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=MobileNet_V2_Weights.IMAGENET1K_V1`. You can also use `weights=MobileNet_V2_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
-
0%| | 0.00/13.6M [00:00<?, ?B/s]
83%|########3 | 11.3M/13.6M [00:00<00:00, 119MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 128MB/s]
+
0%| | 0.00/13.6M [00:00<?, ?B/s]
47%|####6 | 6.30M/13.6M [00:00<00:00, 63.2MB/s]
91%|#########1| 12.3M/13.6M [00:00<00:00, 40.5MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 46.3MB/s]
@@ -418,7 +418,7 @@ Here we give an example of how to measure performance of TVM compiled models.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 90.2933 90.2321 91.3954 89.9113 0.2483
+ 90.3714 90.2342 93.3864 90.0915 0.5081
@@ -467,7 +467,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 5.237 seconds)
+ **Total running time of the script:** ( 1 minutes 6.569 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_prequantized.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt b/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
index 86e5f6239e..9b0ece785e 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
@@ -432,7 +432,7 @@ Here we give an example of how to measure performance of TVM compiled models.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 119.7400 119.7851 125.3382 117.6290 0.9048
+ 120.7364 120.6843 125.5776 120.0880 0.5749
@@ -469,7 +469,7 @@ Here we give an example of how to measure performance of TVM compiled models.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 23.226 seconds)
+ **Total running time of the script:** ( 2 minutes 24.507 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_prequantized_tflite.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
index 3ae5e83bee..c0ca8953b2 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -253,7 +253,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 33.840 seconds)
+ **Total running time of the script:** ( 1 minutes 34.139 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_quantized.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
index f7bab858bf..c8ed169503 100644
--- a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
@@ -166,7 +166,7 @@ Convert and compile model for CPU.
data: None
input_sym_arg_type = in_param.infer_type()[0]
Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/ssd_512_resnet50_v1_voc-9c8b225a.zip...
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@@ -242,7 +242,7 @@ Display result
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 3 minutes 5.044 seconds)
+ **Total running time of the script:** ( 3 minutes 11.827 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_ssd_gluoncv.py:
diff --git a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
index ce765136cc..8519f7cb14 100644
--- a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
@@ -5,26 +5,26 @@
Computation times
=================
-**13:44.102** total execution time for **how_to_deploy_models** files:
+**13:51.776** total execution time for **how_to_deploy_models** files:
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:11.704 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:16.695 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 03:05.044 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 03:11.827 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 02:23.226 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 02:24.507 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:33.840 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:34.139 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:05.237 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:06.569 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 01:00.780 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 00:51.905 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:34.912 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:35.780 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:24.859 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:25.335 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:24.493 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:25.013 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.006 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.007 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
index 42602db13d..42d99aea33 100644
--- a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
@@ -472,7 +472,7 @@ First let us define two helper functions to get the mobilenet model and a cat im
.. code-block:: none
- Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip4824e17e-a166-4fed-b828-ee461dc0ac4d from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip990560b3-c5a6-485d-bf0e-1e676b72ad40 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
diff --git a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
index a09c239061..3659ca3a68 100644
--- a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
Computation times
=================
-**00:46.868** total execution time for **how_to_extend_tvm** files:
+**00:47.833** total execution time for **how_to_extend_tvm** files:
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:43.502 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:44.347 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.341 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.444 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.016 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.034 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``) | 00:00.008 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt b/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
index 3b83d6b873..3a78c5424a 100644
--- a/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
@@ -216,10 +216,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 7130us [7130us] (46.31%; 46.31%)
- FoldScaleAxis: 8267us [6us] (53.69%; 53.69%)
- FoldConstant: 8261us [1688us] (53.65%; 99.93%)
- InferType: 6573us [6573us] (42.69%; 79.57%)
+ InferType: 7283us [7283us] (46.20%; 46.20%)
+ FoldScaleAxis: 8481us [7us] (53.80%; 53.80%)
+ FoldConstant: 8475us [1707us] (53.76%; 99.92%)
+ InferType: 6768us [6768us] (42.93%; 79.86%)
@@ -258,10 +258,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 6608us [6608us] (45.09%; 45.09%)
- FoldScaleAxis: 8046us [5us] (54.91%; 54.91%)
- FoldConstant: 8041us [1662us] (54.87%; 99.94%)
- InferType: 6379us [6379us] (43.53%; 79.33%)
+ InferType: 6747us [6747us] (44.98%; 44.98%)
+ FoldScaleAxis: 8254us [5us] (55.02%; 55.02%)
+ FoldConstant: 8249us [1693us] (54.99%; 99.94%)
+ InferType: 6556us [6556us] (43.71%; 79.48%)
diff --git a/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt b/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
index caa63fba2d..25aadb58b8 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
@@ -340,7 +340,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 53.060577 ms
+ Convolution: 48.410495 ms
diff --git a/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt b/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
index 1a378c019e..a61c1b1966 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
@@ -657,7 +657,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 13.369591 ms
+ conv2d with tensor core: 13.354384 ms
diff --git a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
index a24fec0fbb..9a3f3952dd 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -143,8 +143,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.018622
- Baseline: 3.335183
+ Numpy running time: 0.019184
+ Baseline: 3.423127
@@ -238,7 +238,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.307949
+ Opt1: 0.312657
@@ -340,7 +340,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.329713
+ Opt2: 0.342196
@@ -435,7 +435,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.115594
+ Opt3: 0.119240
@@ -559,7 +559,7 @@ flattening.
.. code-block:: none
- Opt4: 0.109935
+ Opt4: 0.109000
@@ -680,7 +680,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.116148
+ Opt5: 0.111107
@@ -804,7 +804,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
.. code-block:: none
- Opt6: 0.152512
+ Opt6: 0.147616
diff --git a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
index 886339d911..129f99d105 100644
--- a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
Computation times
=================
-**00:35.205** total execution time for **how_to_optimize_operators** files:
+**00:35.375** total execution time for **how_to_optimize_operators** files:
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:32.436 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:32.677 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.573 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.565 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.197 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.133 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
index d29d3cb1d4..85b8ed08d0 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/sg_execution_times.rst.txt
@@ -5,18 +5,18 @@
Computation times
=================
-**08:50.704** total execution time for **how_to_tune_with_autoscheduler** files:
+**09:07.560** total execution time for **how_to_tune_with_autoscheduler** files:
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 05:27.254 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 05:41.793 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:31.095 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:33.478 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:01.281 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:01.827 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:28.056 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:27.648 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:11.974 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:11.843 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:11.045 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:10.971 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
index c9169d1c43..77cbcc5044 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
@@ -206,6 +206,13 @@ file and apply it.
+.. rst-class:: sphx-glr-script-out
+
+ .. code-block:: none
+
+
+ .T
+
@@ -770,7 +777,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.358 ms
+ Execution time of this operator: 0.350 ms
@@ -1377,7 +1384,7 @@ In the example below we resume the status and do more 5 trials.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 5 minutes 27.254 seconds)
+ **Total running time of the script:** ( 5 minutes 41.793 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
index 1a4f48d12d..747f01b650 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_cuda.rst.txt
@@ -643,7 +643,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 7.8974 7.8946 7.9083 7.8892 0.0080
+ 7.8518 7.8494 7.8611 7.8449 0.0068
@@ -671,7 +671,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 1.281 seconds)
+ **Total running time of the script:** ( 1 minutes 1.827 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_cuda.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
index 823712101e..3270b704ca 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
@@ -662,7 +662,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 755.4578 755.6234 755.8838 754.8663 0.4316
+ 756.5267 757.7776 759.3899 752.4125 2.9827
@@ -690,7 +690,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 31.095 seconds)
+ **Total running time of the script:** ( 1 minutes 33.478 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_x86.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
index e961dcf8fc..9a06ab3bfe 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
@@ -386,75 +386,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [128, 512], []),
compute: Buffer(compute_2: Pointer(float32), float32, [128, 512], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute} {
- for (i0.outer.i1.outer.fused: int32, 0, 64) "parallel" {
- allocate(compute_3: Pointer(global float32), float32, [1024]), storage_scope = global {
+ for (i0.outer.i1.outer.fused: int32, 0, 32) "parallel" {
+ allocate(compute_3: Pointer(global float32), float32, [2048]), storage_scope = global {
for (nb_j.inner: int32, 0, 2) {
- for (i.inner.init: int32, 0, 32) {
- let cse_var_1: int32 = ((i.inner.init*32) + (nb_j.inner*16))
- {
- compute_4: Buffer(compute_3, float32, [1024], [])[cse_var_1] = 0f32
- compute_4[(cse_var_1 + 1)] = 0f32
- compute_4[(cse_var_1 + 2)] = 0f32
- compute_4[(cse_var_1 + 3)] = 0f32
- compute_4[(cse_var_1 + 4)] = 0f32
- compute_4[(cse_var_1 + 5)] = 0f32
- compute_4[(cse_var_1 + 6)] = 0f32
- compute_4[(cse_var_1 + 7)] = 0f32
- compute_4[(cse_var_1 + 8)] = 0f32
- compute_4[(cse_var_1 + 9)] = 0f32
- compute_4[(cse_var_1 + 10)] = 0f32
- compute_4[(cse_var_1 + 11)] = 0f32
- compute_4[(cse_var_1 + 12)] = 0f32
- compute_4[(cse_var_1 + 13)] = 0f32
- compute_4[(cse_var_1 + 14)] = 0f32
- compute_4[(cse_var_1 + 15)] = 0f32
+ for (i.inner.init: int32, 0, 64) {
+ for (j.init: int32, 0, 16) {
+ compute_4: Buffer(compute_3, float32, [2048], [])[(((i.inner.init*32) + (nb_j.inner*16)) + j.init)] = 0f32
}
}
- for (elem_idx: int32, 0, let cse_var_2: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_15: Buffer(placeholder_13, int32, [33], [])[(cse_var_2 + 1)] - placeholder_15[cse_var_2])) {
- for (i.inner: int32, 0, 32) {
- let cse_var_21: int32 = (elem_idx*16)
- let cse_var_20: int32 = ((i.inner*32) + (nb_j.inner*16))
- let cse_var_19: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
- let cse_var_18: int32 = ((floordiv(i0.outer.i1.outer.fused, 16)*8192) + (i.inner*256))
- let cse_var_17: int32 = (cse_var_20 + 9)
- let cse_var_16: int32 = (cse_var_20 + 8)
- let cse_var_15: int32 = (cse_var_20 + 7)
- let cse_var_14: int32 = (cse_var_20 + 6)
- let cse_var_13: int32 = (cse_var_20 + 5)
- let cse_var_12: int32 = (cse_var_20 + 4)
- let cse_var_11: int32 = (cse_var_20 + 3)
- let cse_var_10: int32 = (cse_var_20 + 2)
- let cse_var_9: int32 = (cse_var_20 + 15)
- let cse_var_8: int32 = (cse_var_20 + 14)
- let cse_var_7: int32 = (cse_var_20 + 13)
- let cse_var_6: int32 = (cse_var_20 + 12)
- let cse_var_5: int32 = (cse_var_20 + 11)
- let cse_var_4: int32 = (cse_var_20 + 10)
- let cse_var_3: int32 = (cse_var_20 + 1)
- {
- compute_4[cse_var_20] = (compute_4[cse_var_20] + (placeholder_16: Buffer(placeholder_11, float32, [78656], [])[((placeholder_15[cse_var_19]*16) + cse_var_21)]*max(placeholder_17: Buffer(placeholder_10, float32, [32768], [])[(cse_var_18 + placeholder_18: Buffer(placeholder_12, int32, [4916], [])[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_3] = (compute_4[cse_var_3] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 1)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_10] = (compute_4[cse_var_10] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 2)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_11] = (compute_4[cse_var_11] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 3)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_12] = (compute_4[cse_var_12] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 4)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_13] = (compute_4[cse_var_13] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 5)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_14] = (compute_4[cse_var_14] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 6)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_15] = (compute_4[cse_var_15] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 7)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_16] = (compute_4[cse_var_16] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 8)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_17] = (compute_4[cse_var_17] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 9)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_4] = (compute_4[cse_var_4] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 10)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_5] = (compute_4[cse_var_5] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 11)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_6] = (compute_4[cse_var_6] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 12)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_7] = (compute_4[cse_var_7] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 13)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_8] = (compute_4[cse_var_8] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 14)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_9] = (compute_4[cse_var_9] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 15)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, let cse_var_1: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_15: Buffer(placeholder_13, int32, [33], [])[(cse_var_1 + 1)] - placeholder_15[cse_var_1])) {
+ for (i.inner: int32, 0, 64) {
+ for (j: int32, 0, 16) {
+ let cse_var_3: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_2: int32 = (((i.inner*32) + (nb_j.inner*16)) + j)
+ compute_4[cse_var_2] = (compute_4[cse_var_2] + (placeholder_16: Buffer(placeholder_11, float32, [78656], [])[(((placeholder_15[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder_17: Buffer(placeholder_10, float32, [32768], [])[(((floordiv(i0.outer.i1.outer.fused, 16)*16384) + (i.inner*256)) + placeholder_18: Buffer(placeholder_12, int32, [4916], [])[(placeholder_15[cse_var_3] + elem_idx)])], 0f32)))
}
}
}
}
- for (i0.inner: int32, 0, 32) {
- let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*16384) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32))
- compute_5: Buffer(compute_2, float32, [65536], [])[ramp(cse_var_22, 1, 32)] = max((compute_4[ramp((i0.inner*32), 1, 32)] + placeholder_19: Buffer(placeholder_14, float32, [65536], [])[ramp(cse_var_22, 1, 32)]), broadcast(0f32, 32))
+ for (i0.inner: int32, 0, 64) {
+ for (i1.inner: int32, 0, 32) {
+ let cse_var_4: int32 = ((((floordiv(i0.outer.i1.outer.fused, 16)*32768) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32)) + i1.inner)
+ compute_5: Buffer(compute_2, float32, [65536], [])[cse_var_4] = max((compute_4[((i0.inner*32) + i1.inner)] + placeholder_19: Buffer(placeholder_14, float32, [65536], [])[cse_var_4]), 0f32)
+ }
}
}
}
@@ -510,7 +464,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 1.765 ms
+ Execution time of this operator: 1.814 ms
diff --git a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
index b1ef5b9d50..bb3b796f06 100644
--- a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:39.839** total execution time for **how_to_tune_with_autotvm** files:
+**00:35.571** total execution time for **how_to_tune_with_autotvm** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:39.805 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:35.535 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``) | 00:00.020 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt b/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
index 1ca3170e6c..a9861d4cf8 100644
--- a/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/tune_conv2d_cuda.rst.txt
@@ -285,21 +285,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -317,11 +317,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -341,21 +341,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -373,11 +373,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -387,161 +387,132 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 128, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5808757
- No: 2 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 742, in __call__
- yield remote, remote.load_module(os.path.split(build_result.filename)[1])
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/workspace/python/tvm/runtime/module.py", line 357, in evaluator
- blob = feval(*args)
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 16, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2157448
+ No: 2 GFLOPS: 2.33/2.33 result: MeasureResult(costs=(0.09927782425,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.730562210083008, timestamp=1670200892.4803033) [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4520513
+ No: 3 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
+ func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
+ func = build(s, args, target_host=task.target_host, runtime=runtime)
+ File "/workspace/python/tvm/driver/build_module.py", line 227, in build
+ input_mod = lower(inputs, args, name=name, binds=binds)
+ File "/workspace/python/tvm/driver/build_module.py", line 134, in lower
+ return ffi.lower_schedule(inp, args, name, binds, simple_mode)
File "tvm/_ffi/_cython/./packed_func.pxi", line 331, in tvm._ffi._cy3.core.PackedFuncBase.__call__
- File "tvm/_ffi/_cython/./packed_func.pxi", line 262, in tvm._ffi._cy3.core.FuncCall
- File "tvm/_ffi/_cython/./packed_func.pxi", line 251, in tvm._ffi._cy3.core.FuncCall3
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 276, in tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 181, in tvm._ffi._cy3.core.CHECK_CALL
tvm._ffi.base.TVMError: Traceback (most recent call last):
- 4: TVMFuncCall
+ 24: TVMFuncCall
at ../src/runtime/c_runtime_api.cc:477
- 3: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
- 2: tvm::runtime::RPCWrappedFunc::operator()(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
- at ../src/runtime/rpc/rpc_module.cc:129
- 1: tvm::runtime::RPCClientSession::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)> const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1012
- 0: tvm::runtime::RPCEndpoint::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)>)
- at ../src/runtime/rpc/rpc_endpoint.cc:804
- File "../src/runtime/rpc/rpc_endpoint.cc", line 804
- TVMError:
- ---------------------------------------------------------------
- An error occurred during the execution of TVM.
- For more information, please see: https://tvm.apache.org/docs/errors.html
- ---------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=kShutdown
-
- During handling of the above exception, another exception occurred:
-
- Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/usr/lib/python3.7/contextlib.py", line 130, in __exit__
- self.gen.throw(type, value, traceback)
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 746, in __call__
- remote.remove(build_result.filename)
- File "/workspace/python/tvm/rpc/client.py", line 144, in remove
- self._remote_funcs["remove"] = self.get_function("tvm.rpc.server.remove")
- File "/workspace/python/tvm/rpc/client.py", line 72, in get_function
- return self._sess.get_function(name)
- File "/workspace/python/tvm/runtime/module.py", line 171, in get_function
- self.handle, c_str(name), ctypes.c_int(query_imports), ctypes.byref(ret_handle)
- File "/workspace/python/tvm/_ffi/base.py", line 348, in check_call
- raise get_last_ffi_error()
- tvm._ffi.base.TVMError: Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCallKeywords
- 18: _PyEval_EvalFrameDefault
- 17: _PyFunction_FastCallKeywords
- 16: _PyEval_EvalCodeWithName
- 15: _PyEval_EvalFrameDefault
- 14: 0x0000000000537c30
- 13: _PyObject_FastCallKeywords
- 12: 0x00007fc5ed7edfa2
- 11: _ctypes_callproc
- 10: ffi_call
- 9: ffi_call_unix64
- 8: TVMModGetFunction
- at ../src/runtime/c_runtime_api.cc:408
- 7: tvm::runtime::ModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool)
- at ../src/runtime/module.cc:66
- 6: tvm::runtime::RPCModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)
- at ../src/runtime/rpc/rpc_module.cc:185
- 5: tvm::runtime::RPCClientSession::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1007
- 4: tvm::runtime::TVMRetValue tvm::runtime::RPCEndpoint::SysCallRemote<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(tvm::runtime::RPCCode, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.h:223
- 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(int&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
at ../include/tvm/runtime/packed_func.h:1213
0: operator()
- at ../src/runtime/rpc/rpc_endpoint.cc:684
- File "../src/runtime/rpc/rpc_endpoint.cc", line 684
- TVMError:
- ---------------------------------------------------------------
- An error occurred during the execution of TVM.
- For more information, please see: https://tvm.apache.org/docs/errors.html
- ---------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=1
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel
Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCall [('tile_f', [-1, 16, 1, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7366889
- No: 3 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ 24: TVMFuncCall
+ at ../src/runtime/c_runtime_api.cc:477
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
+ 2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 1: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 0: operator()
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 1, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 256]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10250404
+ No: 4 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -561,21 +532,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -593,11 +564,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -617,21 +588,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -649,11 +620,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -663,8 +634,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 1, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,916283
- No: 4 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 4, 8]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 256, 2]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8391612
+ No: 5 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -684,21 +655,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -716,11 +687,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -740,21 +711,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -772,11 +743,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -786,8 +757,9 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2792794
- No: 5 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 4, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 256]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6961579
+ No: 6 GFLOPS: 58.51/58.51 result: MeasureResult(costs=(0.003956673818181818,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.059903621673584, timestamp=1670200897.6246755) [('tile_f', [-1, 2, 8, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 64]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2290448
+ No: 7 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -807,21 +779,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -839,11 +811,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -863,21 +835,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -895,11 +867,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -909,8 +881,9 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 256]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9658217
- No: 6 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 1, 8]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4351736
+ No: 8 GFLOPS: 56.48/58.51 result: MeasureResult(costs=(0.00409861752,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.9851655960083008, timestamp=1670200898.290892) [('tile_f', [-1, 1, 4, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 512, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,32235
+ No: 9 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -930,21 +903,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -962,11 +935,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -986,21 +959,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1018,11 +991,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1032,8 +1005,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 1]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,3128666
- No: 7 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 1, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3857586
+ No: 10 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1053,21 +1026,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1085,11 +1058,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1109,21 +1082,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1141,11 +1114,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1155,8 +1128,9 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 8, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7467584
- No: 8 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 16, 2]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 1, 32]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,1886149
+ No: 11 GFLOPS: 5.26/58.51 result: MeasureResult(costs=(0.043981414749999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.0867502689361572, timestamp=1670200900.554806) [('tile_f', [-1, 2, 2, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 64, 2]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,5089985
+ No: 12 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1176,21 +1150,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1208,11 +1182,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1232,21 +1206,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1264,11 +1238,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1278,11 +1252,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5598341
- No: 9 GFLOPS: 34.16/34.16 result: MeasureResult(costs=(0.00677683211764706,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.503911018371582, timestamp=1670035927.063999) [('tile_f', [-1, 8, 2, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 8, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2371447
- No: 10 GFLOPS: 10.46/34.16 result: MeasureResult(costs=(0.022140299333333332,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.149139404296875, timestamp=1670035927.952396) [('tile_f', [-1, 1, 4, 4]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 16, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8405875
- No: 11 GFLOPS: 76.71/76.71 result: MeasureResult(costs=(0.0030177834411764704,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3312666416168213, timestamp=1670035928.6008291) [('tile_f', [-1, 4, 2, 4]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 16, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2372810
- No: 12 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 128, 2]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2771512
+ No: 13 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1302,21 +1273,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1334,11 +1305,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1358,21 +1329,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1390,11 +1361,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1404,8 +1375,9 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 2, 2]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 16]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2841804
- No: 13 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7771677
+ No: 14 GFLOPS: 70.65/70.65 result: MeasureResult(costs=(0.0032768214375000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.235529184341431, timestamp=1670200904.9939046) [('tile_f', [-1, 2, 16, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 8]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,8817466
+ No: 15 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1425,21 +1397,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1457,11 +1429,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1481,21 +1453,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1513,11 +1485,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1527,8 +1499,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 16, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,953735
- No: 14 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 4, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 16]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1486785
+ No: 16 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1548,21 +1520,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1580,11 +1552,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1604,21 +1576,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1636,11 +1608,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1650,9 +1622,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 128, 4, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3620126
- No: 15 GFLOPS: 17.91/76.71 result: MeasureResult(costs=(0.012923107555555556,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.104569911956787, timestamp=1670035930.9178731) [('tile_f', [-1, 8, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8186523
- No: 16 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 4]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5824854
+ No: 17 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1672,21 +1643,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1704,11 +1675,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1728,21 +1699,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1760,11 +1731,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1774,161 +1745,131 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 32, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 64]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6941042
- No: 17 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 742, in __call__
- yield remote, remote.load_module(os.path.split(build_result.filename)[1])
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/workspace/python/tvm/runtime/module.py", line 357, in evaluator
- blob = feval(*args)
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9904275
+ No: 18 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
+ func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
+ func = build(s, args, target_host=task.target_host, runtime=runtime)
+ File "/workspace/python/tvm/driver/build_module.py", line 227, in build
+ input_mod = lower(inputs, args, name=name, binds=binds)
+ File "/workspace/python/tvm/driver/build_module.py", line 134, in lower
+ return ffi.lower_schedule(inp, args, name, binds, simple_mode)
File "tvm/_ffi/_cython/./packed_func.pxi", line 331, in tvm._ffi._cy3.core.PackedFuncBase.__call__
- File "tvm/_ffi/_cython/./packed_func.pxi", line 262, in tvm._ffi._cy3.core.FuncCall
- File "tvm/_ffi/_cython/./packed_func.pxi", line 251, in tvm._ffi._cy3.core.FuncCall3
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 276, in tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 181, in tvm._ffi._cy3.core.CHECK_CALL
tvm._ffi.base.TVMError: Traceback (most recent call last):
- 4: TVMFuncCall
+ 24: TVMFuncCall
at ../src/runtime/c_runtime_api.cc:477
- 3: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
- 2: tvm::runtime::RPCWrappedFunc::operator()(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
- at ../src/runtime/rpc/rpc_module.cc:129
- 1: tvm::runtime::RPCClientSession::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)> const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1012
- 0: tvm::runtime::RPCEndpoint::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)>)
- at ../src/runtime/rpc/rpc_endpoint.cc:804
- File "../src/runtime/rpc/rpc_endpoint.cc", line 804
- TVMError:
- ---------------------------------------------------------------
- An error occurred during the execution of TVM.
- For more information, please see: https://tvm.apache.org/docs/errors.html
- ---------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=kShutdown
-
- During handling of the above exception, another exception occurred:
-
- Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/usr/lib/python3.7/contextlib.py", line 130, in __exit__
- self.gen.throw(type, value, traceback)
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 746, in __call__
- remote.remove(build_result.filename)
- File "/workspace/python/tvm/rpc/client.py", line 144, in remove
- self._remote_funcs["remove"] = self.get_function("tvm.rpc.server.remove")
- File "/workspace/python/tvm/rpc/client.py", line 72, in get_function
- return self._sess.get_function(name)
- File "/workspace/python/tvm/runtime/module.py", line 171, in get_function
- self.handle, c_str(name), ctypes.c_int(query_imports), ctypes.byref(ret_handle)
- File "/workspace/python/tvm/_ffi/base.py", line 348, in check_call
- raise get_last_ffi_error()
- tvm._ffi.base.TVMError: Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCallKeywords
- 18: _PyEval_EvalFrameDefault
- 17: _PyFunction_FastCallKeywords
- 16: _PyEval_EvalCodeWithName
- 15: _PyEval_EvalFrameDefault
- 14: 0x0000000000537c30
- 13: _PyObject_FastCallKeywords
- 12: 0x00007f2df7882fa2
- 11: _ctypes_callproc
- 10: ffi_call
- 9: ffi_call_unix64
- 8: TVMModGetFunction
- at ../src/runtime/c_runtime_api.cc:408
- 7: tvm::runtime::ModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool)
- at ../src/runtime/module.cc:66
- 6: tvm::runtime::RPCModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)
- at ../src/runtime/rpc/rpc_module.cc:185
- 5: tvm::runtime::RPCClientSession::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1007
- 4: tvm::runtime::TVMRetValue tvm::runtime::RPCEndpoint::SysCallRemote<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(tvm::runtime::RPCCode, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.h:223
- 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(int&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
at ../include/tvm/runtime/packed_func.h:1213
0: operator()
- at ../src/runtime/rpc/rpc_endpoint.cc:684
- File "../src/runtime/rpc/rpc_endpoint.cc", line 684
- TVMError:
- ---------------------------------------------------------------
- An error occurred during the execution of TVM.
- For more information, please see: https://tvm.apache.org/docs/errors.html
- ---------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=1
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel
Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCall [('tile_f', [-1, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5691725
- No: 18 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ 24: TVMFuncCall
+ at ../src/runtime/c_runtime_api.cc:477
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
+ 2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 1: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 0: operator()
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 512, 1, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9075889
+ No: 19 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1948,21 +1889,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1980,11 +1921,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2004,21 +1945,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2036,11 +1977,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2050,8 +1991,8 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 4, 8]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4987332
- No: 19 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 4]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6140977
+ No: 20 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -2071,21 +2012,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2103,11 +2044,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2127,21 +2068,21 @@ for this template
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2159,11 +2100,11 @@ for this template
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2173,8 +2114,7 @@ for this template
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
- tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 1, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9757168
- No: 20 GFLOPS: 274.32/274.32 result: MeasureResult(costs=(0.0008439045105263158,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.268427848815918, timestamp=1670035938.1445587) [('tile_f', [-1, 4, 2, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,207252
+ tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 1, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,3302843
@@ -2229,9 +2169,9 @@ and measure running time.
Finish loading 20 records
Best config:
- [('tile_f', [-1, 4, 2, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,207252
+ [('tile_f', [-1, 2, 16, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 8]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,8817466
Finish loading 20 records
- Time cost of this operator: 0.001213
+ Time cost of this operator: 0.003642
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
index 2a47448277..ef76520c1d 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_autotune.rst.txt
@@ -329,10 +329,10 @@ Timing the untuned program
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 367.1 98.918 (1, 2, 10, 10, 3) 2 1 [367.1]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.039 0.819 (1, 6, 10, 10) 1 1 [3.039]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.263 (1, 1, 10, 10, 3) 1 1 [0.976]
- Total_time - 371.115 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 314.5 98.725 (1, 2, 10, 10, 3) 2 1 [314.5]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.085 0.968 (1, 6, 10, 10) 1 1 [3.085]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.306 (1, 1, 10, 10, 3) 1 1 [0.976]
+ Total_time - 318.561 - - - - -
@@ -397,10 +397,10 @@ Timing the tuned program
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 103.7 97.508 (1, 6, 10, 10, 1) 2 1 [103.7]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.8 1.692 (1, 6, 10, 10) 1 1 [1.8]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.851 0.8 (1, 3, 10, 10, 1) 1 1 [0.851]
- Total_time - 106.35 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 110.0 97.669 (1, 6, 10, 10, 1) 2 1 [110.0]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.78 1.58 (1, 6, 10, 10) 1 1 [1.78]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.846 0.751 (1, 3, 10, 10, 1) 1 1 [0.846]
+ Total_time - 112.626 - - - - -
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
index f47a66844b..38bd59cbe2 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
@@ -109,7 +109,7 @@ download a cat image and preprocess it to use as the model input.
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torch/ao/quantization/utils.py:281: UserWarning: must run observer before calling calculate_qparams. Returning default values.
"must run observer before calling calculate_qparams. " +
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
-
0%| | 0.00/3.42M [00:00<?, ?B/s]
61%|###### | 2.09M/3.42M [00:00<00:00, 16.7MB/s]
100%|##########| 3.42M/3.42M [00:00<00:00, 25.5MB/s]
+
0%| | 0.00/3.42M [00:00<?, ?B/s]
100%|##########| 3.42M/3.42M [00:00<00:00, 225MB/s]
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
return LooseVersion(torch_ver) > ver
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/setuptools/_distutils/version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -314,7 +314,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 2.283 seconds)
+ **Total running time of the script:** ( 1 minutes 3.380 seconds)
.. _sphx_glr_download_how_to_work_with_microtvm_micro_pytorch.py:
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt
index 6877a057a8..3100301ef3 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt
@@ -225,7 +225,7 @@ take about **2 minutes** to download the Stanford Cars, while COCO 2017 validati
.. code-block:: none
- '/tmp/tmp5aob5h71/images/random'
+ '/tmp/tmpiijl6bff/images/random'
@@ -316,7 +316,7 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. image-sg:: /how_to/work_with_microtvm/images/sphx_glr_micro_train_001.png
- :alt: [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0]
+ :alt: [0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]
:srcset: /how_to/work_with_microtvm/images/sphx_glr_micro_train_001.png
:class: sphx-glr-single-img
@@ -325,8 +325,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. code-block:: none
- /tmp/tmp5aob5h71/images/target contains 8144 images
- /tmp/tmp5aob5h71/images/random contains 5000 images
+ /tmp/tmpiijl6bff/images/target contains 8144 images
+ /tmp/tmpiijl6bff/images/random contains 5000 images
@@ -501,13 +501,13 @@ the time on our validation set).
.. code-block:: none
Epoch 1/3
- 328/328 - 47s - loss: 0.2129 - accuracy: 0.9253 - val_loss: 0.1029 - val_accuracy: 0.9637 - 47s/epoch - 144ms/step
+ 328/328 - 47s - loss: 0.2187 - accuracy: 0.9265 - val_loss: 0.1272 - val_accuracy: 0.9573 - 47s/epoch - 144ms/step
Epoch 2/3
- 328/328 - 44s - loss: 0.1026 - accuracy: 0.9628 - val_loss: 0.0844 - val_accuracy: 0.9649 - 44s/epoch - 134ms/step
+ 328/328 - 43s - loss: 0.0993 - accuracy: 0.9654 - val_loss: 0.1068 - val_accuracy: 0.9634 - 43s/epoch - 133ms/step
Epoch 3/3
- 328/328 - 44s - loss: 0.0672 - accuracy: 0.9750 - val_loss: 0.0824 - val_accuracy: 0.9687 - 44s/epoch - 133ms/step
+ 328/328 - 43s - loss: 0.0688 - accuracy: 0.9741 - val_loss: 0.1070 - val_accuracy: 0.9660 - 43s/epoch - 132ms/step
- <keras.callbacks.History object at 0x7fc539eb1f90>
+ <keras.callbacks.History object at 0x7ff6d148bc10>
@@ -864,7 +864,7 @@ Arduino tutorial for how to do that `on GitHub <https://github.com/guberti/tvm-a
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 4 minutes 40.333 seconds)
+ **Total running time of the script:** ( 4 minutes 24.505 seconds)
.. _sphx_glr_download_how_to_work_with_microtvm_micro_train.py:
diff --git a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
index 5e8dffd93a..9663019edb 100644
--- a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
@@ -5,18 +5,18 @@
Computation times
=================
-**06:42.865** total execution time for **how_to_work_with_microtvm** files:
+**06:29.085** total execution time for **how_to_work_with_microtvm** files:
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:40.333 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:24.505 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:02.283 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:03.380 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:48.842 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:49.605 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:07.711 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:07.783 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.693 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.809 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_microtvm_micro_reference_vm.py` (``micro_reference_vm.py``) | 00:00.001 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
index ce83a86ad4..76b6cc8790 100644
--- a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
Computation times
=================
-**00:43.496** total execution time for **how_to_work_with_relay** files:
+**00:43.782** total execution time for **how_to_work_with_relay** files:
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:32.063 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:32.075 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:10.094 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:10.206 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.333 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.494 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``) | 00:00.007 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
index 44863f34d8..d94d2a5642 100644
--- a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
@@ -261,7 +261,7 @@ The following example customizes CUDA lowering rule for :code:`exp`.
.. code-block:: none
- <function my_cuda_math_rule at 0x7fc53a9b1290>
+ <function my_cuda_math_rule at 0x7ff6d20205f0>
diff --git a/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt b/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
index 67fb3cf9a7..5253b61a5f 100644
--- a/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/sg_execution_times.rst.txt
@@ -5,22 +5,22 @@
Computation times
=================
-**00:08.118** total execution time for **how_to_work_with_schedules** files:
+**00:04.935** total execution time for **how_to_work_with_schedules** files:
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:05.696 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:02.418 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.095 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.157 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.565 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.574 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.547 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.566 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.113 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.115 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.050 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.028 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.029 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.023 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.024 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
index e468cbccb4..ae654b49f5 100644
--- a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
@@ -343,7 +343,7 @@ The importing needs to happen before the tensorized GEMV being executed.
B: Buffer(B_2: Pointer(float32), float32, [512, 64], []),
C: Buffer(C_2: Pointer(float32), float32, [1024, 512], [])}
buffer_map = {A_1: A, B_1: B, C_1: C} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpg6udtyna/input0.cc'\nsource_filename = \"/tmp/tmpg6udtyna/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpdqg1gu7i/input0.cc'\nsource_filename = \"/tmp/tmpdqg1gu7i/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
for (i, 0, 1024) {
for (j.outer: int32, 0, 32) {
@tir.call_extern("gemv_update", @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), C_2, ((i*512) + (j.outer*16)), 16, 2, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), A_2, (i*64), 64, 1, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), B_2, (j.outer*1024), 1024, 1, dtype=handle), 16, 64, 64, dtype=int32)
diff --git a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
index 6bfadf90b7..a206e7e181 100644
--- a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:25.782** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:25.488** total execution time for **topic_vta_tutorials_autotvm** files:
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:25.776 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:25.482 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``) | 00:00.006 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
index 6b8160d11b..85ed98deb2 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -289,7 +289,7 @@ The compilation steps are:
DeprecationWarning,
/workspace/vta/tutorials/frontend/deploy_classification.py:213: DeprecationWarning: legacy graph executor behavior of producing json / lib / params will be removed in the next release. Please see documents of tvm.contrib.graph_executor.GraphModule for the new recommended usage.
relay_prog, target=tvm.target.Target(target, host=env.target_host), params=params
- resnet18_v1 inference graph built in 28.24s!
+ resnet18_v1 inference graph built in 28.78s!
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
index 6eab8b130f..a7406c5446 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -333,7 +333,7 @@ The compilation steps are:
/workspace/python/tvm/relay/build_module.py:348: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- yolov3-tiny inference graph built in 19.30s!
+ yolov3-tiny inference graph built in 20.12s!
diff --git a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
index d5989237dc..46ab3b8f3f 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**01:39.165** total execution time for **topic_vta_tutorials_frontend** files:
+**01:40.363** total execution time for **topic_vta_tutorials_frontend** files:
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:51.111 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:51.707 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:48.054 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:48.656 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
index 5458d0f8ef..31345d28a5 100644
--- a/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:03.223** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.215** total execution time for **topic_vta_tutorials_optimize** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.772 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.754 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.450 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.461 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
index f0f74a30e1..994a42eaa2 100644
--- a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:00.777** total execution time for **topic_vta_tutorials** files:
+**00:00.810** total execution time for **topic_vta_tutorials** files:
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.410 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.427 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.366 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.383 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index e6c83765db..cd73a8890c 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -203,13 +203,6 @@ trials, we can load the best schedule from the log file and apply it.
-.. rst-class:: sphx-glr-script-out
-
- .. code-block:: none
-
- *E
-
-
@@ -332,7 +325,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 94.207 ms
+ Execution time of this operator: 94.159 ms
@@ -450,7 +443,7 @@ operations.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 31.935 seconds)
+ **Total running time of the script:** ( 1 minutes 26.336 seconds)
.. _sphx_glr_download_tutorial_auto_scheduler_matmul_x86.py:
diff --git a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
index 4cdefefe0d..dbdc6e82e4 100644
--- a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
@@ -450,16 +450,16 @@ reduce variance, we take 5 measurements and average them.
waiting for device...
device available
Get devices for measurement successfully!
- No: 1 GFLOPS: 1.30/1.30 result: MeasureResult(costs=(0.2058902898,), error_no=MeasureErrorNo.NO_ERROR, all_cost=3.4309840202331543, timestamp=1670034500.533958) [('tile_y', [-1, 2]), ('tile_x', [-1, 1])],None,1
- No: 2 GFLOPS: 12.76/12.76 result: MeasureResult(costs=(0.021029671200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5386679172515869, timestamp=1670034501.0775244) [('tile_y', [-1, 8]), ('tile_x', [-1, 512])],None,93
- No: 3 GFLOPS: 2.53/12.76 result: MeasureResult(costs=(0.10606129180000001,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8564305305480957, timestamp=1670034503.6619613) [('tile_y', [-1, 8]), ('tile_x', [-1, 4])],None,23
- No: 4 GFLOPS: 9.87/12.76 result: MeasureResult(costs=(0.0271899748,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5655226707458496, timestamp=1670034504.9929104) [('tile_y', [-1, 512]), ('tile_x', [-1, 32])],None,59
- No: 5 GFLOPS: 9.65/12.76 result: MeasureResult(costs=(0.027822743599999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6384131908416748, timestamp=1670034506.481211) [('tile_y', [-1, 512]), ('tile_x', [-1, 128])],None,79
- No: 6 GFLOPS: 11.09/12.76 result: MeasureResult(costs=(0.0242144052,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5395686626434326, timestamp=1670034507.0361464) [('tile_y', [-1, 2]), ('tile_x', [-1, 256])],None,81
- No: 7 GFLOPS: 3.27/12.76 result: MeasureResult(costs=(0.0821989346,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4751338958740234, timestamp=1670034508.5170445) [('tile_y', [-1, 32]), ('tile_x', [-1, 8])],None,35
- No: 8 GFLOPS: 12.08/12.76 result: MeasureResult(costs=(0.0222131674,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5597372055053711, timestamp=1670034509.0810752) [('tile_y', [-1, 32]), ('tile_x', [-1, 128])],None,75
- No: 9 GFLOPS: 3.88/12.76 result: MeasureResult(costs=(0.0691471726,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.2390568256378174, timestamp=1670034510.4324343) [('tile_y', [-1, 32]), ('tile_x', [-1, 16])],None,45
- No: 10 GFLOPS: 11.84/12.76 result: MeasureResult(costs=(0.0226699546,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.4928719997406006, timestamp=1670034510.9625611) [('tile_y', [-1, 8]), ('tile_x', [-1, 256])],None,83
+ No: 1 GFLOPS: 11.73/11.73 result: MeasureResult(costs=(0.0228826476,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5500216484069824, timestamp=1670199457.8715615) [('tile_y', [-1, 32]), ('tile_x', [-1, 256])],None,85
+ No: 2 GFLOPS: 0.90/11.73 result: MeasureResult(costs=(0.2995180684,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.992943048477173, timestamp=1670199462.8758476) [('tile_y', [-1, 64]), ('tile_x', [-1, 2])],None,16
+ No: 3 GFLOPS: 12.35/12.35 result: MeasureResult(costs=(0.021742523800000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5141923427581787, timestamp=1670199464.14166) [('tile_y', [-1, 64]), ('tile_x', [-1, 256])],None,86
+ No: 4 GFLOPS: 10.92/12.35 result: MeasureResult(costs=(0.0245865296,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5333995819091797, timestamp=1670199464.698331) [('tile_y', [-1, 256]), ('tile_x', [-1, 32])],None,58
+ No: 5 GFLOPS: 12.55/12.55 result: MeasureResult(costs=(0.0213842842,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5003049373626709, timestamp=1670199465.3563836) [('tile_y', [-1, 128]), ('tile_x', [-1, 512])],None,97
+ No: 6 GFLOPS: 8.45/12.55 result: MeasureResult(costs=(0.031760570599999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7126603126525879, timestamp=1670199466.7831542) [('tile_y', [-1, 512]), ('tile_x', [-1, 64])],None,69
+ No: 7 GFLOPS: 10.14/12.55 result: MeasureResult(costs=(0.026463583999999995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5962440967559814, timestamp=1670199468.1276104) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
+ No: 8 GFLOPS: 1.57/12.55 result: MeasureResult(costs=(0.1710809676,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.9350924491882324, timestamp=1670199471.0713263) [('tile_y', [-1, 64]), ('tile_x', [-1, 4])],None,26
+ No: 9 GFLOPS: 9.58/12.55 result: MeasureResult(costs=(0.028019674799999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5857012271881104, timestamp=1670199471.7738087) [('tile_y', [-1, 8]), ('tile_x', [-1, 32])],None,53
+ No: 10 GFLOPS: 1.47/12.55 result: MeasureResult(costs=(0.1827910366,), error_no=MeasureErrorNo.NO_ERROR, all_cost=3.0309901237487793, timestamp=1670199474.8640888) [('tile_y', [-1, 1]), ('tile_x', [-1, 1])],None,0
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 1461a4fb37..553f4845a6 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -320,7 +320,7 @@ standard deviation.
.. code-block:: none
- {'mean': 511.45323565000126, 'median': 512.1074944499924, 'std': 1.7399256461565293}
+ {'mean': 519.2552413799604, 'median': 519.585381249999, 'std': 2.2776902092340836}
@@ -554,31 +554,30 @@ the tuning data to.
.. code-block:: none
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 11.10/ 17.95 GFLOPS | Progress: (4/20) | 9.91 s
[Task 1/25] Current/Best: 14.65/ 18.48 GFLOPS | Progress: (8/20) | 13.09 s
[Task 1/25] Current/Best: 17.02/ 18.48 GFLOPS | Progress: (12/20) | 18.28 s
[Task 1/25] Current/Best: 8.57/ 18.48 GFLOPS | Progress: (16/20) | 20.82 s
[Task 1/25] Current/Best: 7.17/ 18.48 GFLOPS | Progress: (20/20) | 22.70 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 13.39/ 13.39 GFLOPS | Progress: (4/20) | 2.88 s
[Task 2/25] Current/Best: 4.30/ 18.12 GFLOPS | Progress: (8/20) | 4.59 s
[Task 2/25] Current/Best: 17.88/ 18.12 GFLOPS | Progress: (12/20) | 5.80 s
[Task 2/25] Current/Best: 13.86/ 18.42 GFLOPS | Progress: (16/20) | 7.39 s
[Task 2/25] Current/Best: 15.86/ 18.42 GFLOPS | Progress: (20/20) | 8.73 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 16.84/ 19.09 GFLOPS | Progress: (4/20) | 3.73 s
[Task 3/25] Current/Best: 24.19/ 24.19 GFLOPS | Progress: (8/20) | 5.75 s
[Task 3/25] Current/Best: 7.05/ 24.19 GFLOPS | Progress: (12/20) | 8.03 s
[Task 3/25] Current/Best: 11.51/ 24.19 GFLOPS | Progress: (16/20) | 10.11 s
[Task 3/25] Current/Best: 7.58/ 24.19 GFLOPS | Progress: (20/20) | 12.19 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 15.46/ 15.46 GFLOPS | Progress: (4/20) | 3.19 s
[Task 4/25] Current/Best: 13.42/ 15.46 GFLOPS | Progress: (8/20) | 7.47 s
[Task 4/25] Current/Best: 14.55/ 19.52 GFLOPS | Progress: (12/20) | 11.86 s
[Task 4/25] Current/Best: 12.25/ 19.52 GFLOPS | Progress: (16/20) | 14.03 s
[Task 4/25] Current/Best: 12.79/ 19.52 GFLOPS | Progress: (20/20) | 15.63 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 11.30/ 19.50 GFLOPS | Progress: (4/20) | 3.14 s
[Task 5/25] Current/Best: 16.86/ 19.50 GFLOPS | Progress: (8/20) | 6.51 s
[Task 5/25] Current/Best: 15.27/ 19.50 GFLOPS | Progress: (12/20) | 8.15 s
[Task 5/25] Current/Best: 9.84/ 19.50 GFLOPS | Progress: (16/20) | 9.73 s
[Task 5/25] Current/Best: 11.56/ 19.50 GFLOPS | Progress: (20/20) | 11.41 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 13.26/ 15.07 GFLOPS | Progress: (4/20) | 4.43 s
[Task 6/25] Current/Best: 3.11/ 16.35 GFLOPS | Progress: (8/20) | 7.43 s
[Task 6/25] Current/Best: 21.51/ 21.51 GFLOPS | Progress: (12/20) | 9.40 s
[Task 6/25] Current/Best: 3.14/ 21.51 GFLOPS | Progress: (16/20) | 12.43 s
[Task 6/25] Current/Best: 9.91/ 21.51 GFLOPS | Progress: (20/20) | 15.37 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 18.95/ 18.95 GFLOPS | Progress: (4/20) | 3.45 s
[Task 7/25] Current/Best: 11.54/ 18.95 GFLOPS | Progress: (8/20) | 5.67 s
[Task 7/25] Current/Best: 11.65/ 18.95 GFLOPS | Progress: (12/20) | 7.62 s
[Task 7/25] Current/Best: 12.60/ 18.95 GFLOPS | Progress: (16/20) | 10.09 s
[Task 7/25] Current/Best: 11.05/ 18.95 GFLOPS | Progress: (20/20) | 12.18 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 13.09/ 22.14 GFLOPS | Progress: (4/20) | 3.75 s
[Task 8/25] Current/Best: 6.23/ 22.14 GFLOPS | Progress: (8/20) | 5.58 s
[Task 8/25] Current/Best: 15.79/ 22.14 GFLOPS | Progress: (12/20) | 7.42 s
[Task 8/25] Current/Best: 3.02/ 22.14 GFLOPS | Progress: (16/20) | 10.19 s
[Task 8/25] Current/Best: 12.18/ 22.14 GFLOPS | Progress: (20/20) | 16.15 s Done.
-
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 16.53/ 16.60 GFLOPS | Progress: (4/20) | 3.96 s
[Task 9/25] Current/Best: 12.24/ 17.76 GFLOPS | Progress: (8/20) | 5.31 s
[Task 9/25] Current/Best: 8.65/ 17.76 GFLOPS | Progress: (12/20) | 12.56 s
[Task 9/25] Current/Best: 12.13/ 18.64 GFLOPS | Progress: (16/20) | 14.20 s
[Task 9/25] Current/Best: 13.77/ 18.64 GFLOPS | Progress: (20/20) | 16.61 s Done.
-
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 7.15/ 15.33 GFLOPS | Progress: (4/20) | 3.46 s
[Task 10/25] Current/Best: 1.58/ 15.33 GFLOPS | Progress: (8/20) | 5.60 s
[Task 10/25] Current/Best: 13.26/ 15.85 GFLOPS | Progress: (12/20) | 7.68 s
[Task 10/25] Current/Best: 12.68/ 17.75 GFLOPS | Progress: (16/20) | 9.36 s
[Task 10/25] Current/Best: 16.11/ 18.74 GFLOPS | Progress: (20/20) | 10.77 s Done.
-
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 8.30/ 15.42 GFLOPS | Progress: (4/20) | 4.28 s
[Task 11/25] Current/Best: 12.91/ 22.61 GFLOPS | Progress: (8/20) | 6.17 s
[Task 11/25] Current/Best: 17.22/ 22.61 GFLOPS | Progress: (12/20) | 8.61 s
[Task 11/25] Current/Best: 13.31/ 22.61 GFLOPS | Progress: (16/20) | 10.99 s
[Task 11/25] Current/Best: 11.80/ 22.61 GFLOPS | Progress: (20/20) | 13.80 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 5.68/ 13.11 GFLOPS | Progress: (4/20) | 4.64 s
[Task 12/25] Current/Best: 11.32/ 17.75 GFLOPS | Progress: (8/20) | 6.95 s
[Task 12/25] Current/Best: 16.68/ 17.75 GFLOPS | Progress: (12/20) | 8.99 s
[Task 12/25] Current/Best: 13.26/ 17.75 GFLOPS | Progress: (16/20) | 10.73 s
[Task 12/25] Current/Best: 13.42/ 17.75 GFLOPS | Progress: (20/20) | 14.63 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 16.36/ 21.58 GFLOPS | Progress: (4/20) | 3.99 s
[Task 13/25] Current/Best: 9.44/ 21.58 GFLOPS | Progress: (8/20) | 6.29 s
[Task 13/25] Current/Best: 1.56/ 21.58 GFLOPS | Progress: (12/20) | 10.68 s
[Task 13/25] Current/Best: 23.65/ 23.65 GFLOPS | Progress: (16/20) | 12.41 s
[Task 13/25] Current/Best: 21.12/ 23.65 GFLOPS | Progress: (20/20) | 16.09 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 9.71/ 10.93 GFLOPS | Progress: (4/20) | 4.72 s
[Task 14/25] Current/Best: 5.26/ 20.11 GFLOPS | Progress: (8/20) | 7.07 s
[Task 14/25] Current/Best: 5.55/ 20.11 GFLOPS | Progress: (12/20) | 9.66 s
[Task 14/25] Current/Best: 13.29/ 20.11 GFLOPS | Progress: (16/20) | 11.40 s
[Task 14/25] Current/Best: 11.30/ 20.11 GFLOPS | Progress: (20/20) | 14.04 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 11.76/ 19.70 GFLOPS | Progress: (4/20) | 3.72 s
[Task 15/25] Current/Best: 18.35/ 19.70 GFLOPS | Progress: (8/20) | 5.60 s
[Task 15/25] Current/Best: 22.09/ 22.09 GFLOPS | Progress: (12/20) | 7.95 s
[Task 15/25] Current/Best: 12.19/ 22.09 GFLOPS | Progress: (16/20) | 10.35 s
[Task 15/25] Current/Best: 3.16/ 22.09 GFLOPS | Progress: (20/20)
| 12.71 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 15.28/ 17.63 GFLOPS | Progress: (4/20) | 3.87 s
[Task 16/25] Current/Best: 20.57/ 20.57 GFLOPS | Progress: (8/20) | 5.91 s Done.
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 1.88/ 11.72 GFLOPS | Progress: (4/20) | 9.23 s
[Task 1/25] Current/Best: 17.75/ 17.75 GFLOPS | Progress: (8/20) | 12.22 s
[Task 1/25] Current/Best: 9.94/ 17.75 GFLOPS | Progress: (12/20) | 14.68 s
[Task 1/25] Current/Best: 12.59/ 19.23 GFLOPS | Progress: (16/20) | 17.50 s
[Task 1/25] Current/Best: 18.88/ 19.23 GFLOPS | Progress: (20/20) | 20.86 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 13.80/ 17.95 GFLOPS | Progress: (4/20) | 3.06 s
[Task 2/25] Current/Best: 19.02/ 19.02 GFLOPS | Progress: (8/20) | 4.20 s
[Task 2/25] Current/Best: 4.20/ 19.02 GFLOPS | Progress: (12/20) | 6.84 s
[Task 2/25] Current/Best: 7.59/ 19.02 GFLOPS | Progress: (16/20) | 7.89 s
[Task 2/25] Current/Best: 16.66/ 19.02 GFLOPS | Progress: (20/20) | 9.34 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 20.43/ 20.43 GFLOPS | Progress: (4/20) | 3.40 s
[Task 3/25] Current/Best: 6.64/ 20.43 GFLOPS | Progress: (8/20) | 6.36 s
[Task 3/25] Current/Best: 16.17/ 22.34 GFLOPS | Progress: (12/20) | 8.09 s
[Task 3/25] Current/Best: 11.70/ 23.24 GFLOPS | Progress: (16/20) | 9.83 s
[Task 3/25] Current/Best: 10.99/ 23.24 GFLOPS | Progress: (20/20) | 13.04 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 14.22/ 15.06 GFLOPS | Progress: (4/20) | 4.12 s
[Task 4/25] Current/Best: 15.12/ 16.86 GFLOPS | Progress: (8/20) | 5.62 s
[Task 4/25] Current/Best: 11.91/ 16.86 GFLOPS | Progress: (12/20) | 7.68 s
[Task 4/25] Current/Best: 19.47/ 19.47 GFLOPS | Progress: (16/20) | 18.50 s
[Task 4/25] Current/Best: 14.99/ 19.47 GFLOPS | Progress: (20/20) | 20.54 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 5.46/ 17.01 GFLOPS | Progress: (4/20) | 3.41 s
[Task 5/25] Current/Best: 14.99/ 17.01 GFLOPS | Progress: (8/20) | 5.31 s
[Task 5/25] Current/Best: 5.12/ 17.01 GFLOPS | Progress: (12/20) | 7.23 s
[Task 5/25] Current/Best: 11.71/ 17.01 GFLOPS | Progress: (16/20) | 9.20 s
[Task 5/25] Current/Best: 13.02/ 17.01 GFLOPS | Progress: (20/20) | 11.17 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 20.64/ 20.64 GFLOPS | Progress: (4/20) | 3.93 s
[Task 6/25] Current/Best: 17.78/ 20.64 GFLOPS | Progress: (8/20) | 5.90 s
[Task 6/25] Current/Best: 5.93/ 20.64 GFLOPS | Progress: (12/20) | 7.92 s
[Task 6/25] Current/Best: 11.74/ 20.64 GFLOPS | Progress: (16/20) | 9.89 s
[Task 6/25] Current/Best: 5.75/ 20.64 GFLOPS | Progress: (20/20) | 13.59 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 14.00/ 15.88 GFLOPS | Progress: (4/20) | 3.72 s
[Task 7/25] Current/Best: 3.06/ 15.88 GFLOPS | Progress: (8/20) | 6.73 s
[Task 7/25] Current/Best: 14.79/ 15.88 GFLOPS | Progress: (12/20) | 8.92 s
[Task 7/25] Current/Best: 13.36/ 18.77 GFLOPS | Progress: (16/20) | 11.39 s
[Task 7/25] Current/Best: 11.74/ 18.77 GFLOPS | Progress: (20/20) | 14.26 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 10.13/ 18.34 GFLOPS | Progress: (4/20) | 4.70 s
[Task 8/25] Current/Best: 15.90/ 18.34 GFLOPS | Progress: (8/20) | 8.70 s
[Task 8/25] Current/Best: 14.05/ 18.34 GFLOPS | Progress: (12/20) | 10.87 s
[Task 8/25] Current/Best: 13.29/ 18.34 GFLOPS | Progress: (16/20) | 18.78 s
[Task 8/25] Current/Best: 11.32/ 18.34 GFLOPS | Progress: (20/20) | 23.07 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 16.39/ 17.20 GFLOPS | Progress: (4/20) | 3.17 s
[Task 9/25] Current/Best: 4.78/ 17.20 GFLOPS | Progress: (8/20) | 13.86 s
[Task 9/25] Current/Best: 9.90/ 17.20 GFLOPS | Progress: (12/20) | 24.68 s
[Task 9/25] Current/Best: 22.52/ 22.52 GFLOPS | Progress: (16/20) | 35.43 s
[Task 9/25] Current/Best: 13.86/ 22.52 GFLOPS | Progress: (20/20) | 37.59 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 13.20/ 17.34 GFLOPS | Progress: (4/20) | 2.98 s
[Task 10/25] Current/Best: 13.72/ 17.34 GFLOPS | Progress: (8/20) | 5.28 s
[Task 10/25] Current/Best: 13.11/ 17.34 GFLOPS | Progress: (12/20) | 6.94 s
[Task 10/25] Current/Best: 17.02/ 18.93 GFLOPS | Progress: (16/20) | 8.38 s
[Task 10/25] Current/Best: 12.75/ 18.93 GFLOPS | Progress: (20/20)
| 9.71 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 18.72/ 20.24 GFLOPS | Progress: (4/20) | 3.26 s
[Task 11/25] Current/Best: 19.47/ 20.24 GFLOPS | Progress: (8/20) | 5.63 s
[Task 11/25] Current/Best: 16.12/ 20.24 GFLOPS | Progress: (12/20) | 7.62 s
[Task 11/25] Current/Best: 14.33/ 21.89 GFLOPS | Progress: (16/20) | 9.17 s
[Task 11/25] Current/Best: 14.30/ 21.89 GFLOPS | Progress: (20/20) | 12.29 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 15.93/ 15.93 GFLOPS | Progress: (4/20) | 10.13 s
[Task 12/25] Current/Best: 5.18/ 15.93 GFLOPS | Progress: (8/20) | 15.81 s
[Task 12/25] Current/Best: 14.19/ 18.83 GFLOPS | Progress: (12/20) | 17.69 s
[Task 12/25] Current/Best: 10.43/ 18.83 GFLOPS | Progress: (16/20) | 22.02 s
[Task 12/25] Current/Best: 13.74/ 18.83 GFLOPS | Progress: (20/20) | 27.81 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 6.30/ 11.08 GFLOPS | Progress: (4/20) | 3.83 s
[Task 13/25] Current/Best: 12.03/ 20.14 GFLOPS | Progress: (8/20) | 5.77 s
[Task 13/25] Current/Best: 20.21/ 20.21 GFLOPS | Progress: (12/20) | 8.17 s
[Task 13/25] Current/Best: 6.06/ 20.21 GFLOPS | Progress: (16/20) | 11.67 s
[Task 13/25] Current/Best: 9.72/ 20.21 GFLOPS | Progress: (20/20) | 13.99 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 14.05/ 17.19 GFLOPS | Progress: (4/20) | 2.92 s
[Task 14/25] Current/Best: 14.86/ 17.19 GFLOPS | Progress: (8/20) | 5.97 s Done.
+
[Task 14/25] Current/Best: 9.72/ 17.19 GFLOPS | Progress: (12/20) | 8.65 s
[Task 14/25] Current/Best: 10.70/ 17.19 GFLOPS | Progress: (16/20) | 12.07 s
[Task 14/25] Current/Best: 12.23/ 17.19 GFLOPS | Progress: (20/20) | 19.46 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 19.99/ 19.99 GFLOPS | Progress: (4/20) | 6.46 s
[Task 15/25] Current/Best: 15.11/ 19.99 GFLOPS | Progress: (8/20) | 7.79 s
[Task 15/25] Current/Best: 7.96/ 20.58 GFLOPS | Progress: (12/20) | 10.80 s
[Task 15/25] Current/Best: 10.72/ 20.58 GFLOPS | Progress: (16/20) | 12.67 s
[Task 15/25] Current/Best: 5.08/ 22.05 GFLOPS | Progress: (20/20) | 18.60 s Done.
+
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 12.06/ 19.26 GFLOPS | Progress: (4/20) | 3.38 s
[Task 16/25] Current/Best: 15.04/ 19.26 GFLOPS | Progress: (8/20) | 4.75 s
[Task 16/25] Current/Best: 16.44/ 19.26 GFLOPS | Progress: (12/20) | 6.22 s
[Task 16/25] Current/Best: 7.51/ 19.26 GFLOPS | Progress: (16/20) | 9.00 s
[Task 16/25] Current/Best: 14.93/ 19.26 GFLOPS | Progress: (20/20) | 10.38 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 5.21/ 21.07 GFLOPS | Progress: (4/20) | 3.58 s
[Task 17/25] Current/Best: 16.04/ 23.08 GFLOPS | Progress: (8/20) | 6.36 s
[Task 17/25] Current/Best: 9.01/ 23.08 GFLOPS | Progress: (12/20) | 10.01 s
[Task 17/25] Current/Best: 6.14/ 23.08 GFLOPS | Progress: (16/20) | 11.97 s
[Task 17/25] Current/Best: 7.08/ 23.08 GFLOPS | Progress: (20/20) | 14.05 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 15.36/ 15.36 GFLOPS | Progress: (4/20) | 4.18 s
[Task 18/25] Current/Best: 10.00/ 15.36 GFLOPS | Progress: (8/20) | 7.94 s
[Task 18/25] Current/Best: 10.58/ 19.37 GFLOPS | Progress: (12/20) | 11.47 s
[Task 18/25] Current/Best: 11.70/ 19.37 GFLOPS | Progress: (16/20) | 14.22 s
[Task 18/25] Current/Best: 9.14/ 19.37 GFLOPS | Progress: (20/20) | 20.41 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 6.64/ 20.51 GFLOPS | Progress: (4/20) | 4.49 s
[Task 19/25] Current/Best: 10.11/ 20.51 GFLOPS | Progress: (8/20) | 8.71 s
[Task 19/25] Current/Best: 19.67/ 20.51 GFLOPS | Progress: (12/20) | 15.39 s
[Task 19/25] Current/Best: 10.58/ 20.51 GFLOPS | Progress: (16/20) | 18.60 s
[Task 19/25] Current/Best: 10.97/ 20.51 GFLOPS | Progress: (20/20) | 23.09 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 10.39/ 17.76 GFLOPS | Progress: (4/20) | 3.41 s
[Task 20/25] Current/Best: 16.51/ 17.76 GFLOPS | Progress: (8/20) | 6.96 s
[Task 20/25] Current/Best: 13.42/ 17.76 GFLOPS | Progress: (12/20) | 9.27 s
[Task 20/25] Current/Best: 11.11/ 17.76 GFLOPS | Progress: (16/20) | 12.69 s
[Task 20/25] Current/Best: 12.72/ 17.76 GFLOPS | Progress: (20/20) | 14.50 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 2.71/ 17.05 GFLOPS | Progress: (4/20) | 8.62 s
[Task 21/25] Current/Best: 12.12/ 17.05 GFLOPS | Progress: (8/20) | 10.46 s
[Task 21/25] Current/Best: 18.83/ 18.83 GFLOPS | Progress: (12/20) | 11.80 s
[Task 21/25] Current/Best: 8.73/ 18.83 GFLOPS | Progress: (16/20) | 15.00 s
[Task 21/25] Current/Best: 13.46/ 18.83 GFLOPS | Progress: (20/20
) | 17.18 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
Done.
-
[Task 16/25] Current/Best: 11.45/ 20.57 GFLOPS | Progress: (12/20) | 7.18 s
[Task 16/25] Current/Best: 18.11/ 20.57 GFLOPS | Progress: (16/20) | 8.88 s
[Task 16/25] Current/Best: 16.19/ 20.57 GFLOPS | Progress: (20/20) | 12.28 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 9.90/ 14.22 GFLOPS | Progress: (4/20) | 5.74 s
[Task 17/25] Current/Best: 1.56/ 15.42 GFLOPS | Progress: (8/20) | 9.80 s
[Task 17/25] Current/Best: 11.24/ 19.56 GFLOPS | Progress: (12/20) | 13.65 s
[Task 17/25] Current/Best: 11.76/ 23.83 GFLOPS | Progress: (16/20) | 15.78 s
[Task 17/25] Current/Best: 3.09/ 23.83 GFLOPS | Progress: (20/20) | 19.17 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 13.73/ 20.84 GFLOPS | Progress: (4/20) | 3.56 s
[Task 18/25] Current/Best: 8.66/ 20.84 GFLOPS | Progress: (8/20) | 10.78 s
[Task 18/25] Current/Best: 12.05/ 20.84 GFLOPS | Progress: (12/20) | 13.16 s
[Task 18/25] Current/Best: 17.88/ 20.84 GFLOPS | Progress: (16/20) | 16.25 s
[Task 18/25] Current/Best: 17.77/ 21.74 GFLOPS | Progress: (20/20) | 22.41 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 18.83/ 18.83 GFLOPS | Progress: (4/20) | 3.56 s
[Task 19/25] Current/Best: 10.99/ 21.85 GFLOPS | Progress: (8/20) | 7.15 s
[Task 19/25] Current/Best: 17.55/ 21.85 GFLOPS | Progress: (12/20) | 12.19 s
[Task 19/25] Current/Best: 5.38/ 21.85 GFLOPS | Progress: (16/20) | 15.29 s
[Task 19/25] Current/Best: 3.08/ 21.85 GFLOPS | Progress: (20/20) | 18.87 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 9.72/ 12.65 GFLOPS | Progress: (4/20) | 3.67 s
[Task 20/25] Current/Best: 17.37/ 19.32 GFLOPS | Progress: (8/20) | 5.63 s
[Task 20/25] Current/Best: 2.65/ 19.32 GFLOPS | Progress: (12/20) | 8.50 s
[Task 20/25] Current/Best: 6.83/ 19.32 GFLOPS | Progress: (16/20) | 12.59 s
[Task 20/25] Current/Best: 10.01/ 19.32 GFLOPS | Progress: (20/20) | 15.38 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 5.24/ 19.19 GFLOPS | Progress: (4/20) | 3.24 s
[Task 21/25] Current/Best: 20.11/ 20.11 GFLOPS | Progress: (8/20) | 4.98 s
[Task 21/25] Current/Best: 6.30/ 20.11 GFLOPS | Progress: (12/20) | 8.72 s Done.
-
[Task 21/25] Current/Best: 5.21/ 20.11 GFLOPS | Progress: (16/20) | 12.30 s
[Task 21/25] Current/Best: 11.59/ 20.11 GFLOPS | Progress: (20/20) | 14.04 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 8.10/ 18.68 GFLOPS | Progress: (4/20) | 3.55 s
[Task 22/25] Current/Best: 10.58/ 18.68 GFLOPS | Progress: (8/20) | 5.59 s
[Task 22/25] Current/Best: 12.48/ 18.68 GFLOPS | Progress: (12/20) | 7.63 s
[Task 22/25] Current/Best: 2.06/ 18.68 GFLOPS | Progress: (16/20) | 10.67 s
[Task 22/25] Current/Best: 13.88/ 19.50 GFLOPS | Progress: (20/20) | 12.34 s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 8.42/ 19.08 GFLOPS | Progress: (4/20) | 3.98 s
[Task 23/25] Current/Best: 6.13/ 19.12 GFLOPS | Progress: (8/20) | 6.82 s
[Task 23/25] Current/Best: 19.86/ 22.83 GFLOPS | Progress: (12/20) | 9.70 s
[Task 23/25] Current/Best: 12.95/ 22.83 GFLOPS | Progress: (16/20) | 13.25 s
[Task 23/25] Current/Best: 3.08/ 22.83 GFLOPS | Progress: (20/20) | 16.62 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 3.49/ 5.85 GFLOPS | Progress: (4/20) | 12.18 s
[Task 24/25] Current/Best: 2.89/ 5.85 GFLOPS | Progress: (8/20) | 22.67 s
[Task 24/25] Current/Best: 2.23/ 5.85 GFLOPS | Progress: (12/20) | 26.96 s
[Task 24/25] Current/Best: 3.50/ 5.85 GFLOPS | Progress: (16/20) | 29.63 s
[Task 24/25] Current/Best: 6.73/ 6.73 GFLOPS | Progress: (20/20) | 40.09 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
- Done.
-
[Task 25/25] Current/Best: 3.04/ 3.04 GFLOPS | Progress: (4/20) | 12.93 s
[Task 25/25] Current/Best: 8.81/ 8.81 GFLOPS | Progress: (8/20) | 23.58 s
[Task 25/25] Current/Best: 3.56/ 8.81 GFLOPS | Progress: (12/20) | 35.24 s
[Task 25/25] Current/Best: 1.55/ 9.61 GFLOPS | Progress: (16/20) | 37.01 s
[Task 25/25] Current/Best: 6.58/ 9.61 GFLOPS | Progress: (20/20) | 39.21 s
+
[Task 22/25] Current/Best: 19.30/ 19.30 GFLOPS | Progress: (4/20) | 2.84 s
[Task 22/25] Current/Best: 13.73/ 19.30 GFLOPS | Progress: (8/20) | 5.02 s
[Task 22/25] Current/Best: 8.75/ 19.30 GFLOPS | Progress: (12/20) | 7.14 s
[Task 22/25] Current/Best: 14.33/ 19.30 GFLOPS | Progress: (16/20) | 8.78 s
[Task 22/25] Current/Best: 14.52/ 19.30 GFLOPS | Progress: (20/20) | 10.65 s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 10.42/ 18.02 GFLOPS | Progress: (4/20) | 6.55 s
[Task 23/25] Current/Best: 12.22/ 22.08 GFLOPS | Progress: (8/20) | 8.37 s
[Task 23/25] Current/Best: 11.57/ 22.08 GFLOPS | Progress: (12/20) | 11.62 s
[Task 23/25] Current/Best: 2.68/ 22.08 GFLOPS | Progress: (16/20) | 14.66 s
[Task 23/25] Current/Best: 12.13/ 22.08 GFLOPS | Progress: (20/20) | 18.11 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 1.17/ 7.53 GFLOPS | Progress: (4/20) | 4.21 s
[Task 24/25] Current/Best: 3.61/ 7.53 GFLOPS | Progress: (8/20) | 14.90 s
[Task 24/25] Current/Best: 6.96/ 7.53 GFLOPS | Progress: (12/20) | 26.38 s
[Task 24/25] Current/Best: 9.85/ 9.85 GFLOPS | Progress: (16/20) | 37.64 s
[Task 24/25] Current/Best: 7.94/ 9.85 GFLOPS | Progress: (20/20) | 49.05 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
+
[Task 25/25] Current/Best: 9.24/ 9.24 GFLOPS | Progress: (4/20) | 5.16 s
[Task 25/25] Current/Best: 3.02/ 9.24 GFLOPS | Progress: (8/20) | 6.30 s
[Task 25/25] Current/Best: 5.36/ 9.24 GFLOPS | Progress: (12/20) | 16.81 s
[Task 25/25] Current/Best: 5.87/ 9.24 GFLOPS | Progress: (16/20) | 27.51 s
[Task 25/25] Current/Best: 3.47/ 9.24 GFLOPS | Progress: (20/20) | 38.21 s
@@ -674,8 +673,8 @@ Verify that the optimized model runs and produces the same results:
.. code-block:: none
- class='n02123045 tabby, tabby cat' with probability=0.621103
- class='n02123159 tiger cat' with probability=0.356379
+ class='n02123045 tabby, tabby cat' with probability=0.621104
+ class='n02123159 tiger cat' with probability=0.356378
class='n02124075 Egyptian cat' with probability=0.019712
class='n02129604 tiger, Panthera tigris' with probability=0.001215
class='n04040759 radiator' with probability=0.000262
@@ -732,8 +731,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 409.24640631999864, 'median': 408.0138838500261, 'std': 2.7773848280345828}
- unoptimized: {'mean': 511.45323565000126, 'median': 512.1074944499924, 'std': 1.7399256461565293}
+ optimized: {'mean': 414.6784987999854, 'median': 413.53415209996456, 'std': 2.862276002582264}
+ unoptimized: {'mean': 519.2552413799604, 'median': 519.585381249999, 'std': 2.2776902092340836}
@@ -756,7 +755,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 10 minutes 28.375 seconds)
+ **Total running time of the script:** ( 11 minutes 32.331 seconds)
.. _sphx_glr_download_tutorial_autotvm_relay_x86.py:
diff --git a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
index 8f8ee0d40a..8bdbedf4bf 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -270,7 +270,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.349e-07 secs/op
+ 1.337e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index 3e3f53ff1d..1925786939 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -260,7 +260,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0xe44e7d0)), stage(b, placeholder(b, 0x23786b00)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min [...]
+ [stage(a, placeholder(a, 0x198acef0)), stage(b, placeholder(b, 0x198ac140)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(mi [...]
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index 85f339b4c5..8446b9b9df 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,32 +5,32 @@
Computation times
=================
-**13:54.342** total execution time for **tutorial** files:
+**14:57.553** total execution time for **tutorial** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 10:28.375 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 11:32.331 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:31.935 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:26.336 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:01.476 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:01.108 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:33.344 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:34.314 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:17.615 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:21.457 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.816 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.994 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.632 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.837 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.140 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.164 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``) | 00:00.006 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``) | 00:00.007 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_uma.py` (``uma.py``) | 00:00.001 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``) | 00:00.001 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_uma.py` (``uma.py``) | 00:00.002 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``) | 00:00.001 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``) | 00:00.001 | 0.0 MB |
++------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_install.py` (``install.py``) | 00:00.001 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
index 4f897512b2..89b47ba311 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -294,7 +294,7 @@ helper function to run a profile of the TVM generated code.
.. code-block:: none
- Numpy running time: 0.000008
+ Numpy running time: 0.000007
naive: 0.000007
@@ -393,7 +393,7 @@ compile and run this new schedule with the parallel operation applied:
.. code-block:: none
- parallel: 0.000008
+ parallel: 0.000007
@@ -448,7 +448,7 @@ factor to be the number of threads on your CPU.
.. code-block:: none
- vector: 0.000026
+ vector: 0.000025
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [n: int32], [stride: int32], type="auto"),
@@ -499,10 +499,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 8.216080004785908e-06 1.0
- naive 7.0635e-06 0.8597165553263205
- parallel 7.682999999999999e-06 0.9351174764029333
- vector 2.5695600000000002e-05 3.127476848452326
+ numpy 7.2540900146123025e-06 1.0
+ naive 6.7245e-06 0.9269942868718859
+ parallel 6.974700000000001e-06 0.9614851740122453
+ vector 2.4689800000000002e-05 3.403569565619673
@@ -923,7 +923,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.018542
+ Numpy running time: 0.018558
@@ -981,7 +981,7 @@ optimizations.
.. code-block:: none
- none: 3.436734
+ none: 3.364908
@@ -1083,7 +1083,7 @@ schedule.
.. code-block:: none
- blocking: 0.304102
+ blocking: 0.325445
@@ -1178,7 +1178,7 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- vectorization: 0.344460
+ vectorization: 0.356750
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1024, 1024], []),
@@ -1251,7 +1251,7 @@ more cache friendly.
.. code-block:: none
- loop permutation: 0.113885
+ loop permutation: 0.121551
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1024, 1024], []),
@@ -1349,7 +1349,7 @@ optimized schedule.
.. code-block:: none
- array packing: 0.108551
+ array packing: 0.108996
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1024, 1024], []),
@@ -1441,7 +1441,7 @@ to `C` when all the block results are ready.
.. code-block:: none
- block caching: 0.114804
+ block caching: 0.110712
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1024, 1024], []),
@@ -1526,7 +1526,7 @@ of thread-level parallelization.
.. code-block:: none
- parallelization: 0.152331
+ parallelization: 0.147181
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1024, 1024], []),
@@ -1606,13 +1606,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.4367338129000005 1.0
- blocking 0.3041015317 0.08848562276151135
- vectorization 0.34446008499999997 0.10022891028308535
- loop permutation 0.1138847535 0.033137496151877194
- array packing 0.10855134179999999 0.0315856123021648
- block caching 0.1148035163 0.03340483218952764
- parallelization 0.1523305629 0.04432422503256361
+ none 3.3649080392000004 1.0
+ blocking 0.32544473690000003 0.09671727521485961
+ vectorization 0.3567504413 0.10602085915691671
+ loop permutation 0.121550724 0.036123044845201305
+ array packing 0.10899627760000001 0.03239205242171005
+ block caching 0.11071204350000001 0.03290195221095004
+ parallelization 0.1471810597 0.04373999467010456
@@ -1654,7 +1654,7 @@ the computation for specific platforms.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 1.476 seconds)
+ **Total running time of the script:** ( 1 minutes 1.108 seconds)
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
diff --git a/docs/commit_hash b/docs/commit_hash
index bb38cb744b..963ae036e6 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-d31a1fb0dbea484dec045c22ce2a756aa1071b38
+3a81aef40bca9479d4a691b3a80e42b01f3f8a0d
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index 5d81e3015f..0b119ccac9 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -585,7 +585,7 @@ class:['truck 0.9266'] left:471 top:83 right:689 bottom:169
class:['bicycle 0.9984'] left:111 top:113 right:577 bottom:447
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 10.168 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 11.752 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-darknet-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7716f96385bd5abb6e822041e285be54/from_darknet.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_darknet.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/from_mxnet.html b/docs/how_to/compile_models/from_mxnet.html
index 3f740cf951..40d8aec47e 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -440,7 +440,7 @@ to download the full example code</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"x"</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#tuple" title="builtins.tuple" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span><span class="o">.</span><span class="n">shape</span></a><span class="p">)</span>
</pre></div>
</div>
-<img src="../../_images/sphx_glr_from_mxnet_001.png" srcset="../../_images/sphx_glr_from_mxnet_001.png" alt="from mxnet" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip4df2b424-93b8-4131-9de0-6c69c9785930 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+<img src="../../_images/sphx_glr_from_mxnet_001.png" srcset="../../_images/sphx_glr_from_mxnet_001.png" alt="from mxnet" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipad99cdc3-9bdb-4914-a4b4-f33edf155ba6 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index ec5d88b3d8..8426a7bfac 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -448,14 +448,14 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
0%| | 0.00/41.5M [00:00<?, ?B/s]
- 19%|#9 | 7.90M/41.5M [00:00<00:00, 82.8MB/s]
- 38%|###8 | 15.8M/41.5M [00:00<00:00, 33.5MB/s]
- 54%|#####3 | 22.3M/41.5M [00:00<00:00, 39.7MB/s]
- 66%|######5 | 27.2M/41.5M [00:00<00:00, 37.4MB/s]
- 77%|#######7 | 32.0M/41.5M [00:00<00:00, 39.0MB/s]
- 87%|########7 | 36.1M/41.5M [00:00<00:00, 39.5MB/s]
- 97%|#########6| 40.2M/41.5M [00:01<00:00, 34.6MB/s]
-100%|##########| 41.5M/41.5M [00:01<00:00, 38.7MB/s]
+ 15%|#5 | 6.33M/41.5M [00:00<00:01, 36.3MB/s]
+ 24%|##3 | 9.79M/41.5M [00:00<00:00, 34.0MB/s]
+ 39%|###8 | 16.0M/41.5M [00:00<00:00, 35.9MB/s]
+ 54%|#####3 | 22.3M/41.5M [00:00<00:00, 44.7MB/s]
+ 65%|######4 | 26.8M/41.5M [00:00<00:00, 43.4MB/s]
+ 79%|#######9 | 32.8M/41.5M [00:00<00:00, 48.9MB/s]
+ 92%|#########2| 38.3M/41.5M [00:00<00:00, 51.4MB/s]
+100%|##########| 41.5M/41.5M [00:00<00:00, 44.5MB/s]
</pre></div>
</div>
</div>
diff --git a/docs/how_to/compile_models/from_pytorch.html b/docs/how_to/compile_models/from_pytorch.html
index d447e84fcb..a5bd8d3bab 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -431,13 +431,10 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
0%| | 0.00/44.7M [00:00<?, ?B/s]
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- 54%|#####3 | 24.0M/44.7M [00:00<00:00, 56.8MB/s]
- 66%|######5 | 29.4M/44.7M [00:00<00:00, 48.9MB/s]
- 76%|#######6 | 34.1M/44.7M [00:00<00:00, 46.6MB/s]
- 93%|#########2| 41.5M/44.7M [00:00<00:00, 55.0MB/s]
-100%|##########| 44.7M/44.7M [00:00<00:00, 56.3MB/s]
+ 32%|###2 | 14.3M/44.7M [00:00<00:00, 142MB/s]
+ 62%|######2 | 27.9M/44.7M [00:00<00:00, 92.7MB/s]
+ 86%|########5 | 38.3M/44.7M [00:00<00:00, 83.1MB/s]
+100%|##########| 44.7M/44.7M [00:00<00:00, 68.9MB/s]
</pre></div>
</div>
</div>
diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index 6d2a4cc9d5..31cf9d47c7 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -645,7 +645,7 @@ banana (score = 0.00022)
desk (score = 0.00019)
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 11.071 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 13.893 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-tensorflow-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7f1d3d1b878694c201c614c807cdebc8/from_tensorflow.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_tensorflow.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/sg_execution_times.html b/docs/how_to/compile_models/sg_execution_times.html
index 906df128a0..27260f07d7 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-compile-models-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>05:40.684</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>05:49.535</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -349,43 +349,43 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="from_tensorflow.html#sphx-glr-how-to-compile-models-from-tensorflow-py"><span class="std std-ref">Compile Tensorflow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tensorflow.py</span></code>)</p></td>
-<td><p>01:11.071</p></td>
+<td><p>01:13.893</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_darknet.html#sphx-glr-how-to-compile-models-from-darknet-py"><span class="std std-ref">Compile YOLO-V2 and YOLO-V3 in DarkNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_darknet.py</span></code>)</p></td>
-<td><p>01:10.168</p></td>
+<td><p>01:11.752</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_paddle.html#sphx-glr-how-to-compile-models-from-paddle-py"><span class="std std-ref">Compile PaddlePaddle Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_paddle.py</span></code>)</p></td>
-<td><p>00:45.262</p></td>
+<td><p>00:47.345</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_oneflow.html#sphx-glr-how-to-compile-models-from-oneflow-py"><span class="std std-ref">Compile OneFlow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_oneflow.py</span></code>)</p></td>
-<td><p>00:31.272</p></td>
+<td><p>00:32.784</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_mxnet.html#sphx-glr-how-to-compile-models-from-mxnet-py"><span class="std std-ref">Compile MXNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_mxnet.py</span></code>)</p></td>
-<td><p>00:28.243</p></td>
+<td><p>00:29.055</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_coreml.html#sphx-glr-how-to-compile-models-from-coreml-py"><span class="std std-ref">Compile CoreML Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_coreml.py</span></code>)</p></td>
-<td><p>00:25.879</p></td>
+<td><p>00:26.278</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_tflite.html#sphx-glr-how-to-compile-models-from-tflite-py"><span class="std std-ref">Compile TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tflite.py</span></code>)</p></td>
-<td><p>00:25.755</p></td>
+<td><p>00:25.495</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_pytorch.html#sphx-glr-how-to-compile-models-from-pytorch-py"><span class="std std-ref">Compile PyTorch Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_pytorch.py</span></code>)</p></td>
-<td><p>00:22.251</p></td>
+<td><p>00:22.531</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_keras.html#sphx-glr-how-to-compile-models-from-keras-py"><span class="std std-ref">Compile Keras Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_keras.py</span></code>)</p></td>
-<td><p>00:18.356</p></td>
+<td><p>00:17.956</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_onnx.html#sphx-glr-how-to-compile-models-from-onnx-py"><span class="std std-ref">Compile ONNX Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_onnx.py</span></code>)</p></td>
-<td><p>00:02.427</p></td>
+<td><p>00:02.446</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno.html b/docs/how_to/deploy_models/deploy_model_on_adreno.html
index dc87d3d3a0..fa53dac021 100644
--- a/docs/how_to/deploy_models/deploy_model_on_adreno.html
+++ b/docs/how_to/deploy_models/deploy_model_on_adreno.html
@@ -919,10 +919,9 @@ Top5 predictions:
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 3348.4568 3345.1975 3361.9201 3344.0796 5.4964
+ 2547.1204 2547.1048 2554.2133 2542.3841 3.3906
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 0.780 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-model-on-adreno-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/2387d8448da213eb625e6b3d916327d4/deploy_model_on_adreno.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_model_on_adreno.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_model_on_android.html b/docs/how_to/deploy_models/deploy_model_on_android.html
index a582764405..9522d022e0 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -661,7 +661,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.2571 16.4238 16.8795 15.6466 0.3999
+ 16.0696 15.9438 16.8597 15.8614 0.3103
</pre></div>
</div>
</div>
diff --git a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
index 5cc3826344..8236ff25ea 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -453,29 +453,29 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
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/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torch/nn/functional.py:3897: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
for i in range(dim)
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/torchvision/models/detection/anchor_utils.py:124: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode=& [...]
@@ -573,7 +573,7 @@ torchvision rcnn models.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get 9 valid boxes
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 11.704 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 16.695 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-object-detection-pytorch-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7795da4b258c8feff986668b95ef57ad/deploy_object_detection_pytorch.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_object_detection_pytorch.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_prequantized.html b/docs/how_to/deploy_models/deploy_prequantized.html
index d4e3b9f288..01280c6dda 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -497,8 +497,9 @@ training. Other models require a full post training calibration.</p>
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
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</pre></div>
</div>
</div>
@@ -589,7 +590,7 @@ output values are identical out of 1000 outputs from mobilenet v2.</p>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 90.2933 90.2321 91.3954 89.9113 0.2483
+ 90.3714 90.2342 93.3864 90.0915 0.5081
</pre></div>
</div>
<div class="admonition note">
@@ -628,7 +629,7 @@ This includes support for the VNNI 8 bit dot product instruction (CascadeLake or
<div class="section" id="deploy-a-quantized-tflite-model">
<h2>Deploy a quantized TFLite Model<a class="headerlink" href="#deploy-a-quantized-tflite-model" title="Permalink to this headline">¶</a></h2>
<p>TODO</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 5.237 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.569 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-prequantized-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/fb8217c13f4351224c6cf3aacf1a87fc/deploy_prequantized.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_prequantized.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_prequantized_tflite.html b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
index 92aeb155fb..d84722b176 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -582,7 +582,7 @@ TFLite Top-5 labels: [387 102 386 341 349]
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 119.7400 119.7851 125.3382 117.6290 0.9048
+ 120.7364 120.6843 125.5776 120.0880 0.5749
</pre></div>
</div>
<div class="admonition note">
@@ -610,7 +610,7 @@ network for ARM CPU</span></a>.</p></li>
</ul>
</div></blockquote>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 23.226 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 24.507 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-prequantized-tflite-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/56691c7a27d45da61d112276334640d3/deploy_prequantized_tflite.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_prequantized_tflite.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_quantized.html b/docs/how_to/deploy_models/deploy_quantized.html
index d6c8cb1868..4eabb6b938 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -520,7 +520,7 @@ for calibration. But the accuracy might be impacted.</p>
DeprecationWarning,
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 33.840 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 34.139 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-quantized-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7810ecf51bfc05f7d5e8a400ac3e815d/deploy_quantized.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_quantized.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_ssd_gluoncv.html b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
index a77fb8ee77..fa8557cc6d 100644
--- a/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
+++ b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
@@ -462,24 +462,22 @@ to your device.</p>
Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/ssd_512_resnet50_v1_voc-9c8b225a.zip...
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</pre></div>
</div>
<p>Create TVM runtime and do inference
@@ -518,7 +516,7 @@ Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from h
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
</div>
-<img src="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" srcset="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" alt="deploy ssd gluoncv" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 5.044 seconds)</p>
+<img src="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" srcset="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" alt="deploy ssd gluoncv" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 11.827 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-ssd-gluoncv-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/cccb17d28e5e8b2e94ea8cd5ec59f6ed/deploy_ssd_gluoncv.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_ssd_gluoncv.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/sg_execution_times.html b/docs/how_to/deploy_models/sg_execution_times.html
index aae8fa994f..fedee4372a 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
+++ b/docs/how_to/deploy_models/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-deploy-models-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>13:44.102</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>13:51.776</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 86%" />
@@ -349,43 +349,43 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_object_detection_pytorch.html#sphx-glr-how-to-deploy-models-deploy-object-detection-pytorch-py"><span class="std std-ref">Compile PyTorch Object Detection Models</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_object_detection_pytorch.py</span></code>)</p></td>
-<td><p>03:11.704</p></td>
+<td><p>03:16.695</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_ssd_gluoncv.html#sphx-glr-how-to-deploy-models-deploy-ssd-gluoncv-py"><span class="std std-ref">Deploy Single Shot Multibox Detector(SSD) model</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_ssd_gluoncv.py</span></code>)</p></td>
-<td><p>03:05.044</p></td>
+<td><p>03:11.827</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_prequantized_tflite.html#sphx-glr-how-to-deploy-models-deploy-prequantized-tflite-py"><span class="std std-ref">Deploy a Framework-prequantized Model with TVM - Part 3 (TFLite)</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_prequantized_tflite.py</span></code>)</p></td>
-<td><p>02:23.226</p></td>
+<td><p>02:24.507</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_quantized.html#sphx-glr-how-to-deploy-models-deploy-quantized-py"><span class="std std-ref">Deploy a Quantized Model on Cuda</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_quantized.py</span></code>)</p></td>
-<td><p>01:33.840</p></td>
+<td><p>01:34.139</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_prequantized.html#sphx-glr-how-to-deploy-models-deploy-prequantized-py"><span class="std std-ref">Deploy a Framework-prequantized Model with TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_prequantized.py</span></code>)</p></td>
-<td><p>01:05.237</p></td>
+<td><p>01:06.569</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_adreno.html#sphx-glr-how-to-deploy-models-deploy-model-on-adreno-py"><span class="std std-ref">Deploy the Pretrained Model on Adreno</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_adreno.py</span></code>)</p></td>
-<td><p>01:00.780</p></td>
+<td><p>00:51.905</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_android.html#sphx-glr-how-to-deploy-models-deploy-model-on-android-py"><span class="std std-ref">Deploy the Pretrained Model on Android</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_android.py</span></code>)</p></td>
-<td><p>00:34.912</p></td>
+<td><p>00:35.780</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_nano.html#sphx-glr-how-to-deploy-models-deploy-model-on-nano-py"><span class="std std-ref">Deploy the Pretrained Model on Jetson Nano</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_nano.py</span></code>)</p></td>
-<td><p>00:24.859</p></td>
+<td><p>00:25.335</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_rasp.html#sphx-glr-how-to-deploy-models-deploy-model-on-rasp-py"><span class="std std-ref">Deploy the Pretrained Model on Raspberry Pi</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_rasp.py</span></code>)</p></td>
-<td><p>00:24.493</p></td>
+<td><p>00:25.013</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_sparse.html#sphx-glr-how-to-deploy-models-deploy-sparse-py"><span class="std std-ref">Deploy a Hugging Face Pruned Model on CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_sparse.py</span></code>)</p></td>
-<td><p>00:00.006</p></td>
+<td><p>00:00.007</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/extend_tvm/bring_your_own_datatypes.html b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
index 9791b5ad42..7ed1f88ff9 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -621,7 +621,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
<span class="n">module</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">params</span></a> <span class="o">=</span> <span class="n">get_mobilenet</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip4824e17e-a166-4fed-b828-ee461dc0ac4d from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip990560b3-c5a6-485d-bf0e-1e676b72ad40 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
</pre></div>
</div>
<p>It’s easy to execute MobileNet with native TVM:</p>
diff --git a/docs/how_to/extend_tvm/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index 6465e22014..653a28856b 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-extend-tvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:46.868</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:47.833</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -349,15 +349,15 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="bring_your_own_datatypes.html#sphx-glr-how-to-extend-tvm-bring-your-own-datatypes-py"><span class="std std-ref">Bring Your Own Datatypes to TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">bring_your_own_datatypes.py</span></code>)</p></td>
-<td><p>00:43.502</p></td>
+<td><p>00:44.347</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="use_pass_instrument.html#sphx-glr-how-to-extend-tvm-use-pass-instrument-py"><span class="std std-ref">How to Use TVM Pass Instrument</span></a> (<code class="docutils literal notranslate"><span class="pre">use_pass_instrument.py</span></code>)</p></td>
-<td><p>00:02.341</p></td>
+<td><p>00:02.444</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="use_pass_infra.html#sphx-glr-how-to-extend-tvm-use-pass-infra-py"><span class="std std-ref">How to Use TVM Pass Infra</span></a> (<code class="docutils literal notranslate"><span class="pre">use_pass_infra.py</span></code>)</p></td>
-<td><p>00:01.016</p></td>
+<td><p>00:01.034</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="low_level_custom_pass.html#sphx-glr-how-to-extend-tvm-low-level-custom-pass-py"><span class="std std-ref">Writing a Customized Pass</span></a> (<code class="docutils literal notranslate"><span class="pre">low_level_custom_pass.py</span></code>)</p></td>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 3428dd223b..d9536fc124 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -525,10 +525,10 @@ profile the execution time of each passes.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 7130us [7130us] (46.31%; 46.31%)
-FoldScaleAxis: 8267us [6us] (53.69%; 53.69%)
- FoldConstant: 8261us [1688us] (53.65%; 99.93%)
- InferType: 6573us [6573us] (42.69%; 79.57%)
+InferType: 7283us [7283us] (46.20%; 46.20%)
+FoldScaleAxis: 8481us [7us] (53.80%; 53.80%)
+ FoldConstant: 8475us [1707us] (53.76%; 99.92%)
+ InferType: 6768us [6768us] (42.93%; 79.86%)
</pre></div>
</div>
</div>
@@ -550,10 +550,10 @@ Refer to following sections and <a class="reference internal" href="../../refere
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 6608us [6608us] (45.09%; 45.09%)
-FoldScaleAxis: 8046us [5us] (54.91%; 54.91%)
- FoldConstant: 8041us [1662us] (54.87%; 99.94%)
- InferType: 6379us [6379us] (43.53%; 79.33%)
+InferType: 6747us [6747us] (44.98%; 44.98%)
+FoldScaleAxis: 8254us [5us] (55.02%; 55.02%)
+ FoldConstant: 8249us [1693us] (54.99%; 99.94%)
+ InferType: 6556us [6556us] (43.71%; 79.48%)
</pre></div>
</div>
<p>Register empty list to clear existing instruments.</p>
diff --git a/docs/how_to/optimize_operators/opt_conv_cuda.html b/docs/how_to/optimize_operators/opt_conv_cuda.html
index ec13589352..ccbadb4efe 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -577,7 +577,7 @@ latency of convolution.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Convolution: </span><span class="si">%f</span><span class="s2"> ms"</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">*</span> <span cl [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 53.060577 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 48.410495 ms
</pre></div>
</div>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-optimize-operators-opt-conv-cuda-py">
diff --git a/docs/how_to/optimize_operators/opt_conv_tensorcore.html b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
index 56853e52d7..fcf76c3acf 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -914,7 +914,7 @@ be able to run on our build server</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"conv2d with tensor core: </span><span class="si">%f</span><span class="s2"> ms"</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">* [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 13.369591 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 13.354384 ms
</pre></div>
</div>
</div>
diff --git a/docs/how_to/optimize_operators/opt_gemm.html b/docs/how_to/optimize_operators/opt_gemm.html
index 057c542fc1..943fde495c 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -474,8 +474,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
<span class="nb">print</span><span class="p">(</span><span class="s2">"Baseline: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.018622
-Baseline: 3.335183
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.019184
+Baseline: 3.423127
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -534,7 +534,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt1: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.307949
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.312657
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -600,7 +600,7 @@ vastly.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt2: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.329713
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.342196
</pre></div>
</div>
<p>Here is the generated IR after vectorization.</p>
@@ -660,7 +660,7 @@ the access pattern for A matrix is more cache friendly.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt3: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.115594
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.119240
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -742,7 +742,7 @@ flattening.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt4: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.109935
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.109000
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -827,7 +827,7 @@ write to C when all the block results are ready.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt5: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.116148
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.111107
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -916,7 +916,7 @@ write to C when all the block results are ready.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt6: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">opt6_time</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.152512
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.147616
</pre></div>
</div>
<p>Here is the generated IR after parallelization.</p>
diff --git a/docs/how_to/optimize_operators/sg_execution_times.html b/docs/how_to/optimize_operators/sg_execution_times.html
index 833a020eb8..a400f3127c 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-optimize-operators-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:35.205</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:35.375</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -349,15 +349,15 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="opt_gemm.html#sphx-glr-how-to-optimize-operators-opt-gemm-py"><span class="std std-ref">How to optimize GEMM on CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">opt_gemm.py</span></code>)</p></td>
-<td><p>00:32.436</p></td>
+<td><p>00:32.677</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="opt_conv_tensorcore.html#sphx-glr-how-to-optimize-operators-opt-conv-tensorcore-py"><span class="std std-ref">How to optimize convolution using TensorCores</span></a> (<code class="docutils literal notranslate"><span class="pre">opt_conv_tensorcore.py</span></code>)</p></td>
-<td><p>00:01.573</p></td>
+<td><p>00:01.565</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="opt_conv_cuda.html#sphx-glr-how-to-optimize-operators-opt-conv-cuda-py"><span class="std std-ref">How to optimize convolution on GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">opt_conv_cuda.py</span></code>)</p></td>
-<td><p>00:01.197</p></td>
+<td><p>00:01.133</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
index a355d774d9..9e25d20fe7 100644
--- a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
+++ b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-tune-with-autoscheduler-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>08:50.704</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>09:07.560</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -349,27 +349,27 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_layer_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py"><span class="std std-ref">Auto-scheduling a Convolution Layer for GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_layer_cuda.py</span></code>)</p></td>
-<td><p>05:27.254</p></td>
+<td><p>05:41.793</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_x86.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-x86-py"><span class="std std-ref">Auto-scheduling a Neural Network for x86 CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_x86.py</span></code>)</p></td>
-<td><p>01:31.095</p></td>
+<td><p>01:33.478</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-cuda-py"><span class="std std-ref">Auto-scheduling a Neural Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_cuda.py</span></code>)</p></td>
-<td><p>01:01.281</p></td>
+<td><p>01:01.827</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_sparse_x86.html#sphx-glr-how-to-tune-with-autoscheduler-tune-sparse-x86-py"><span class="std std-ref">Auto-scheduling Sparse Matrix Multiplication on CPU with Custom Sketch Rule</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_sparse_x86.py</span></code>)</p></td>
-<td><p>00:28.056</p></td>
+<td><p>00:27.648</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_arm.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-arm-py"><span class="std std-ref">Auto-scheduling a Neural Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_arm.py</span></code>)</p></td>
-<td><p>00:11.974</p></td>
+<td><p>00:11.843</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
-<td><p>00:11.045</p></td>
+<td><p>00:10.971</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html b/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
index 57a505caf3..535885946f 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
@@ -488,6 +488,9 @@ file and apply it.</p>
<span class="k">del</span> <span class="n">measure_ctx</span>
</pre></div>
</div>
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>.T
+</pre></div>
+</div>
<p>We can lower the schedule to see the IR after auto-scheduling.
The auto-scheduler correctly performs optimizations including multi-level tiling,
cooperative fetching, unrolling and operator fusion.</p>
@@ -1016,7 +1019,7 @@ cooperative fetching, unrolling and operator fusion.</p>
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.358 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.350 ms
</pre></div>
</div>
</div>
@@ -1579,7 +1582,7 @@ In the example below we resume the status and do more 5 trials.</p>
Get devices for measurement successfully!
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 27.254 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 41.793 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/e3e540f3b477c0c52d8eb73e674e8ffd/tune_conv2d_layer_cuda.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_conv2d_layer_cuda.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
index d957900b72..31c64a2f4e 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -915,7 +915,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 7.8974 7.8946 7.9083 7.8892 0.0080
+ 7.8518 7.8494 7.8611 7.8449 0.0068
</pre></div>
</div>
</div>
@@ -937,7 +937,7 @@ to learn how to use the RPC Tracker and RPC Server.
To use the RPC Tracker in auto-scheduler, replace the runner in <code class="code docutils literal notranslate"><span class="pre">TuningOptions</span></code>
with <a class="reference internal" href="../../reference/api/python/auto_scheduler.html#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref any py py-class docutils literal notranslate"><span class="pre">auto_scheduler.RPCRunner</span></code></a>.</p></li>
</ol>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 1.281 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 1.827 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-cuda-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/eafe360d52540634c9eea0fa89e804bd/tune_network_cuda.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_cuda.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
index a6a80caf36..90813b7e2b 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -934,7 +934,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 755.4578 755.6234 755.8838 754.8663 0.4316
+ 756.5267 757.7776 759.3899 752.4125 2.9827
</pre></div>
</div>
</div>
@@ -956,7 +956,7 @@ to learn how to use the RPC Tracker and RPC Server.
To use the RPC Tracker in auto-scheduler, replace the runner in <code class="code docutils literal notranslate"><span class="pre">TuningOptions</span></code>
with <a class="reference internal" href="../../reference/api/python/auto_scheduler.html#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref any py py-class docutils literal notranslate"><span class="pre">auto_scheduler.RPCRunner</span></code></a>.</p></li>
</ol>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 31.095 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 33.478 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-x86-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/e416b94ca1090b0897c0f6e0df95b911/tune_network_x86.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_x86.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
index ebcb4a16d4..18a3ebbffa 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
@@ -632,75 +632,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [128, 512], []),
compute: Buffer(compute_2: Pointer(float32), float32, [128, 512], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute} {
- for (i0.outer.i1.outer.fused: int32, 0, 64) "parallel" {
- allocate(compute_3: Pointer(global float32), float32, [1024]), storage_scope = global {
+ for (i0.outer.i1.outer.fused: int32, 0, 32) "parallel" {
+ allocate(compute_3: Pointer(global float32), float32, [2048]), storage_scope = global {
for (nb_j.inner: int32, 0, 2) {
- for (i.inner.init: int32, 0, 32) {
- let cse_var_1: int32 = ((i.inner.init*32) + (nb_j.inner*16))
- {
- compute_4: Buffer(compute_3, float32, [1024], [])[cse_var_1] = 0f32
- compute_4[(cse_var_1 + 1)] = 0f32
- compute_4[(cse_var_1 + 2)] = 0f32
- compute_4[(cse_var_1 + 3)] = 0f32
- compute_4[(cse_var_1 + 4)] = 0f32
- compute_4[(cse_var_1 + 5)] = 0f32
- compute_4[(cse_var_1 + 6)] = 0f32
- compute_4[(cse_var_1 + 7)] = 0f32
- compute_4[(cse_var_1 + 8)] = 0f32
- compute_4[(cse_var_1 + 9)] = 0f32
- compute_4[(cse_var_1 + 10)] = 0f32
- compute_4[(cse_var_1 + 11)] = 0f32
- compute_4[(cse_var_1 + 12)] = 0f32
- compute_4[(cse_var_1 + 13)] = 0f32
- compute_4[(cse_var_1 + 14)] = 0f32
- compute_4[(cse_var_1 + 15)] = 0f32
+ for (i.inner.init: int32, 0, 64) {
+ for (j.init: int32, 0, 16) {
+ compute_4: Buffer(compute_3, float32, [2048], [])[(((i.inner.init*32) + (nb_j.inner*16)) + j.init)] = 0f32
}
}
- for (elem_idx: int32, 0, let cse_var_2: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_15: Buffer(placeholder_13, int32, [33], [])[(cse_var_2 + 1)] - placeholder_15[cse_var_2])) {
- for (i.inner: int32, 0, 32) {
- let cse_var_21: int32 = (elem_idx*16)
- let cse_var_20: int32 = ((i.inner*32) + (nb_j.inner*16))
- let cse_var_19: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
- let cse_var_18: int32 = ((floordiv(i0.outer.i1.outer.fused, 16)*8192) + (i.inner*256))
- let cse_var_17: int32 = (cse_var_20 + 9)
- let cse_var_16: int32 = (cse_var_20 + 8)
- let cse_var_15: int32 = (cse_var_20 + 7)
- let cse_var_14: int32 = (cse_var_20 + 6)
- let cse_var_13: int32 = (cse_var_20 + 5)
- let cse_var_12: int32 = (cse_var_20 + 4)
- let cse_var_11: int32 = (cse_var_20 + 3)
- let cse_var_10: int32 = (cse_var_20 + 2)
- let cse_var_9: int32 = (cse_var_20 + 15)
- let cse_var_8: int32 = (cse_var_20 + 14)
- let cse_var_7: int32 = (cse_var_20 + 13)
- let cse_var_6: int32 = (cse_var_20 + 12)
- let cse_var_5: int32 = (cse_var_20 + 11)
- let cse_var_4: int32 = (cse_var_20 + 10)
- let cse_var_3: int32 = (cse_var_20 + 1)
- {
- compute_4[cse_var_20] = (compute_4[cse_var_20] + (placeholder_16: Buffer(placeholder_11, float32, [78656], [])[((placeholder_15[cse_var_19]*16) + cse_var_21)]*max(placeholder_17: Buffer(placeholder_10, float32, [32768], [])[(cse_var_18 + placeholder_18: Buffer(placeholder_12, int32, [4916], [])[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_3] = (compute_4[cse_var_3] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 1)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_10] = (compute_4[cse_var_10] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 2)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_11] = (compute_4[cse_var_11] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 3)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_12] = (compute_4[cse_var_12] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 4)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_13] = (compute_4[cse_var_13] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 5)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_14] = (compute_4[cse_var_14] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 6)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_15] = (compute_4[cse_var_15] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 7)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_16] = (compute_4[cse_var_16] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 8)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_17] = (compute_4[cse_var_17] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 9)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_4] = (compute_4[cse_var_4] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 10)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_5] = (compute_4[cse_var_5] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 11)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_6] = (compute_4[cse_var_6] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 12)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_7] = (compute_4[cse_var_7] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 13)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_8] = (compute_4[cse_var_8] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 14)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
- compute_4[cse_var_9] = (compute_4[cse_var_9] + (placeholder_16[(((placeholder_15[cse_var_19]*16) + cse_var_21) + 15)]*max(placeholder_17[(cse_var_18 + placeholder_18[(placeholder_15[cse_var_19] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, let cse_var_1: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_15: Buffer(placeholder_13, int32, [33], [])[(cse_var_1 + 1)] - placeholder_15[cse_var_1])) {
+ for (i.inner: int32, 0, 64) {
+ for (j: int32, 0, 16) {
+ let cse_var_3: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_2: int32 = (((i.inner*32) + (nb_j.inner*16)) + j)
+ compute_4[cse_var_2] = (compute_4[cse_var_2] + (placeholder_16: Buffer(placeholder_11, float32, [78656], [])[(((placeholder_15[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder_17: Buffer(placeholder_10, float32, [32768], [])[(((floordiv(i0.outer.i1.outer.fused, 16)*16384) + (i.inner*256)) + placeholder_18: Buffer(placeholder_12, int32, [4916], [])[(placeholder_15[cse_var_3] + elem_idx)])], 0f32)))
}
}
}
}
- for (i0.inner: int32, 0, 32) {
- let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*16384) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32))
- compute_5: Buffer(compute_2, float32, [65536], [])[ramp(cse_var_22, 1, 32)] = max((compute_4[ramp((i0.inner*32), 1, 32)] + placeholder_19: Buffer(placeholder_14, float32, [65536], [])[ramp(cse_var_22, 1, 32)]), broadcast(0f32, 32))
+ for (i0.inner: int32, 0, 64) {
+ for (i1.inner: int32, 0, 32) {
+ let cse_var_4: int32 = ((((floordiv(i0.outer.i1.outer.fused, 16)*32768) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32)) + i1.inner)
+ compute_5: Buffer(compute_2, float32, [65536], [])[cse_var_4] = max((compute_4[((i0.inner*32) + i1.inner)] + placeholder_19: Buffer(placeholder_14, float32, [65536], [])[cse_var_4]), 0f32)
+ }
}
}
}
@@ -738,7 +692,7 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.765 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.814 ms
</pre></div>
</div>
<div class="admonition note">
diff --git a/docs/how_to/tune_with_autotvm/sg_execution_times.html b/docs/how_to/tune_with_autotvm/sg_execution_times.html
index a177bdb25f..6fc0e9ae90 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-tune-with-autotvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:39.839</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:35.571</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -349,7 +349,7 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-conv2d-cuda-py"><span class="std std-ref">Tuning High Performance Convolution on NVIDIA GPUs</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_cuda.py</span></code>)</p></td>
-<td><p>00:39.805</p></td>
+<td><p>00:35.535</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_x86.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-x86-py"><span class="std std-ref">Auto-tuning a Convolutional Network for x86 CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_x86.py</span></code>)</p></td>
diff --git a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
index 52dd7a9e3f..9db37310f5 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -587,21 +587,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -619,11 +619,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -643,21 +643,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -675,11 +675,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -689,161 +689,132 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 128, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5808757
-No: 2 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 742, in __call__
- yield remote, remote.load_module(os.path.split(build_result.filename)[1])
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/workspace/python/tvm/runtime/module.py", line 357, in evaluator
- blob = feval(*args)
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 16, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2157448
+No: 2 GFLOPS: 2.33/2.33 result: MeasureResult(costs=(0.09927782425,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.730562210083008, timestamp=1670200892.4803033) [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4520513
+No: 3 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
+ func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
+ func = build(s, args, target_host=task.target_host, runtime=runtime)
+ File "/workspace/python/tvm/driver/build_module.py", line 227, in build
+ input_mod = lower(inputs, args, name=name, binds=binds)
+ File "/workspace/python/tvm/driver/build_module.py", line 134, in lower
+ return ffi.lower_schedule(inp, args, name, binds, simple_mode)
File "tvm/_ffi/_cython/./packed_func.pxi", line 331, in tvm._ffi._cy3.core.PackedFuncBase.__call__
- File "tvm/_ffi/_cython/./packed_func.pxi", line 262, in tvm._ffi._cy3.core.FuncCall
- File "tvm/_ffi/_cython/./packed_func.pxi", line 251, in tvm._ffi._cy3.core.FuncCall3
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 276, in tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 181, in tvm._ffi._cy3.core.CHECK_CALL
tvm._ffi.base.TVMError: Traceback (most recent call last):
- 4: TVMFuncCall
+ 24: TVMFuncCall
at ../src/runtime/c_runtime_api.cc:477
- 3: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
- 2: tvm::runtime::RPCWrappedFunc::operator()(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
- at ../src/runtime/rpc/rpc_module.cc:129
- 1: tvm::runtime::RPCClientSession::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)> const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1012
- 0: tvm::runtime::RPCEndpoint::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)>)
- at ../src/runtime/rpc/rpc_endpoint.cc:804
- File "../src/runtime/rpc/rpc_endpoint.cc", line 804
-TVMError:
----------------------------------------------------------------
-An error occurred during the execution of TVM.
-For more information, please see: https://tvm.apache.org/docs/errors.html
----------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=kShutdown
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/usr/lib/python3.7/contextlib.py", line 130, in __exit__
- self.gen.throw(type, value, traceback)
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 746, in __call__
- remote.remove(build_result.filename)
- File "/workspace/python/tvm/rpc/client.py", line 144, in remove
- self._remote_funcs["remove"] = self.get_function("tvm.rpc.server.remove")
- File "/workspace/python/tvm/rpc/client.py", line 72, in get_function
- return self._sess.get_function(name)
- File "/workspace/python/tvm/runtime/module.py", line 171, in get_function
- self.handle, c_str(name), ctypes.c_int(query_imports), ctypes.byref(ret_handle)
- File "/workspace/python/tvm/_ffi/base.py", line 348, in check_call
- raise get_last_ffi_error()
-tvm._ffi.base.TVMError: Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCallKeywords
- 18: _PyEval_EvalFrameDefault
- 17: _PyFunction_FastCallKeywords
- 16: _PyEval_EvalCodeWithName
- 15: _PyEval_EvalFrameDefault
- 14: 0x0000000000537c30
- 13: _PyObject_FastCallKeywords
- 12: 0x00007fc5ed7edfa2
- 11: _ctypes_callproc
- 10: ffi_call
- 9: ffi_call_unix64
- 8: TVMModGetFunction
- at ../src/runtime/c_runtime_api.cc:408
- 7: tvm::runtime::ModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool)
- at ../src/runtime/module.cc:66
- 6: tvm::runtime::RPCModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)
- at ../src/runtime/rpc/rpc_module.cc:185
- 5: tvm::runtime::RPCClientSession::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1007
- 4: tvm::runtime::TVMRetValue tvm::runtime::RPCEndpoint::SysCallRemote<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(tvm::runtime::RPCCode, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.h:223
- 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(int&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
at ../include/tvm/runtime/packed_func.h:1213
0: operator()
- at ../src/runtime/rpc/rpc_endpoint.cc:684
- File "../src/runtime/rpc/rpc_endpoint.cc", line 684
-TVMError:
----------------------------------------------------------------
-An error occurred during the execution of TVM.
-For more information, please see: https://tvm.apache.org/docs/errors.html
----------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=1
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel
Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCall [('tile_f', [-1, 16, 1, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7366889
-No: 3 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+ 24: TVMFuncCall
+ at ../src/runtime/c_runtime_api.cc:477
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
+ 2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 1: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 0: operator()
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 1, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 1, 256]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10250404
+No: 4 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -863,21 +834,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -895,11 +866,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -919,21 +890,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -951,11 +922,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -965,8 +936,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 1, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,916283
-No: 4 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 4, 8]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 256, 2]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8391612
+No: 5 GFLOPS: 0.00/2.33 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -986,21 +957,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1018,11 +989,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1042,21 +1013,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1074,11 +1045,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1088,8 +1059,9 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2792794
-No: 5 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 4, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 256]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6961579
+No: 6 GFLOPS: 58.51/58.51 result: MeasureResult(costs=(0.003956673818181818,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.059903621673584, timestamp=1670200897.6246755) [('tile_f', [-1, 2, 8, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 64]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2290448
+No: 7 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1109,21 +1081,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1141,11 +1113,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1165,21 +1137,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1197,11 +1169,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1211,8 +1183,9 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 256]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9658217
-No: 6 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 1, 8]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4351736
+No: 8 GFLOPS: 56.48/58.51 result: MeasureResult(costs=(0.00409861752,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.9851655960083008, timestamp=1670200898.290892) [('tile_f', [-1, 1, 4, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 512, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,32235
+No: 9 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1232,21 +1205,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1264,11 +1237,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1288,21 +1261,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1320,11 +1293,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1334,8 +1307,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 1]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,3128666
-No: 7 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 1, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3857586
+No: 10 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1355,21 +1328,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1387,11 +1360,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1411,21 +1384,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1443,11 +1416,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1457,8 +1430,9 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 8, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7467584
-No: 8 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 16, 2]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 1, 32]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,1886149
+No: 11 GFLOPS: 5.26/58.51 result: MeasureResult(costs=(0.043981414749999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.0867502689361572, timestamp=1670200900.554806) [('tile_f', [-1, 2, 2, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 64, 2]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,5089985
+No: 12 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1478,21 +1452,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1510,11 +1484,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1534,21 +1508,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1566,11 +1540,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1580,11 +1554,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5598341
-No: 9 GFLOPS: 34.16/34.16 result: MeasureResult(costs=(0.00677683211764706,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.503911018371582, timestamp=1670035927.063999) [('tile_f', [-1, 8, 2, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 8, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2371447
-No: 10 GFLOPS: 10.46/34.16 result: MeasureResult(costs=(0.022140299333333332,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.149139404296875, timestamp=1670035927.952396) [('tile_f', [-1, 1, 4, 4]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 16, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8405875
-No: 11 GFLOPS: 76.71/76.71 result: MeasureResult(costs=(0.0030177834411764704,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3312666416168213, timestamp=1670035928.6008291) [('tile_f', [-1, 4, 2, 4]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 16, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2372810
-No: 12 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 128, 2]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2771512
+No: 13 GFLOPS: 0.00/58.51 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1604,21 +1575,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1636,11 +1607,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1660,21 +1631,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1692,11 +1663,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1706,8 +1677,9 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 2, 2]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 16]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2841804
-No: 13 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7771677
+No: 14 GFLOPS: 70.65/70.65 result: MeasureResult(costs=(0.0032768214375000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.235529184341431, timestamp=1670200904.9939046) [('tile_f', [-1, 2, 16, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 8]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,8817466
+No: 15 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1727,21 +1699,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1759,11 +1731,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1783,21 +1755,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1815,11 +1787,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1829,8 +1801,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 16, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 128]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,953735
-No: 14 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 4, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 16]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1486785
+No: 16 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1850,21 +1822,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1882,11 +1854,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1906,21 +1878,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -1938,11 +1910,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -1952,9 +1924,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 128, 4, 1]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 16, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3620126
-No: 15 GFLOPS: 17.91/76.71 result: MeasureResult(costs=(0.012923107555555556,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.104569911956787, timestamp=1670035930.9178731) [('tile_f', [-1, 8, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,8186523
-No: 16 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 4]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5824854
+No: 17 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -1974,21 +1945,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2006,11 +1977,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2030,21 +2001,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2062,11 +2033,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2076,161 +2047,131 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 32, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 64]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6941042
-No: 17 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 742, in __call__
- yield remote, remote.load_module(os.path.split(build_result.filename)[1])
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/workspace/python/tvm/runtime/module.py", line 357, in evaluator
- blob = feval(*args)
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 64, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9904275
+No: 18 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
+ func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
+ func = build(s, args, target_host=task.target_host, runtime=runtime)
+ File "/workspace/python/tvm/driver/build_module.py", line 227, in build
+ input_mod = lower(inputs, args, name=name, binds=binds)
+ File "/workspace/python/tvm/driver/build_module.py", line 134, in lower
+ return ffi.lower_schedule(inp, args, name, binds, simple_mode)
File "tvm/_ffi/_cython/./packed_func.pxi", line 331, in tvm._ffi._cy3.core.PackedFuncBase.__call__
- File "tvm/_ffi/_cython/./packed_func.pxi", line 262, in tvm._ffi._cy3.core.FuncCall
- File "tvm/_ffi/_cython/./packed_func.pxi", line 251, in tvm._ffi._cy3.core.FuncCall3
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 276, in tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 181, in tvm._ffi._cy3.core.CHECK_CALL
tvm._ffi.base.TVMError: Traceback (most recent call last):
- 4: TVMFuncCall
+ 24: TVMFuncCall
at ../src/runtime/c_runtime_api.cc:477
- 3: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
- 2: tvm::runtime::RPCWrappedFunc::operator()(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
- at ../src/runtime/rpc/rpc_module.cc:129
- 1: tvm::runtime::RPCClientSession::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)> const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1012
- 0: tvm::runtime::RPCEndpoint::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)>)
- at ../src/runtime/rpc/rpc_endpoint.cc:804
- File "../src/runtime/rpc/rpc_endpoint.cc", line 804
-TVMError:
----------------------------------------------------------------
-An error occurred during the execution of TVM.
-For more information, please see: https://tvm.apache.org/docs/errors.html
----------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=kShutdown
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 706, in run_through_rpc
- costs = time_f(*args).results
- File "/usr/lib/python3.7/contextlib.py", line 130, in __exit__
- self.gen.throw(type, value, traceback)
- File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 746, in __call__
- remote.remove(build_result.filename)
- File "/workspace/python/tvm/rpc/client.py", line 144, in remove
- self._remote_funcs["remove"] = self.get_function("tvm.rpc.server.remove")
- File "/workspace/python/tvm/rpc/client.py", line 72, in get_function
- return self._sess.get_function(name)
- File "/workspace/python/tvm/runtime/module.py", line 171, in get_function
- self.handle, c_str(name), ctypes.c_int(query_imports), ctypes.byref(ret_handle)
- File "/workspace/python/tvm/_ffi/base.py", line 348, in check_call
- raise get_last_ffi_error()
-tvm._ffi.base.TVMError: Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCallKeywords
- 18: _PyEval_EvalFrameDefault
- 17: _PyFunction_FastCallKeywords
- 16: _PyEval_EvalCodeWithName
- 15: _PyEval_EvalFrameDefault
- 14: 0x0000000000537c30
- 13: _PyObject_FastCallKeywords
- 12: 0x00007f2df7882fa2
- 11: _ctypes_callproc
- 10: ffi_call
- 9: ffi_call_unix64
- 8: TVMModGetFunction
- at ../src/runtime/c_runtime_api.cc:408
- 7: tvm::runtime::ModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool)
- at ../src/runtime/module.cc:66
- 6: tvm::runtime::RPCModuleNode::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)
- at ../src/runtime/rpc/rpc_module.cc:185
- 5: tvm::runtime::RPCClientSession::GetFunction(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.cc:1007
- 4: tvm::runtime::TVMRetValue tvm::runtime::RPCEndpoint::SysCallRemote<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(tvm::runtime::RPCCode, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
- at ../src/runtime/rpc/rpc_endpoint.h:223
- 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&>(int&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
at ../include/tvm/runtime/packed_func.h:1213
0: operator()
- at ../src/runtime/rpc/rpc_endpoint.cc:684
- File "../src/runtime/rpc/rpc_endpoint.cc", line 684
-TVMError:
----------------------------------------------------------------
-An error occurred during the execution of TVM.
-For more information, please see: https://tvm.apache.org/docs/errors.html
----------------------------------------------------------------
- Check failed: (code == RPCCode::kReturn) is false: code=1
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel
Traceback (most recent call last):
- 52: 0xffffffffffffffff
- 51: _start
- 50: __libc_start_main
- 49: _Py_UnixMain
- 48: 0x0000000000650da0
- 47: 0x0000000000650afa
- 46: _PyFunction_FastCallDict
- 45: _PyEval_EvalCodeWithName
- 44: _PyEval_EvalFrameDefault
- 43: _PyFunction_FastCallKeywords
- 42: _PyEval_EvalCodeWithName
- 41: _PyEval_EvalFrameDefault
- 40: _PyMethodDef_RawFastCallKeywords
- 39: 0x0000000000546369
- 38: _PyEval_EvalCodeWithName
- 37: _PyEval_EvalFrameDefault
- 36: _PyFunction_FastCallKeywords
- 35: _PyEval_EvalCodeWithName
- 34: _PyEval_EvalFrameDefault
- 33: _PyFunction_FastCallDict
- 32: _PyEval_EvalCodeWithName
- 31: _PyEval_EvalFrameDefault
- 30: _PyObject_FastCallDict
- 29: 0x00000000004c06e1
- 28: _PyFunction_FastCallDict
- 27: _PyEval_EvalFrameDefault
- 26: _PyMethodDescr_FastCallKeywords
- 25: 0x00000000005dcb58
- 24: 0x00000000005dc83f
- 23: 0x00000000004ba127
- 22: _PyEval_EvalFrameDefault
- 21: _PyFunction_FastCallKeywords
- 20: _PyEval_EvalFrameDefault
- 19: _PyFunction_FastCall [('tile_f', [-1, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,5691725
-No: 18 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+ 24: TVMFuncCall
+ at ../src/runtime/c_runtime_api.cc:477
+ 23: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 22: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 21: operator()
+ at ../include/tvm/runtime/packed_func.h:1730
+ 20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
+ at ../include/tvm/runtime/packed_func.h:1670
+ 19: run<>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 18: run<tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1630
+ 14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
+ at ../include/tvm/runtime/packed_func.h:1645
+ 13: operator()
+ at ../src/driver/driver_api.cc:388
+ 12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
+ at ../src/driver/driver_api.cc:374
+ 11: tvm::LowerWithPassList(tvm::IRModule, tvm::runtime::Array<tvm::transform::Pass, void>)
+ at ../src/driver/driver_api.cc:269
+ 10: tvm::transform::Pass::operator()(tvm::IRModule) const
+ at ../src/ir/transform.cc:258
+ 9: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 8: tvm::transform::SequentialNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:453
+ 7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/ir/transform.cc:274
+ 6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
+ at ../src/tir/ir/transform.cc:100
+ 5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
+ at ../include/tvm/runtime/packed_func.h:1749
+ 4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
+ at ../include/tvm/runtime/packed_func.h:1693
+ 3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
+ at ../include/tvm/runtime/packed_func.h:1617
+ 2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
+ at ../include/tvm/runtime/packed_func.h:1217
+ 1: Call
+ at ../include/tvm/runtime/packed_func.h:1213
+ 0: operator()
+ at ../src/runtime/c_runtime_api.cc:534
+ File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
+ File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
+ raise InstantiationError("Skipped because of invalid gpu kernel")
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 512, 1, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9075889
+No: 19 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -2250,21 +2191,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2282,11 +2223,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2306,21 +2247,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2338,11 +2279,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2352,8 +2293,8 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 4, 8]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 2, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4987332
-No: 19 GFLOPS: 0.00/76.71 result: Traceback (most recent call last):
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 4]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6140977
+No: 20 GFLOPS: 0.00/70.65 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 592, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 544, in _build_func_common
@@ -2373,21 +2314,21 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2405,11 +2346,11 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2429,21 +2370,21 @@ Traceback (most recent call last):
22: Call
at ../include/tvm/runtime/packed_func.h:1213
21: operator()
- at ../include/tvm/runtime/packed_func.h:1731
+ at ../include/tvm/runtime/packed_func.h:1730
20: unpack_call<tvm::IRModule, 5, tvm::<lambda(tvm::te::Schedule, const tvm::runtime::Array<tvm::runtime::ObjectRef>&, const tvm::runtime::String&, const tvm::runtime::Map<tvm::te::Tensor, tvm::tir::Buffer>&, bool)> >
- at ../include/tvm/runtime/packed_func.h:1671
+ at ../include/tvm/runtime/packed_func.h:1670
19: run<>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
18: run<tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
17: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
16: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
15: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1631
+ at ../include/tvm/runtime/packed_func.h:1630
14: run<tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_, tvm::runtime::TVMMovableArgValueWithContext_>
- at ../include/tvm/runtime/packed_func.h:1646
+ at ../include/tvm/runtime/packed_func.h:1645
13: operator()
at ../src/driver/driver_api.cc:388
12: tvm::LowerSchedule(tvm::te::Schedule, tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer, std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>, std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&, tvm::GlobalVarSupply, bool)
@@ -2461,11 +2402,11 @@ Traceback (most recent call last):
6: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
at ../src/tir/ir/transform.cc:100
5: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext)>::operator()(tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext) const
- at ../include/tvm/runtime/packed_func.h:1750
+ at ../include/tvm/runtime/packed_func.h:1749
4: tvm::tir::PrimFunc tvm::runtime::detail::typed_packed_call_dispatcher<tvm::tir::PrimFunc>::run<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::runtime::PackedFunc const&, tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&)
- at ../include/tvm/runtime/packed_func.h:1694
+ at ../include/tvm/runtime/packed_func.h:1693
3: tvm::runtime::TVMRetValue tvm::runtime::PackedFunc::operator()<tvm::tir::PrimFunc, tvm::IRModule, tvm::transform::PassContext>(tvm::tir::PrimFunc&&, tvm::IRModule&&, tvm::transform::PassContext&&) const
- at ../include/tvm/runtime/packed_func.h:1618
+ at ../include/tvm/runtime/packed_func.h:1617
2: tvm::runtime::PackedFuncObj::CallPacked(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
at ../include/tvm/runtime/packed_func.h:1217
1: Call
@@ -2475,8 +2416,7 @@ Traceback (most recent call last):
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 875, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
-tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 16, 1, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9757168
-No: 20 GFLOPS: 274.32/274.32 result: MeasureResult(costs=(0.0008439045105263158,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.268427848815918, timestamp=1670035938.1445587) [('tile_f', [-1, 4, 2, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,207252
+tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 1, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,3302843
</pre></div>
</div>
<p>Finally we can inspect the best config from log file, check correctness,
@@ -2515,9 +2455,9 @@ and measure running time.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Finish loading 20 records
Best config:
-[('tile_f', [-1, 4, 2, 1]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 8, 1]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,207252
+[('tile_f', [-1, 2, 16, 2]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 8]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,8817466
Finish loading 20 records
-Time cost of this operator: 0.001213
+Time cost of this operator: 0.003642
</pre></div>
</div>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autotvm-tune-conv2d-cuda-py">
diff --git a/docs/how_to/work_with_microtvm/micro_autotune.html b/docs/how_to/work_with_microtvm/micro_autotune.html
index c4eabb1f2e..105cc16332 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -598,10 +598,10 @@ the tuned operator.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 367.1 98.918 (1, 2, 10, 10, 3) 2 1 [367.1]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.039 0.819 (1, 6, 10, 10) 1 1 [3.039]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.263 (1, 1, 10, 10, 3) 1 1 [0.976]
-Total_time - 371.115 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 314.5 98.725 (1, 2, 10, 10, 3) 2 1 [314.5]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.085 0.968 (1, 6, 10, 10) 1 1 [3.085]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.306 (1, 1, 10, 10, 3) 1 1 [0.976]
+Total_time - 318.561 - - - - -
</pre></div>
</div>
</div>
@@ -653,10 +653,10 @@ Total_time -
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 103.7 97.508 (1, 6, 10, 10, 1) 2 1 [103.7]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.8 1.692 (1, 6, 10, 10) 1 1 [1.8]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.851 0.8 (1, 3, 10, 10, 1) 1 1 [0.851]
-Total_time - 106.35 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 110.0 97.669 (1, 6, 10, 10, 1) 2 1 [110.0]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.78 1.58 (1, 6, 10, 10) 1 1 [1.78]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.846 0.751 (1, 3, 10, 10, 1) 1 1 [0.846]
+Total_time - 112.626 - - - - -
</pre></div>
</div>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-autotune-py">
diff --git a/docs/how_to/work_with_microtvm/micro_pytorch.html b/docs/how_to/work_with_microtvm/micro_pytorch.html
index e9deac83ed..05485743db 100644
--- a/docs/how_to/work_with_microtvm/micro_pytorch.html
+++ b/docs/how_to/work_with_microtvm/micro_pytorch.html
@@ -440,8 +440,7 @@ download a cat image and preprocess it to use as the model input.</p>
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
0%| | 0.00/3.42M [00:00<?, ?B/s]
- 61%|###### | 2.09M/3.42M [00:00<00:00, 16.7MB/s]
-100%|##########| 3.42M/3.42M [00:00<00:00, 25.5MB/s]
+100%|##########| 3.42M/3.42M [00:00<00:00, 225MB/s]
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
return LooseVersion(torch_ver) > ver
/venv/apache-tvm-py3.7/lib/python3.7/site-packages/setuptools/_distutils/version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -565,7 +564,7 @@ via the host <cite>main.cc`</cite> or if a Zephyr emulated board is selected as
Torch top-1 id: 282, class name: tiger cat
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 2.283 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 3.380 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-pytorch-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/12b9ecc04c41abaa12022061771821d1/micro_pytorch.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">micro_pytorch.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/micro_train.html b/docs/how_to/work_with_microtvm/micro_train.html
index b84100a6a9..35cba781ad 100644
--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -530,7 +530,7 @@ take about <strong>2 minutes</strong> to download the Stanford Cars, while COCO
<a href="https://docs.python.org/3/library/shutil.html#shutil.move" title="shutil.move" class="sphx-glr-backref-module-shutil sphx-glr-backref-type-py-function"><span class="n">shutil</span><span class="o">.</span><span class="n">move</span></a><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-typ [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>'/tmp/tmp5aob5h71/images/random'
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>'/tmp/tmpiijl6bff/images/random'
</pre></div>
</div>
</div>
@@ -590,8 +590,8 @@ objects to other stuff? We can display some examples from our datasets using <co
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">)</span>
</pre></div>
</div>
-<img src="../../_images/sphx_glr_micro_train_001.png" srcset="../../_images/sphx_glr_micro_train_001.png" alt="[0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmp5aob5h71/images/target contains 8144 images
-/tmp/tmp5aob5h71/images/random contains 5000 images
+<img src="../../_images/sphx_glr_micro_train_001.png" srcset="../../_images/sphx_glr_micro_train_001.png" alt="[0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmpiijl6bff/images/target contains 8144 images
+/tmp/tmpiijl6bff/images/random contains 5000 images
</pre></div>
</div>
</div>
@@ -703,13 +703,13 @@ the time on our validation set).</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Epoch 1/3
-328/328 - 47s - loss: 0.2129 - accuracy: 0.9253 - val_loss: 0.1029 - val_accuracy: 0.9637 - 47s/epoch - 144ms/step
+328/328 - 47s - loss: 0.2187 - accuracy: 0.9265 - val_loss: 0.1272 - val_accuracy: 0.9573 - 47s/epoch - 144ms/step
Epoch 2/3
-328/328 - 44s - loss: 0.1026 - accuracy: 0.9628 - val_loss: 0.0844 - val_accuracy: 0.9649 - 44s/epoch - 134ms/step
+328/328 - 43s - loss: 0.0993 - accuracy: 0.9654 - val_loss: 0.1068 - val_accuracy: 0.9634 - 43s/epoch - 133ms/step
Epoch 3/3
-328/328 - 44s - loss: 0.0672 - accuracy: 0.9750 - val_loss: 0.0824 - val_accuracy: 0.9687 - 44s/epoch - 133ms/step
+328/328 - 43s - loss: 0.0688 - accuracy: 0.9741 - val_loss: 0.1070 - val_accuracy: 0.9660 - 43s/epoch - 132ms/step
-<keras.callbacks.History object at 0x7fc539eb1f90>
+<keras.callbacks.History object at 0x7ff6d148bc10>
</pre></div>
</div>
</div>
@@ -971,7 +971,7 @@ as intended.</p>
<p>From here, we could modify the model to read live images from the camera - we have another
Arduino tutorial for how to do that <a class="reference external" href="https://github.com/guberti/tvm-arduino-demos/tree/master/examples/person_detection">on GitHub</a>. Alternatively, we could also
<a class="reference external" href="https://tvm.apache.org/docs/how_to/work_with_microtvm/micro_autotune.html">use TVM’s autotuning capabilities</a> to dramatically improve the model’s performance.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 4 minutes 40.333 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 4 minutes 24.505 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-train-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/b52cec46baf4f78d6bcd94cbe269c8a6/micro_train.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">micro_train.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/sg_execution_times.html b/docs/how_to/work_with_microtvm/sg_execution_times.html
index d177528294..0ea40730f7 100644
--- a/docs/how_to/work_with_microtvm/sg_execution_times.html
+++ b/docs/how_to/work_with_microtvm/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-microtvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>06:42.865</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
+<p><strong>06:29.085</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -349,23 +349,23 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="micro_train.html#sphx-glr-how-to-work-with-microtvm-micro-train-py"><span class="std std-ref">Training Vision Models for microTVM on Arduino</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_train.py</span></code>)</p></td>
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+<td><p>04:24.505</p></td>
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</tr>
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</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="micro_autotune.html#sphx-glr-how-to-work-with-microtvm-micro-autotune-py"><span class="std std-ref">Autotuning with microTVM</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_autotune.py</span></code>)</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="micro_aot.html#sphx-glr-how-to-work-with-microtvm-micro-aot-py"><span class="std std-ref">microTVM Host-Driven AoT</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_aot.py</span></code>)</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="micro_tflite.html#sphx-glr-how-to-work-with-microtvm-micro-tflite-py"><span class="std std-ref">microTVM with TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_tflite.py</span></code>)</p></td>
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+<td><p>00:03.809</p></td>
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</tr>
<tr class="row-even"><td><p><a class="reference internal" href="micro_reference_vm.html#sphx-glr-how-to-work-with-microtvm-micro-reference-vm-py"><span class="std std-ref">microTVM Reference Virtual Machines</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_reference_vm.py</span></code>)</p></td>
diff --git a/docs/how_to/work_with_relay/sg_execution_times.html b/docs/how_to/work_with_relay/sg_execution_times.html
index d6ff12f2fd..19a3be183a 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-relay-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:43.496</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:43.782</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -349,15 +349,15 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="using_pipeline_executor.html#sphx-glr-how-to-work-with-relay-using-pipeline-executor-py"><span class="std std-ref">Using Pipeline Executor in Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_pipeline_executor.py</span></code>)</p></td>
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<td><p>0.0 MB</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="using_external_lib.html#sphx-glr-how-to-work-with-relay-using-external-lib-py"><span class="std std-ref">Using External Libraries in Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_external_lib.py</span></code>)</p></td>
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<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="build_gcn.html#sphx-glr-how-to-work-with-relay-build-gcn-py"><span class="std std-ref">Building a Graph Convolutional Network</span></a> (<code class="docutils literal notranslate"><span class="pre">build_gcn.py</span></code>)</p></td>
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+<td><p>00:01.494</p></td>
<td><p>0.0 MB</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="using_relay_viz.html#sphx-glr-how-to-work-with-relay-using-relay-viz-py"><span class="std std-ref">Use Relay Visualizer to Visualize Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_relay_viz.py</span></code>)</p></td>
diff --git a/docs/how_to/work_with_schedules/intrin_math.html b/docs/how_to/work_with_schedules/intrin_math.html
index 8e3087b10c..cc35047bd2 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -535,7 +535,7 @@ The following example customizes CUDA lowering rule for <code class="code docuti
<a href="../../reference/api/python/ir.html#tvm.ir.register_intrin_lowering" title="tvm.ir.register_intrin_lowering" class="sphx-glr-backref-module-tvm-ir sphx-glr-backref-type-py-function"><span class="n">register_intrin_lowering</span></a><span class="p">(</span><span class="s2">"tir.exp"</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s2">"cuda"</span><span class="p">,</span> <span class="n">f</span><span class="o">= [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7fc53a9b1290>
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7ff6d20205f0>
</pre></div>
</div>
<p>Register the rule to TVM with override option to override existing rule.
diff --git a/docs/how_to/work_with_schedules/sg_execution_times.html b/docs/how_to/work_with_schedules/sg_execution_times.html
index ac02ea5e50..e13bd27931 100644
--- a/docs/how_to/work_with_schedules/sg_execution_times.html
+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -340,7 +340,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:08.118</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
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<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -349,23 +349,23 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="intrin_math.html#sphx-glr-how-to-work-with-schedules-intrin-math-py"><span class="std std-ref">Intrinsics and Math Functions</span></a> (<code class="docutils literal notranslate"><span class="pre">intrin_math.py</span></code>)</p></td>
-<td><p>00:05.696</p></td>
+<td><p>00:02.418</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensorize.html#sphx-glr-how-to-work-with-schedules-tensorize-py"><span class="std std-ref">Use Tensorize to Leverage Hardware Intrinsics</span></a> (<code class="docutils literal notranslate"><span class="pre">tensorize.py</span></code>)</p></td>
-<td><p>00:01.095</p></td>
+<td><p>00:01.157</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
-<td><p>00:00.565</p></td>
+<td><p>00:00.574</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="scan.html#sphx-glr-how-to-work-with-schedules-scan-py"><span class="std std-ref">Scan and Recurrent Kernel</span></a> (<code class="docutils literal notranslate"><span class="pre">scan.py</span></code>)</p></td>
-<td><p>00:00.547</p></td>
+<td><p>00:00.566</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="extern_op.html#sphx-glr-how-to-work-with-schedules-extern-op-py"><span class="std std-ref">External Tensor Functions</span></a> (<code class="docutils literal notranslate"><span class="pre">extern_op.py</span></code>)</p></td>
-<td><p>00:00.113</p></td>
+<td><p>00:00.115</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="schedule_primitives.html#sphx-glr-how-to-work-with-schedules-schedule-primitives-py"><span class="std std-ref">Schedule Primitives in TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">schedule_primitives.py</span></code>)</p></td>
@@ -373,11 +373,11 @@
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tedd.html#sphx-glr-how-to-work-with-schedules-tedd-py"><span class="std std-ref">Use Tensor Expression Debug Display (TEDD) for Visualization</span></a> (<code class="docutils literal notranslate"><span class="pre">tedd.py</span></code>)</p></td>
-<td><p>00:00.028</p></td>
+<td><p>00:00.029</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tuple_inputs.html#sphx-glr-how-to-work-with-schedules-tuple-inputs-py"><span class="std std-ref">Compute and Reduce with Tuple Inputs</span></a> (<code class="docutils literal notranslate"><span class="pre">tuple_inputs.py</span></code>)</p></td>
-<td><p>00:00.023</p></td>
+<td><p>00:00.024</p></td>
<td><p>0.0 MB</p></td>
</tr>
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diff --git a/docs/how_to/work_with_schedules/tensorize.html b/docs/how_to/work_with_schedules/tensorize.html
index 3c44e4c03a..c562b8e56c 100644
--- a/docs/how_to/work_with_schedules/tensorize.html
+++ b/docs/how_to/work_with_schedules/tensorize.html
@@ -586,7 +586,7 @@ The importing needs to happen before the tensorized GEMV being executed.</p>
B: Buffer(B_2: Pointer(float32), float32, [512, 64], []),
C: Buffer(C_2: Pointer(float32), float32, [1024, 512], [])}
buffer_map = {A_1: A, B_1: B, C_1: C} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpg6udtyna/input0.cc'\nsource_filename = \"/tmp/tmpg6udtyna/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = allo [...]
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpdqg1gu7i/input0.cc'\nsource_filename = \"/tmp/tmpdqg1gu7i/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = allo [...]
for (i, 0, 1024) {
for (j.outer: int32, 0, 32) {
@tir.call_extern("gemv_update", @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), C_2, ((i*512) + (j.outer*16)), 16, 2, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), A_2, (i*64), 64, 1, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), B_2, (j.outer*1024), 1024, 1, dtype=handle), 16, 64, 64, dtype=int32)
diff --git a/docs/reference/api/doxygen/data__type_8h_source.html b/docs/reference/api/doxygen/data__type_8h_source.html
index 9c6b5bd6e6..bd9a91b7bf 100644
--- a/docs/reference/api/doxygen/data__type_8h_source.html
+++ b/docs/reference/api/doxygen/data__type_8h_source.html
@@ -66,13 +66,13 @@ $(function() {
<div class="title">data_type.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="data__type_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more [...]
+<a href="data__type_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more [...]
<div class="ttc" id="namespacetvm_1_1runtime_html_af22b89284299c81d0c1802199af446d7"><div class="ttname"><a href="namespacetvm_1_1runtime.html#af22b89284299c81d0c1802199af446d7">tvm::runtime::operator<<</a></div><div class="ttdeci">std::ostream & operator<<(std::ostream &os, const ObjectRef &n)</div><div class="ttdef"><b>Definition:</b> repr_printer.h:69</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a1b8eedadc5a269b2f9614ce69a9932e7"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a1b8eedadc5a269b2f9614ce69a9932e7">tvm::runtime::GetCustomTypeRegistered</a></div><div class="ttdeci">bool GetCustomTypeRegistered(uint8_t type_code)</div><div class="ttdoc">Runtime utility for checking whether custom type is registered. </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a4f3c849cf79c0812a50fdbb9ad175648"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a4f3c849cf79c0812a50fdbb9ad175648">tvm::runtime::DataType::is_int</a></div><div class="ttdeci">bool is_int() const</div><div class="ttdef"><b>Definition:</b> data_type.h:99</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_aee574cee6755b0c2f1aa664c6967686f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#aee574cee6755b0c2f1aa664c6967686f">tvm::runtime::TypeEqual</a></div><div class="ttdeci">bool TypeEqual(DLDataType lhs, DLDataType rhs)</div><div class="ttdoc">Check whether two types are equal . </div><div class="ttdef"><b>Definition:</b> data_type.h:251</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a3c9ce1627be2550f656cd37b6c698c7da92916e0b7138b26e222f4b85618bd5b4"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a3c9ce1627be2550f656cd37b6c698c7da92916e0b7138b26e222f4b85618bd5b4">tvm::runtime::DataType::kCustomBegin</a></div><div class="ttdef"><b>Definition:</b> data_type.h:57</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_ac360f2d9815036ab1b4d84d9cfb46b4f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ac360f2d9815036ab1b4d84d9cfb46b4f">tvm::runtime::DLDataType2String</a></div><div class="ttdeci">std::string DLDataType2String(DLDataType t)</div><div class="ttdoc">convert a TVM type to string. </div><div class="ttdef"><b>Definition:</b> data_type.h:342</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_ac360f2d9815036ab1b4d84d9cfb46b4f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ac360f2d9815036ab1b4d84d9cfb46b4f">tvm::runtime::DLDataType2String</a></div><div class="ttdeci">std::string DLDataType2String(DLDataType t)</div><div class="ttdoc">convert a TVM type to string. </div><div class="ttdef"><b>Definition:</b> data_type.h:341</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_ad01a53416152b68029d67190c3709d25"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ad01a53416152b68029d67190c3709d25">tvm::runtime::GetVectorBytes</a></div><div class="ttdeci">int GetVectorBytes(DataType dtype)</div><div class="ttdoc">Get the number of bytes needed in a vector. </div><div class="ttdef"><b>Definition:</b> data_type.h:225</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_ac6d167947285dff3c780bd5d01ace9b9"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ac6d167947285dff3c780bd5d01ace9b9">tvm::runtime::ParseCustomDatatype</a></div><div class="ttdeci">uint8_t ParseCustomDatatype(const std::string &s, const char **scan)</div><div class="ttdoc">Runtime utility for parsing string of the form "custom[<typename>]". </div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a06a49d761ea6373557c24c01eaceb07d"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a06a49d761ea6373557c24c01eaceb07d">tvm::runtime::GetCustomTypeName</a></div><div class="ttdeci">std::string GetCustomTypeName(uint8_t type_code)</div><div class="ttdoc">Runtime utility for getting custom type name from code. </div></div>
@@ -91,7 +91,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a3c195fd818d2eb645f9aa0ab826ba09c"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a3c195fd818d2eb645f9aa0ab826ba09c">tvm::runtime::DataType::bytes</a></div><div class="ttdeci">int bytes() const</div><div class="ttdef"><b>Definition:</b> data_type.h:85</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a83095169a6537b1ccd3098e3aab86530"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a83095169a6537b1ccd3098e3aab86530">tvm::runtime::DataType::is_float16</a></div><div class="ttdeci">bool is_float16() const</div><div class="ttdef"><b>Definition:</b> data_type.h:95</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_af9303c49b737675bdab034c4032dcc48"><div class="ttname"><a href="namespacetvm_1_1runtime.html#af9303c49b737675bdab034c4032dcc48">tvm::runtime::DLDataTypeCode2Str</a></div><div class="ttdeci">const char * DLDataTypeCode2Str(DLDataTypeCode type_code)</div><div class="ttdoc">Convert type code to its name. </div><div class="ttdef"><b>Definition:</b> data_type.h:299</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_a277f104e659f71cd8885744700016341"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a277f104e659f71cd8885744700016341">tvm::runtime::String2DLDataType</a></div><div class="ttdeci">DLDataType String2DLDataType(std::string s)</div><div class="ttdoc">convert a string to TVM type. </div><div class="ttdef"><b>Definition:</b> data_type.h:349</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_a277f104e659f71cd8885744700016341"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a277f104e659f71cd8885744700016341">tvm::runtime::String2DLDataType</a></div><div class="ttdeci">DLDataType String2DLDataType(std::string s)</div><div class="ttdoc">convert a string to TVM type. </div><div class="ttdef"><b>Definition:</b> data_type.h:348</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html">tvm::runtime::DataType</a></div><div class="ttdoc">Runtime primitive data type. </div><div class="ttdef"><b>Definition:</b> data_type.h:41</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_acb927f3f6ae5116e8f439159fafbc04e"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#acb927f3f6ae5116e8f439159fafbc04e">tvm::runtime::DataType::bits</a></div><div class="ttdeci">int bits() const</div><div class="ttdef"><b>Definition:</b> data_type.h:83</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a237a714a6a16e14aa01fa4ac52426551"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a237a714a6a16e14aa01fa4ac52426551">tvm::runtime::DataType::Float</a></div><div class="ttdeci">static DataType Float(int bits, int lanes=1)</div><div class="ttdoc">Construct an float type. </div><div class="ttdef"><b>Definition:</b> data_type.h:178</div></div>
@@ -118,7 +118,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ae6d224687a4a655ae387d55f72430c8f"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ae6d224687a4a655ae387d55f72430c8f">tvm::runtime::DataType::is_vector_bool</a></div><div class="ttdeci">bool is_vector_bool() const</div><div class="ttdef"><b>Definition:</b> data_type.h:107</div></div>
<div class="ttc" id="c__runtime__api_8h_html"><div class="ttname"><a href="c__runtime__api_8h.html">c_runtime_api.h</a></div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a3c9ce1627be2550f656cd37b6c698c7da6622631a910a54272097f7f4b6373e9d"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a3c9ce1627be2550f656cd37b6c698c7da6622631a910a54272097f7f4b6373e9d">tvm::runtime::DataType::kFloat</a></div><div class="ttdef"><b>Definition:</b> data_type.h:54</div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ad1cf4571ee1a22c188c66ee2e6e6c042"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ad1cf4571ee1a22c188c66ee2e6e6c042">tvm::runtime::DataType::UInt</a></div><div class="ttdeci">static DataType UInt(int bits, int lanes=1)</div><div class="ttdoc">Construct an uint type. </div><div class="ttdef"><b>Definition:</b> data_type.h:171</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ab45f13dd70d982d9f977c79b6f7fac98"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ab45f13dd70d982d9f977c79b6f7fac98">tvm::runtime::DataType::Int</a></div><div class="ttdeci">static DataType Int(int bits, int lanes=1)</div><div class="ttdoc">Construct an int type. </div><div class="ttdef"><b>Definition:</b> data_type.h:164</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_aa27f63a2395ce1ac52e4d7740a31383b"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#aa27f63a2395ce1ac52e4d7740a31383b">tvm::runtime::DataType::DataType</a></div><div class="ttdeci">DataType(DLDataType dtype)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> data_type.h:65</div></div>
diff --git a/docs/reference/api/doxygen/data__type__rewriter_8h_source.html b/docs/reference/api/doxygen/data__type__rewriter_8h_source.html
index 6e1bb9add7..6c9c9e0fb8 100644
--- a/docs/reference/api/doxygen/data__type__rewriter_8h_source.html
+++ b/docs/reference/api/doxygen/data__type__rewriter_8h_source.html
@@ -95,7 +95,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1MaxNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1MaxNode.html">tvm::tir::MaxNode</a></div><div class="ttdoc">max(a, b) </div><div class="ttdef"><b>Definition:</b> expr.h:299</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1IndexDataTypeRewriter_html_a34ba7e2f7b8a676f84a8fcb37d3c5dba"><div class="ttname"><a href="classtvm_1_1tir_1_1IndexDataTypeRewriter.html#a34ba7e2f7b8a676f84a8fcb37d3c5dba">tvm::tir::IndexDataTypeRewriter::var_remap_</a></div><div class="ttdeci">Map< Var, Var > var_remap_</div><div class="ttdef"><b>Definition:</b> data_type_rewriter.h:126</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Buffer_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Buffer.html">tvm::tir::Buffer</a></div><div class="ttdoc">Buffer is a symbolic n-darray structure. It is a composition of primitive symbolic types...</div><div class="ttdef"><b>Definition:</b> buffer.h:160</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html">tvm::tir::StmtExprMutator</a></div><div class="ttdoc">Mutator that recursively mutates stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:315</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html">tvm::tir::StmtExprMutator</a></div><div class="ttdoc">Mutator that recursively mutates stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:314</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1BufferStoreNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1BufferStoreNode.html">tvm::tir::BufferStoreNode</a></div><div class="ttdoc">Store value to the high dimension buffer. </div><div class="ttdef"><b>Definition:</b> stmt.h:290</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1RampNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1RampNode.html">tvm::tir::RampNode</a></div><div class="ttdoc">Construct a vector with lanes elements where its i-th element equals base + i * stride. This is useful to construct a index for a continuous vector load. </div><div class="ttdef"><b>Definition:</b> expr.h:802</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1MinNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1MinNode.html">tvm::tir::MinNode</a></div><div class="ttdoc">min(a, b) </div><div class="ttdef"><b>Definition:</b> expr.h:282</div></div>
diff --git a/docs/reference/api/doxygen/detail_2broadcast_8h_source.html b/docs/reference/api/doxygen/detail_2broadcast_8h_source.html
index 6629fd6791..aceb54caca 100644
--- a/docs/reference/api/doxygen/detail_2broadcast_8h_source.html
+++ b/docs/reference/api/doxygen/detail_2broadcast_8h_source.html
@@ -76,7 +76,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Array_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Array.html">tvm::runtime::Array</a></div><div class="ttdoc">Array, container representing a contiguous sequence of ObjectRefs. </div><div class="ttdef"><b>Definition:</b> array.h:289</div></div>
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_ae8c7db788e840dc1c2ed1f365d5ea829"><div class="ttname"><a href="namespacetvm_1_1tir.html#ae8c7db788e840dc1c2ed1f365d5ea829">tvm::tir::IntImmNode</a></div><div class="ttdeci">tvm::IntImmNode IntImmNode</div><div class="ttdef"><b>Definition:</b> expr.h:49</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:951</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:950</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_af30c02f3a3f37c7963b3af60fb9c72a1"><div class="ttname"><a href="namespacetvm_1_1topi.html#af30c02f3a3f37c7963b3af60fb9c72a1">tvm::topi::shape</a></div><div class="ttdeci">Tensor shape(const Tensor &src, DataType dtype, const std::string name="T_shape", const std::string tag=kInjective)</div><div class="ttdoc">Get the shape of input tensor. </div><div class="ttdef"><b>Definition:</b> transform.h:1758</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Array_html_a6b097149e69ea03fe3b812a3f5f7fcd9"><div class="ttname"><a href="classtvm_1_1runtime_1_1Array.html#a6b097149e69ea03fe3b812a3f5f7fcd9">tvm::runtime::Array::end</a></div><div class="ttdeci">iterator end() const</div><div class="ttdef"><b>Definition:</b> array.h:390</div></div>
<div class="ttc" id="classtvm_1_1te_1_1Tensor_html"><div class="ttname"><a href="classtvm_1_1te_1_1Tensor.html">tvm::te::Tensor</a></div><div class="ttdoc">Tensor structure representing a possible input, or intermediate computation result. </div><div class="ttdef"><b>Definition:</b> tensor.h:102</div></div>
@@ -86,7 +86,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1topi_html_a7da4c96db87c1459a2b097b87afd811f"><div class="ttname"><a href="namespacetvm_1_1topi.html#a7da4c96db87c1459a2b097b87afd811f">tvm::topi::cast</a></div><div class="ttdeci">Tensor cast(const Tensor &x, DataType type, std::string name="T_cast", std::string tag=kElementWise)</div><div class="ttdoc">Cast each element of x to the given type. If expr is scalar and type is a corresponding vector type...</div><div class="ttdef"><b>Defini [...]
<div class="ttc" id="classtvm_1_1PrimExpr_html"><div class="ttname"><a href="classtvm_1_1PrimExpr.html">tvm::PrimExpr</a></div><div class="ttdoc">Reference to PrimExprNode. </div><div class="ttdef"><b>Definition:</b> expr.h:112</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_a2d76fa1fb628ff276a284e61123589c5"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#a2d76fa1fb628ff276a284e61123589c5">tvm::runtime::ObjectRef::as</a></div><div class="ttdeci">const ObjectType * as() const</div><div class="ttdoc">Try to downcast the internal Object to a raw pointer of a corresponding type. </div><div class="ttdef"><b>Definition:</b> object.h:865</div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
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diff --git a/docs/reference/api/doxygen/detail_2extern_8h_source.html b/docs/reference/api/doxygen/detail_2extern_8h_source.html
index e2c5da58a4..69b2775a4d 100644
--- a/docs/reference/api/doxygen/detail_2extern_8h_source.html
+++ b/docs/reference/api/doxygen/detail_2extern_8h_source.html
@@ -66,7 +66,7 @@ $(function() {
<div class="title">extern.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="detail_2extern_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or m [...]
+<a href="detail_2extern_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or m [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Call_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Call.html">tvm::tir::Call</a></div><div class="ttdoc">Managed reference to CallNode. </div><div class="ttdef"><b>Definition:</b> expr.h:973</div></div>
@@ -81,7 +81,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Map_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Map.html">tvm::runtime::Map</a></div><div class="ttdoc">Map container of NodeRef->NodeRef in DSL graph. Map implements copy on write semantics, which means map is mutable but copy will happen when array is referenced in more than two places. </div><div class="ttdef"><b>Definition:</b> map.h:1271</div></div>
<div class="ttc" id="builtin_8h_html"><div class="ttname"><a href="builtin_8h.html">builtin.h</a></div><div class="ttdoc">TIR builtin intrinsics. </div></div>
<div class="ttc" id="namespacetvm_1_1script_1_1ir__builder_1_1tir_html_a101850df27120c29355e6215b9b2b525"><div class="ttname"><a href="namespacetvm_1_1script_1_1ir__builder_1_1tir.html#a101850df27120c29355e6215b9b2b525">tvm::script::ir_builder::tir::Evaluate</a></div><div class="ttdeci">void Evaluate(PrimExpr value)</div><div class="ttdoc">Evaluate the input expression. </div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ab45f13dd70d982d9f977c79b6f7fac98"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ab45f13dd70d982d9f977c79b6f7fac98">tvm::runtime::DataType::Int</a></div><div class="ttdeci">static DataType Int(int bits, int lanes=1)</div><div class="ttdoc">Construct an int type. </div><div class="ttdef"><b>Definition:</b> data_type.h:164</div></div>
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diff --git a/docs/reference/api/doxygen/device__api_8h_source.html b/docs/reference/api/doxygen/device__api_8h_source.html
index 682e2e3cd2..4b219f60c5 100644
--- a/docs/reference/api/doxygen/device__api_8h_source.html
+++ b/docs/reference/api/doxygen/device__api_8h_source.html
@@ -66,7 +66,7 @@ $(function() {
<div class="title">device_api.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="device__api_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more [...]
+<a href="device__api_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more [...]
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html">tvm::runtime::TVMRetValue</a></div><div class="ttdoc">Return Value container, Unlike TVMArgValue, which only holds reference and do not delete the underlyi...</div><div class="ttdef"><b>Definition:</b> packed_func.h:799</div></div>
<div class="ttc" id="namespacetvm_1_1tir_1_1attr_html_a7e4e7cd47471a9089022214d63d24206"><div class="ttname"><a href="namespacetvm_1_1tir_1_1attr.html#a7e4e7cd47471a9089022214d63d24206">tvm::tir::attr::device_type</a></div><div class="ttdeci">constexpr const char * device_type</div><div class="ttdoc">The device type. </div><div class="ttdef"><b>Definition:</b> stmt.h:1405</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a57cbccb14c35a0e62dbc1b911188fcefa474961a2b52fee7b33e529015162e884"><div class="ttname"><a href="c__runtime__api_8h.html#a57cbccb14c35a0e62dbc1b911188fcefa474961a2b52fee7b33e529015162e884">TVMDeviceExtType_End</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:118</div></div>
@@ -77,16 +77,16 @@ $(function() {
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DeviceAPI_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1DeviceAPI.html">tvm::runtime::DeviceAPI</a></div><div class="ttdoc">TVM Runtime Device API, abstracts the device specific interface for memory management. </div><div class="ttdef"><b>Definition:</b> device_api.h:79</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a57cbccb14c35a0e62dbc1b911188fcefad77aa5af5411ed9f3719f48af1f04b02"><div class="ttname"><a href="c__runtime__api_8h.html#a57cbccb14c35a0e62dbc1b911188fcefad77aa5af5411ed9f3719f48af1f04b02">kDLAOCL</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:114</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_aa93f6c733bf54ca19d642a5ae2ec94be"><div class="ttname"><a href="namespacetvm_1_1runtime.html#aa93f6c733bf54ca19d642a5ae2ec94be">tvm::runtime::AddRPCSessionMask</a></div><div class="ttdeci">Device AddRPCSessionMask(Device dev, int session_table_index)</div><div class="ttdoc">Add a RPC session mask to a Device. RPC clients typically do this when decoding a Device received fro...</div><div class="ttdef"><b>Definition:</b> device_api.h:338</d [...]
-<div class="ttc" id="namespacetvm_1_1runtime_html_a8d284249899038cca33c40d97eefa1e3"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a8d284249899038cca33c40d97eefa1e3">tvm::runtime::GetRPCSessionIndex</a></div><div class="ttdeci">int GetRPCSessionIndex(Device dev)</div><div class="ttdoc">Return the RPCSessTable index of the RPC Session that owns this device. </div><div class="ttdef"><b>Definition:</b> device_api.h:305</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_aa93f6c733bf54ca19d642a5ae2ec94be"><div class="ttname"><a href="namespacetvm_1_1runtime.html#aa93f6c733bf54ca19d642a5ae2ec94be">tvm::runtime::AddRPCSessionMask</a></div><div class="ttdeci">Device AddRPCSessionMask(Device dev, int session_table_index)</div><div class="ttdoc">Add a RPC session mask to a Device. RPC clients typically do this when decoding a Device received fro...</div><div class="ttdef"><b>Definition:</b> device_api.h:337</d [...]
+<div class="ttc" id="namespacetvm_1_1runtime_html_a8d284249899038cca33c40d97eefa1e3"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a8d284249899038cca33c40d97eefa1e3">tvm::runtime::GetRPCSessionIndex</a></div><div class="ttdeci">int GetRPCSessionIndex(Device dev)</div><div class="ttdoc">Return the RPCSessTable index of the RPC Session that owns this device. </div><div class="ttdef"><b>Definition:</b> device_api.h:304</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DeviceAPI_html_a8967810939aa24e17c37599c5014e50f"><div class="ttname"><a href="classtvm_1_1runtime_1_1DeviceAPI.html#a8967810939aa24e17c37599c5014e50f">tvm::runtime::DeviceAPI::GetTargetProperty</a></div><div class="ttdeci">virtual void GetTargetProperty(Device dev, const std::string &property, TVMRetValue *rv)</div><div class="ttdoc">Query the device for specified properties. </div><div class="ttdef"><b>Definition:</b> device_api.h:103</di [...]
<div class="ttc" id="c__runtime__api_8h_html_ab1d5f6b7945e1410602a8a057fda5757"><div class="ttname"><a href="c__runtime__api_8h.html#ab1d5f6b7945e1410602a8a057fda5757">TVMStreamHandle</a></div><div class="ttdeci">void * TVMStreamHandle</div><div class="ttdoc">The stream that is specific to device can be NULL, which indicates the default one. </div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:229</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a48cbe06e6c95ca6fabc20dd1cbacc2c9"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a48cbe06e6c95ca6fabc20dd1cbacc2c9">tvm::runtime::kRPCSessMask</a></div><div class="ttdeci">constexpr int kRPCSessMask</div><div class="ttdoc">The device type bigger than this is RPC device. </div><div class="ttdef"><b>Definition:</b> device_api.h:244</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DeviceAPI_html_af3fe69d9823d7c67c86ecf247d894f27"><div class="ttname"><a href="classtvm_1_1runtime_1_1DeviceAPI.html#af3fe69d9823d7c67c86ecf247d894f27">tvm::runtime::DeviceAPI::~DeviceAPI</a></div><div class="ttdeci">virtual ~DeviceAPI()</div><div class="ttdoc">virtual destructor </div><div class="ttdef"><b>Definition:</b> device_api.h:82</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_aa5f13cd8047078f88d142fe53337ba6f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#aa5f13cd8047078f88d142fe53337ba6f">tvm::runtime::IsRPCSessionDevice</a></div><div class="ttdeci">bool IsRPCSessionDevice(Device dev)</div><div class="ttdoc">Return true if a Device is owned by an RPC session. </div><div class="ttdef"><b>Definition:</b> device_api.h:299</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_aa5f13cd8047078f88d142fe53337ba6f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#aa5f13cd8047078f88d142fe53337ba6f">tvm::runtime::IsRPCSessionDevice</a></div><div class="ttdeci">bool IsRPCSessionDevice(Device dev)</div><div class="ttdoc">Return true if a Device is owned by an RPC session. </div><div class="ttdef"><b>Definition:</b> device_api.h:298</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a8f5819cabea098a1818cf7cda40fdb1f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a8f5819cabea098a1818cf7cda40fdb1f">tvm::runtime::kTempAllocaAlignment</a></div><div class="ttdeci">constexpr int kTempAllocaAlignment</div><div class="ttdoc">Number of bytes each allocation must align to in temporary allocation. </div><div class="ttdef"><b>Definition:</b> device_api.h:65</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DeviceAPI_html_a04a11f5fc72ad905880f639e5a7a4bd5"><div class="ttname"><a href="classtvm_1_1runtime_1_1DeviceAPI.html#a04a11f5fc72ad905880f639e5a7a4bd5">tvm::runtime::DeviceAPI::NeedSetDevice</a></div><div class="ttdeci">static bool NeedSetDevice(int device_type)</div><div class="ttdoc">Whether a certian device type requires set device device before launching the kernel function...</div><div class="ttdef"><b>Definition:</b> device_api.h:220</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_af32398517b6b915361c5716f8e32c16f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#af32398517b6b915361c5716f8e32c16f">tvm::runtime::RemoveRPCSessionMask</a></div><div class="ttdeci">Device RemoveRPCSessionMask(Device dev)</div><div class="ttdoc">Remove the RPC session mask from a Device. RPC clients typically do this when encoding a Device for t...</div><div class="ttdef"><b>Definition:</b> device_api.h:317</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_af32398517b6b915361c5716f8e32c16f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#af32398517b6b915361c5716f8e32c16f">tvm::runtime::RemoveRPCSessionMask</a></div><div class="ttdeci">Device RemoveRPCSessionMask(Device dev)</div><div class="ttdoc">Remove the RPC session mask from a Device. RPC clients typically do this when encoding a Device for t...</div><div class="ttdef"><b>Definition:</b> device_api.h:316</div></div>
<div class="ttc" id="ndarray_8h_html"><div class="ttname"><a href="ndarray_8h.html">ndarray.h</a></div><div class="ttdoc">A device-independent managed NDArray abstraction. </div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a46fef1ca0ccc05473e9bb0a8c6b66619afae6abc73ecd8ccc7f556da2f56e40eb"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a46fef1ca0ccc05473e9bb0a8c6b66619afae6abc73ecd8ccc7f556da2f56e40eb">tvm::runtime::kExist</a></div><div class="ttdef"><b>Definition:</b> device_api.h:39</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a57cbccb14c35a0e62dbc1b911188fcefa3357ff71d095bc9bdbe5116599bade5f"><div class="ttname"><a href="c__runtime__api_8h.html#a57cbccb14c35a0e62dbc1b911188fcefa3357ff71d095bc9bdbe5116599bade5f">kDLMicroDev</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:117</div></div>
diff --git a/docs/reference/api/doxygen/dilate_8h_source.html b/docs/reference/api/doxygen/dilate_8h_source.html
index 5059609b9a..e93d45588e 100644
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@@ -67,7 +67,7 @@ $(function() {
</div><!--header-->
<div class="contents">
<a href="dilate_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more cont [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="namespacetvm_html_a353217978feabae3575560bf1586885f"><div class="ttname"><a href="namespacetvm.html#a353217978feabae3575560bf1586885f">tvm::if_then_else</a></div><div class="ttdeci">PrimExpr if_then_else(PrimExpr cond, PrimExpr true_value, PrimExpr false_value, Span span=Span())</div><div class="ttdoc">Conditional expression. </div></div>
diff --git a/docs/reference/api/doxygen/elemwise_8h_source.html b/docs/reference/api/doxygen/elemwise_8h_source.html
index 54c68a9b10..476255ab7a 100644
--- a/docs/reference/api/doxygen/elemwise_8h_source.html
+++ b/docs/reference/api/doxygen/elemwise_8h_source.html
@@ -72,7 +72,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1topi_html_a7ac1dc0d99ce93090a4cdf90ab19d4b8"><div class="ttname"><a href="namespacetvm_1_1topi.html#a7ac1dc0d99ce93090a4cdf90ab19d4b8">tvm::topi::minimum</a></div><div class="ttdeci">tvm::PrimExpr minimum(const tvm::PrimExpr &a, const tvm::PrimExpr &b)</div><div class="ttdef"><b>Definition:</b> broadcast.h:354</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a91313bc00e3b96717f8420181f789300"><div class="ttname"><a href="namespacetvm_1_1topi.html#a91313bc00e3b96717f8420181f789300">tvm::topi::abs</a></div><div class="ttdeci">Tensor abs(const Tensor &x, std::string name="T_" "abs", std::string tag=kElementWise)</div><div class="ttdef"><b>Definition:</b> elemwise.h:60</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a08b96a24b96a201fb5069337e22e7336"><div class="ttname"><a href="namespacetvm_1_1topi.html#a08b96a24b96a201fb5069337e22e7336">tvm::topi::isinf</a></div><div class="ttdeci">Tensor isinf(const Tensor &x, std::string name="T_" "isinf", std::string tag=kElementWise)</div><div class="ttdef"><b>Definition:</b> elemwise.h:75</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a5c22ce14da6f5589de129861bb06da78"><div class="ttname"><a href="namespacetvm_1_1topi.html#a5c22ce14da6f5589de129861bb06da78">tvm::topi::full</a></div><div class="ttdeci">Tensor full(const Array< PrimExpr > &shape, DataType dtype, const PrimExpr fill_value, std::string name="T_full", std::string tag=kElementWise)</div><div class="ttdoc">Creates an operation that fill a tensor with fill_value. </div><div class="ttdef"><b>De [...]
<div class="ttc" id="namespacetvm_1_1topi_html_a7e7506fced8d921ca7e1a10ae27b1b5b"><div class="ttname"><a href="namespacetvm_1_1topi.html#a7e7506fced8d921ca7e1a10ae27b1b5b">tvm::topi::sqrt</a></div><div class="ttdeci">Tensor sqrt(const Tensor &x, std::string name="T_" "sqrt", std::string tag=kElementWise)</div><div class="ttdef"><b>Definition:</b> elemwise.h:52</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
diff --git a/docs/reference/api/doxygen/generic__func_8h_source.html b/docs/reference/api/doxygen/generic__func_8h_source.html
index 84a037da87..9efdc85797 100644
--- a/docs/reference/api/doxygen/generic__func_8h_source.html
+++ b/docs/reference/api/doxygen/generic__func_8h_source.html
@@ -94,7 +94,7 @@ $(function() {
<div class="ttc" id="target_8h_html"><div class="ttname"><a href="target_8h.html">target.h</a></div><div class="ttdoc">Compilation target object. </div></div>
<div class="ttc" id="namespacetvm_html_a0da40d3e210aa3b38a17982a7b7866b8"><div class="ttname"><a href="namespacetvm.html#a0da40d3e210aa3b38a17982a7b7866b8">tvm::ret</a></div><div class="ttdeci">PrimExpr ret(PrimExpr value, Span span=Span())</div><div class="ttdoc">Return the value. </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html">tvm::runtime::PackedFunc</a></div><div class="ttdoc">Packed function is a type-erased function. The arguments are passed by packed format. </div><div class="ttdef"><b>Definition:</b> packed_func.h:138</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1514</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1513</div></div>
<div class="ttc" id="classtvm_1_1GenericFunc_html_a74a6f06af50db51c3ff42fd493c44826"><div class="ttname"><a href="classtvm_1_1GenericFunc.html#a74a6f06af50db51c3ff42fd493c44826">tvm::GenericFunc::Get</a></div><div class="ttdeci">static GenericFunc Get(const std::string &name)</div><div class="ttdoc">Find or register the GenericFunc instance corresponding to the give name. </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_ae423057ecf93c18714d17f53cd1d318f"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#ae423057ecf93c18714d17f53cd1d318f">tvm::runtime::ObjectRef::get_mutable</a></div><div class="ttdeci">Object * get_mutable() const</div><div class="ttdef"><b>Definition:</b> object.h:576</div></div>
<div class="ttc" id="packed__func_8h_html"><div class="ttname"><a href="packed__func_8h.html">packed_func.h</a></div><div class="ttdoc">Type-erased function used across TVM API. </div></div>
diff --git a/docs/reference/api/doxygen/ir_2attrs_8h_source.html b/docs/reference/api/doxygen/ir_2attrs_8h_source.html
index e4e496cd41..b60fb90b16 100644
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+++ b/docs/reference/api/doxygen/ir_2attrs_8h_source.html
@@ -154,7 +154,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1detail_1_1AttrsSHashVisitor_html"><div class="ttname"><a href="classtvm_1_1detail_1_1AttrsSHashVisitor.html">tvm::detail::AttrsSHashVisitor</a></div><div class="ttdef"><b>Definition:</b> attrs.h:487</div></div>
<div class="ttc" id="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry_html_ae3ca1012c8502b2d3132cc81530c6c0e"><div class="ttname"><a href="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry.html#ae3ca1012c8502b2d3132cc81530c6c0e">tvm::detail::AttrTriggerNonDefaultEntry::~AttrTriggerNonDefaultEntry</a></div><div class="ttdeci">~AttrTriggerNonDefaultEntry() DMLC_THROW_EXCEPTION</div><div class="ttdef"><b>Definition:</b> attrs.h:792</div></div>
<div class="ttc" id="classtvm_1_1detail_1_1AttrExistVisitor_html_a42cfd0949c298dea06fb2c4fb39e188d"><div class="ttname"><a href="classtvm_1_1detail_1_1AttrExistVisitor.html#a42cfd0949c298dea06fb2c4fb39e188d">tvm::detail::AttrExistVisitor::key_</a></div><div class="ttdeci">std::string key_</div><div class="ttdef"><b>Definition:</b> attrs.h:774</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1String_html_a2ee7733b1c8092383ffab8c67bf8cb20"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html#a2ee7733b1c8092383ffab8c67bf8cb20">tvm::runtime::String::CanConvertFrom</a></div><div class="ttdeci">static bool CanConvertFrom(const TVMArgValue &val)</div><div class="ttdoc">Check if a TVMArgValue can be converted to String, i.e. it can be std::string or String. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1973</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1String_html_a2ee7733b1c8092383ffab8c67bf8cb20"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html#a2ee7733b1c8092383ffab8c67bf8cb20">tvm::runtime::String::CanConvertFrom</a></div><div class="ttdeci">static bool CanConvertFrom(const TVMArgValue &val)</div><div class="ttdoc">Check if a TVMArgValue can be converted to String, i.e. it can be std::string or String. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1972</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></div><div class="ttdoc">Base class of all object reference. </div><div class="ttdef"><b>Definition:</b> object.h:511</div></div>
<div class="ttc" id="namespacetvm_html_a28c693333c2b15702b1a9a57dec0fbf5"><div class="ttname"><a href="namespacetvm.html#a28c693333c2b15702b1a9a57dec0fbf5">tvm::NullValue< DataType ></a></div><div class="ttdeci">DataType NullValue< DataType >()</div><div class="ttdef"><b>Definition:</b> attrs.h:90</div></div>
<div class="ttc" id="object_8h_html_af8330e3864503fb7c4133ae4d48fe4a2"><div class="ttname"><a href="object_8h.html#af8330e3864503fb7c4133ae4d48fe4a2">TVM_DEFINE_OBJECT_REF_COW_METHOD</a></div><div class="ttdeci">#define TVM_DEFINE_OBJECT_REF_COW_METHOD(ObjectName)</div><div class="ttdoc">Define CopyOnWrite function in an ObjectRef. </div><div class="ttdef"><b>Definition:</b> object.h:785</div></div>
@@ -196,7 +196,7 @@ $(function() {
<div class="ttc" id="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry_html_a8cbd96cebaceae86c9c7613de9cc43dd"><div class="ttname"><a href="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry.html#a8cbd96cebaceae86c9c7613de9cc43dd">tvm::detail::AttrTriggerNonDefaultEntry::set_lower_bound</a></div><div class="ttdeci">TSelf & set_lower_bound(DMLC_ATTRIBUTE_UNUSED const T &begin)</div><div class="ttdef"><b>Definition:</b> attrs.h:804</div></div>
<div class="ttc" id="object_8h_html_ac2b7418e9549512b5db0126cf2a716f1"><div class="ttname"><a href="object_8h.html#ac2b7418e9549512b5db0126cf2a716f1">TVM_DECLARE_BASE_OBJECT_INFO</a></div><div class="ttdeci">#define TVM_DECLARE_BASE_OBJECT_INFO(TypeName, ParentType)</div><div class="ttdoc">helper macro to declare a base object type that can be inherited. </div><div class="ttdef"><b>Definition:</b> object.h:648</div></div>
<div class="ttc" id="classtvm_1_1detail_1_1AttrNonDefaultVisitor_html"><div class="ttname"><a href="classtvm_1_1detail_1_1AttrNonDefaultVisitor.html">tvm::detail::AttrNonDefaultVisitor</a></div><div class="ttdef"><b>Definition:</b> attrs.h:814</div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793af2b95de1a09ed39055edfe8ef5ea484d"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793af2b95de1a09ed39055edfe8ef5ea484d">kTVMStr</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:178</div></div>
<div class="ttc" id="classtvm_1_1detail_1_1AttrInitVisitor_html_af0856406dd74c88334291da4eff0543d"><div class="ttname"><a href="classtvm_1_1detail_1_1AttrInitVisitor.html#af0856406dd74c88334291da4eff0543d">tvm::detail::AttrInitVisitor::operator()</a></div><div class="ttdeci">AttrInitEntry< T > operator()(const char *key, T *value)</div><div class="ttdef"><b>Definition:</b> attrs.h:649</div></div>
<div class="ttc" id="namespacetvm_html_a2e3193a20ee748b08d5a528275859dbe"><div class="ttname"><a href="namespacetvm.html#a2e3193a20ee748b08d5a528275859dbe">tvm::AttrsWithDefaultValues</a></div><div class="ttdeci">TAttrs AttrsWithDefaultValues()</div><div class="ttdoc">Create an Attr object with all default values. </div><div class="ttdef"><b>Definition:</b> attrs.h:312</div></div>
diff --git a/docs/reference/api/doxygen/ir_2expr_8h_source.html b/docs/reference/api/doxygen/ir_2expr_8h_source.html
index 993e7df698..0066f0aca5 100644
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@@ -138,7 +138,7 @@ $(function() {
<div class="ttc" id="namespacetvm_html_abd7d1b3232218b25e2e0cf6ef699a65f"><div class="ttname"><a href="namespacetvm.html#abd7d1b3232218b25e2e0cf6ef699a65f">tvm::operator^</a></div><div class="ttdeci">PrimExpr operator^(PrimExpr a, PrimExpr b)</div><div class="ttdoc">take bitwise xor of two values </div></div>
<div class="ttc" id="classtvm_1_1RangeNode_html_a4bbc33969cb484c20306da1d2b9fa1fd"><div class="ttname"><a href="classtvm_1_1RangeNode.html#a4bbc33969cb484c20306da1d2b9fa1fd">tvm::RangeNode::RangeNode</a></div><div class="ttdeci">RangeNode(PrimExpr min, PrimExpr extent, Span span=Span())</div><div class="ttdef"><b>Definition:</b> expr.h:688</div></div>
<div class="ttc" id="classtvm_1_1RelayExprNode_html_ad6ea21e1a03d972ac5cf81b80b88b2c4"><div class="ttname"><a href="classtvm_1_1RelayExprNode.html#ad6ea21e1a03d972ac5cf81b80b88b2c4">tvm::RelayExprNode::virtual_device_</a></div><div class="ttdeci">ObjectRef virtual_device_</div><div class="ttdoc">The virtual device (VirtualDevice) for this node (the result of device planning). For first-order exp...</div><div class="ttdef"><b>Definition:</b> expr.h:407</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a289a65bf255e3d192c60d7b5a8dcf097"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_::AsObjectRef</a></div><div class="ttdeci">TObjectRef AsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1823</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a289a65bf255e3d192c60d7b5a8dcf097"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_::AsObjectRef</a></div><div class="ttdeci">TObjectRef AsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1822</div></div>
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
<div class="ttc" id="classtvm_1_1IntImmNode_html_a81f4c116ffb5931fdd64639eacad415d"><div class="ttname"><a href="classtvm_1_1IntImmNode.html#a81f4c116ffb5931fdd64639eacad415d">tvm::IntImmNode::value</a></div><div class="ttdeci">int64_t value</div><div class="ttdoc">the Internal value. </div><div class="ttdef"><b>Definition:</b> expr.h:492</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1String_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html">tvm::runtime::String</a></div><div class="ttdoc">Reference to string objects. </div><div class="ttdef"><b>Definition:</b> string.h:97</div></div>
diff --git a/docs/reference/api/doxygen/layer__norm_8h_source.html b/docs/reference/api/doxygen/layer__norm_8h_source.html
index 05d1305c07..42b6b4beb4 100644
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@@ -68,7 +68,7 @@ $(function() {
<div class="contents">
<a href="layer__norm_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more [...]
<div class="ttc" id="namespacetvm_1_1topi_html_a12a94f9c1103f5e05fb9819e7176bf4c"><div class="ttname"><a href="namespacetvm_1_1topi.html#a12a94f9c1103f5e05fb9819e7176bf4c">tvm::topi::MakeTupleSumReducer</a></div><div class="ttdeci">FCommReduce MakeTupleSumReducer()</div><div class="ttdoc">Create communitive reducer summing over tuples. </div><div class="ttdef"><b>Definition:</b> reduction.h:576</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a29e22aa45900dad3b6f9f705bb1dc688"><div class="ttname"><a href="namespacetvm_1_1topi.html#a29e22aa45900dad3b6f9f705bb1dc688">tvm::topi::kInjective</a></div><div class="ttdeci">constexpr auto kInjective</div><div class="ttdef"><b>Definition:</b> tags.h:33</div></div>
diff --git a/docs/reference/api/doxygen/local__response__norm_8h_source.html b/docs/reference/api/doxygen/local__response__norm_8h_source.html
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<a href="local__response__norm_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Var_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Var.html">tvm::tir::Var</a></div><div class="ttdoc">a named variable in TIR </div><div class="ttdef"><b>Definition:</b> var.h:88</div></div>
diff --git a/docs/reference/api/doxygen/metadata_8h_source.html b/docs/reference/api/doxygen/metadata_8h_source.html
index 2c5138b038..1441f4862c 100644
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<div class="ttc" id="metadata__types_8h_html"><div class="ttname"><a href="metadata__types_8h.html">metadata_types.h</a></div><div class="ttdoc">Defines types which can be used in metadata here which are also shared between C and C++ code bases...</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1metadata_1_1TensorInfoNode_html_a76aebd7390d27be91e5b7bad9e664c5d"><div class="ttname"><a href="classtvm_1_1runtime_1_1metadata_1_1TensorInfoNode.html#a76aebd7390d27be91e5b7bad9e664c5d">tvm::runtime::metadata::TensorInfoNode::num_shape</a></div><div class="ttdeci">int64_t num_shape() const</div><div class="ttdef"><b>Definition:</b> metadata.h:88</div></div>
<div class="ttc" id="c__runtime__api_8h_html"><div class="ttname"><a href="c__runtime__api_8h.html">c_runtime_api.h</a></div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1metadata_1_1MetadataBase_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1metadata_1_1MetadataBase.html">tvm::runtime::metadata::MetadataBase</a></div><div class="ttdoc">Reference class for the common MetadataBaseNode class. </div><div class="ttdef"><b>Definition:</b> metadata_base.h:54</div></div>
<div class="ttc" id="metadata_8h_html_a700f5dfbc1a51a0186d4c5a298ea3fd6"><div class="ttname"><a href="metadata_8h.html#a700f5dfbc1a51a0186d4c5a298ea3fd6">TVM_METADATA_VERSION</a></div><div class="ttdeci">#define TVM_METADATA_VERSION</div><div class="ttdef"><b>Definition:</b> metadata.h:39</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1metadata_1_1MetadataNode_html_a6e76b478a43f97e867727f4cd3036771"><div class="ttname"><a href="classtvm_1_1runtime_1_1metadata_1_1MetadataNode.html#a6e76b478a43f97e867727f4cd3036771">tvm::runtime::metadata::MetadataNode::num_inputs</a></div><div class="ttdeci">int64_t num_inputs() const</div><div class="ttdef"><b>Definition:</b> metadata.h:60</div></div>
diff --git a/docs/reference/api/doxygen/ndarray_8h_source.html b/docs/reference/api/doxygen/ndarray_8h_source.html
index acae14ace3..894601cfd4 100644
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<div class="ttc" id="namespacetvm_1_1runtime_html_a8fb37910dcd9bb6899e6a3a47f006514"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a8fb37910dcd9bb6899e6a3a47f006514">tvm::runtime::SaveDLTensor</a></div><div class="ttdeci">bool SaveDLTensor(dmlc::Stream *strm, const DLTensor *tensor)</div><div class="ttdoc">Save a DLTensor to stream. </div><div class="ttdef"><b>Definition:</b> ndarray.h:449</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_html_abec485628a0ca451b668c42fd8fa691a"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray.html#abec485628a0ca451b668c42fd8fa691a">tvm::runtime::NDArray::FromDLPack</a></div><div class="ttdeci">static NDArray FromDLPack(DLManagedTensor *tensor)</div><div class="ttdoc">Create a NDArray backed by a dlpack tensor. </div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1514</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1513</div></div>
<div class="ttc" id="namespacetvm_html_aae7034e3e41c18e7fb78ff32bfc6a318"><div class="ttname"><a href="namespacetvm.html#aae7034e3e41c18e7fb78ff32bfc6a318">tvm::NullOpt</a></div><div class="ttdeci">constexpr runtime::NullOptType NullOpt</div><div class="ttdef"><b>Definition:</b> optional.h:160</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_html_abdef2994270da88d69a39245216543d8"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray.html#abdef2994270da88d69a39245216543d8">tvm::runtime::NDArray::CopyToBytes</a></div><div class="ttdeci">void CopyToBytes(void *data, size_t nbytes) const</div><div class="ttdoc">Copy data content into another array. </div></div>
<div class="ttc" id="namespacetvm_html_ab7076521b2e0d4224b7803811cbd1fd6"><div class="ttname"><a href="namespacetvm.html#ab7076521b2e0d4224b7803811cbd1fd6">tvm::kNullDeviceType</a></div><div class="ttdeci">constexpr DLDeviceType kNullDeviceType</div><div class="ttdef"><b>Definition:</b> ndarray.h:48</div></div>
diff --git a/docs/reference/api/doxygen/nn_2bnn_8h_source.html b/docs/reference/api/doxygen/nn_2bnn_8h_source.html
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@@ -67,7 +67,7 @@ $(function() {
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<a href="nn_2bnn_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more con [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Var_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Var.html">tvm::tir::Var</a></div><div class="ttdoc">a named variable in TIR </div><div class="ttdef"><b>Definition:</b> var.h:88</div></div>
diff --git a/docs/reference/api/doxygen/nn_2pooling_8h_source.html b/docs/reference/api/doxygen/nn_2pooling_8h_source.html
index 6ef2fe708e..1a3c1e18ff 100644
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@@ -72,7 +72,7 @@ $(function() {
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<div class="ttc" id="namespacetvm_1_1topi_html_a4b434e701bc9835e2a7de8f0fadebea5"><div class="ttname"><a href="namespacetvm_1_1topi.html#a4b434e701bc9835e2a7de8f0fadebea5">tvm::topi::MakeArgmaxReducer</a></div><div class="ttdeci">FCommReduce MakeArgmaxReducer(bool select_last_index=false)</div><div class="ttdef"><b>Definition:</b> reduction.h:495</div></div>
<div class="ttc" id="namespacetvm_html_ada5ad8338d3144221d8f16380e6c4855"><div class="ttname"><a href="namespacetvm.html#ada5ad8338d3144221d8f16380e6c4855">tvm::indexmod</a></div><div class="ttdeci">PrimExpr indexmod(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute the remainder floor(a / b) where a and b are non-negative. </div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_ae488679377c78cd5411b7df11c297673"><div class="ttname"><a href="namespacetvm_1_1topi.html#ae488679377c78cd5411b7df11c297673">tvm::topi::min</a></div><div class="ttdeci">Tensor min(const Tensor &data, const Array< Integer > &axis, bool keepdims=false, bool atleast1d=false)</div><div class="ttdoc">Creates an operation that finds the minimum of elements over a given axis. </div><div class="ttdef"><b>Definition:</b> reduction.h:410 [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1topi_1_1nn_html_a3fb74f1c3df6edf17c9a3f1e122f84fe"><div class="ttname"><a href="namespacetvm_1_1topi_1_1nn.html#a3fb74f1c3df6edf17c9a3f1e122f84fe">tvm::topi::nn::adaptive_pool_impl</a></div><div class="ttdeci">Tensor adaptive_pool_impl(const Tensor &x, const Array< PrimExpr > &output_size, PoolType pool_type, const std::vector< int > &axes)</div><div class="ttdoc">Perform adaptive pooling on N dimensional data. </div><div class [...]
diff --git a/docs/reference/api/doxygen/object_8h_source.html b/docs/reference/api/doxygen/object_8h_source.html
index b6a7e37644..bd01f0cbb9 100644
--- a/docs/reference/api/doxygen/object_8h_source.html
+++ b/docs/reference/api/doxygen/object_8h_source.html
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<div class="ttc" id="classtvm_1_1runtime_1_1ObjectPtr_html_a62e18d1b81152c6caf93961eca6d04bc"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectPtr.html#a62e18d1b81152c6caf93961eca6d04bc">tvm::runtime::ObjectPtr::ObjectPtr</a></div><div class="ttdeci">ObjectPtr(ObjectPtr< Y > &&other)</div><div class="ttdoc">move constructor </div><div class="ttdef"><b>Definition:</b> object.h:393</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectPtr_html_ac56d7fad8cbc348ad8ef0e7e23ee90e2"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectPtr.html#ac56d7fad8cbc348ad8ef0e7e23ee90e2">tvm::runtime::ObjectPtr::~ObjectPtr</a></div><div class="ttdeci">~ObjectPtr()</div><div class="ttdoc">destructor </div><div class="ttdef"><b>Definition:</b> object.h:400</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1514</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1513</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html_a4bfc2586cb55f2af47728187b3256255"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">tvm::runtime::Object::type_index_</a></div><div class="ttdeci">uint32_t type_index_</div><div class="ttdoc">Type index(tag) that indicates the type of the object. </div><div class="ttdef"><b>Definition:</b> object.h:261</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_a0ae0da21d247cd87ea94fe3777c4405e"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#a0ae0da21d247cd87ea94fe3777c4405e">tvm::runtime::ObjectRef::use_count</a></div><div class="ttdeci">int use_count() const</div><div class="ttdef"><b>Definition:</b> object.h:552</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html_ae341e561272ff43cdcbc927bc29ac50d"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">tvm::runtime::Object::operator=</a></div><div class="ttdeci">Object & operator=(Object &&other)</div><div class="ttdef"><b>Definition:</b> object.h:254</div></div>
diff --git a/docs/reference/api/doxygen/packed__func_8h_source.html b/docs/reference/api/doxygen/packed__func_8h_source.html
index 2d3e0fee5c..1287a9bbc6 100644
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<div class="title">packed_func.h</div> </div>
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-<a href="packed__func_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or mor [...]
+<a href="packed__func_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or mor [...]
<div class="ttc" id="namespacetvm_1_1runtime_html_a129050a60cebb0bbe18f96b41a36a948"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a129050a60cebb0bbe18f96b41a36a948">tvm::runtime::ArgTypeCode2Str</a></div><div class="ttdeci">const char * ArgTypeCode2Str(int type_code)</div><div class="ttdoc">Convert argument type code to string. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1225</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgs_html_afec79c909bdf103a01cdb4732c0afdf3"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgs.html#afec79c909bdf103a01cdb4732c0afdf3">tvm::runtime::TVMArgs::num_args</a></div><div class="ttdeci">int num_args</div><div class="ttdef"><b>Definition:</b> packed_func.h:395</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgValue_html_a987b2fb283cea5484d4655e3f711c046"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgValue.html#a987b2fb283cea5484d4655e3f711c046">tvm::runtime::TVMArgValue::TVMArgValue</a></div><div class="ttdeci">TVMArgValue()</div><div class="ttdoc">default constructor </div><div class="ttdef"><b>Definition:</b> packed_func.h:649</div></div>
@@ -74,23 +74,23 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a952f62623ec147f366363b664d749566"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a952f62623ec147f366363b664d749566">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(std::string value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:900</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ArrayNode_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ArrayNode.html">tvm::runtime::ArrayNode</a></div><div class="ttdoc">array node content in array </div><div class="ttdef"><b>Definition:</b> array.h:40</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html">tvm::runtime::TVMRetValue</a></div><div class="ttdoc">Return Value container, Unlike TVMArgValue, which only holds reference and do not delete the underlyi...</div><div class="ttdef"><b>Definition:</b> packed_func.h:799</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1Module_html_a1233f7b896bb299ef07f9e41a4ffdc17"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html#a1233f7b896bb299ef07f9e41a4ffdc17">tvm::runtime::Module::GetFunction</a></div><div class="ttdeci">PackedFunc GetFunction(const std::string &name, bool query_imports=false)</div><div class="ttdoc">Get packed function from current module by name. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1937</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1Module_html_a1233f7b896bb299ef07f9e41a4ffdc17"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html#a1233f7b896bb299ef07f9e41a4ffdc17">tvm::runtime::Module::GetFunction</a></div><div class="ttdeci">PackedFunc GetFunction(const std::string &name, bool query_imports=false)</div><div class="ttdoc">Get packed function from current module by name. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1936</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_html_ade0e2757904f4f5ba5c667ae01793a47"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray.html#ade0e2757904f4f5ba5c667ae01793a47">tvm::runtime::NDArray::FFIDecRef</a></div><div class="ttdeci">static void FFIDecRef(TVMArrayHandle handle)</div><div class="ttdoc">DecRef resource managed by an FFI array handle. </div><div class="ttdef"><b>Definition:</b> ndarray.h:438</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_ae47baae854e2ff66d0ef87178727d8f4"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#ae47baae854e2ff66d0ef87178727d8f4">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(TVMMovableArgValue_ &&other)</div><div class="ttdef"><b>Definition:</b> packed_func.h:940</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a4c6dffcee3ea29b0b5862f1cc42c5c1c"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a4c6dffcee3ea29b0b5862f1cc42c5c1c">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, TObjectRef &&value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1596</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a4c6dffcee3ea29b0b5862f1cc42c5c1c"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a4c6dffcee3ea29b0b5862f1cc42c5c1c">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, TObjectRef &&value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1595</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a74ea2767d491c57cb9c71e26ee934344"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a74ea2767d491c57cb9c71e26ee934344">tvm::runtime::TVMRetValue::MoveToCHost</a></div><div class="ttdeci">void MoveToCHost(TVMValue *ret_value, int *ret_type_code)</div><div class="ttdoc">Move the value back to front-end via C API. This marks the current container as null. The managed resources are moved to the front-end. The fr [...]
<div class="ttc" id="namespacetvm_html_aac2abc149c1a47944c37b560181b15c0"><div class="ttname"><a href="namespacetvm.html#aac2abc149c1a47944c37b560181b15c0">tvm::min</a></div><div class="ttdeci">PrimExpr min(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take minimum of two values </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectPtr_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectPtr.html">tvm::runtime::ObjectPtr</a></div><div class="ttdoc">A custom smart pointer for Object. </div><div class="ttdef"><b>Definition:</b> object.h:358</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgs_html_a5d2aeac7387e436e6e19d7a6dfe91307"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgs.html#a5d2aeac7387e436e6e19d7a6dfe91307">tvm::runtime::TVMArgs::TVMArgs</a></div><div class="ttdeci">TVMArgs(const TVMValue *values, const int *type_codes, int num_args)</div><div class="ttdoc">constructor </div><div class="ttdef"><b>Definition:</b> packed_func.h:402</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html">tvm::runtime::TypedPackedFunc< R(Args...)></a></div><div class="ttdoc">A PackedFunc wrapper to provide typed function signature. It is backed by a PackedFunc internally...</div><div class="ttdef"><b>Definition:</b> packed_func.h:227</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncObj_1_1Extractor_html_adf102893804b158738958af709d50d4a"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncObj_1_1Extractor.html#adf102893804b158738958af709d50d4a">tvm::runtime::PackedFuncObj::Extractor::Call</a></div><div class="ttdeci">static void Call(const PackedFuncObj *obj, TVMArgs args, TVMRetValue *rv)</div><div class="ttdoc">Extracting the callable method from callable type. </div><div class="ttdef"><b>Definitio [...]
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a6e00a60133af36e1a83543b6e9605ce1"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a6e00a60133af36e1a83543b6e9605ce1">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const char *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1559</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a6e00a60133af36e1a83543b6e9605ce1"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a6e00a60133af36e1a83543b6e9605ce1">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const char *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1558</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html_a327afe71a47ff06867d6276db08ad5b6"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html#a327afe71a47ff06867d6276db08ad5b6">tvm::runtime::PackedFunc::operator!=</a></div><div class="ttdeci">bool operator!=(std::nullptr_t null) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:180</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a510ec87e6718c0e6197e7321ca8774f2"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a510ec87e6718c0e6197e7321ca8774f2">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(bool value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:895</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_aed3e983e990c5c4ed3ac09b95055297e"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#aed3e983e990c5c4ed3ac09b95055297e">tvm::runtime::TVMPODValue_::type_code_</a></div><div class="ttdeci">int type_code_</div><div class="ttdoc">the type code </div><div class="ttdef"><b>Definition:</b> packed_func.h:637</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html">tvm::runtime::TVMPODValue_</a></div><div class="ttdoc">Internal base class to handle conversion to POD values. </div><div class="ttdef"><b>Definition:</b> packed_func.h:541</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a09f6c31e1462a4662c1e546a38b5bcde"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a09f6c31e1462a4662c1e546a38b5bcde">tvm::runtime::PackedFuncObj::_type_index</a></div><div class="ttdeci">static constexpr const uint32_t _type_index</div><div class="ttdef"><b>Definition:</b> packed_func.h:77</div></div>
-<div class="ttc" id="namespacetvm_1_1runtime_html_ac360f2d9815036ab1b4d84d9cfb46b4f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ac360f2d9815036ab1b4d84d9cfb46b4f">tvm::runtime::DLDataType2String</a></div><div class="ttdeci">std::string DLDataType2String(DLDataType t)</div><div class="ttdoc">convert a TVM type to string. </div><div class="ttdef"><b>Definition:</b> data_type.h:342</div></div>
+<div class="ttc" id="namespacetvm_1_1runtime_html_ac360f2d9815036ab1b4d84d9cfb46b4f"><div class="ttname"><a href="namespacetvm_1_1runtime.html#ac360f2d9815036ab1b4d84d9cfb46b4f">tvm::runtime::DLDataType2String</a></div><div class="ttdeci">std::string DLDataType2String(DLDataType t)</div><div class="ttdoc">convert a TVM type to string. </div><div class="ttdef"><b>Definition:</b> data_type.h:341</div></div>
<div class="ttc" id="unionTVMValue_html_a3b172297f9f7bf2f5391f7d87309cd44"><div class="ttname"><a href="unionTVMValue.html#a3b172297f9f7bf2f5391f7d87309cd44">TVMValue::v_handle</a></div><div class="ttdeci">void * v_handle</div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:204</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_a0bccd3ff1f23a8aa094e1a679539096d"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a0bccd3ff1f23a8aa094e1a679539096d">tvm::runtime::TypedPackedFunc< R(Args...)>::packed</a></div><div class="ttdeci">const PackedFunc & packed() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:358</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793ad742641b52cb5098f576373021a1399d"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793ad742641b52cb5098f576373021a1399d">kTVMObjectRValueRefArg</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:181</div></div>
@@ -100,7 +100,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html_a9b39e8a75956bc889745ded9131b9c17"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html#a9b39e8a75956bc889745ded9131b9c17">tvm::runtime::PackedFunc::CallPacked</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void CallPacked(TVMArgs args, TVMRetValue *rv) const</div><div class="ttdoc">Call the function in packed format. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1220</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793a41343a05e42d08053d9fa1da85f70af6"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793a41343a05e42d08053d9fa1da85f70af6">kTVMModuleHandle</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:176</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMMovableArgValue___html_a8eca9048535541f374a5806f9648131b"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMMovableArgValue__.html#a8eca9048535541f374a5806f9648131b">tvm::runtime::TVMMovableArgValue_::TVMMovableArgValue_</a></div><div class="ttdeci">TVMMovableArgValue_(TVMValue value, int type_code)</div><div class="ttdef"><b>Definition:</b> packed_func.h:711</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a0ae2685077edbfa6a4e1743b8f5ad3ed"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a0ae2685077edbfa6a4e1743b8f5ad3ed">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DLTensor *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1544</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a0ae2685077edbfa6a4e1743b8f5ad3ed"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a0ae2685077edbfa6a4e1743b8f5ad3ed">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DLTensor *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1543</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a0eeb2af3fa21cebfdc2bcf04b2fbb1f6"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a0eeb2af3fa21cebfdc2bcf04b2fbb1f6">tvm::runtime::TVMRetValue::~TVMRetValue</a></div><div class="ttdeci">~TVMRetValue()</div><div class="ttdoc">destructor </div><div class="ttdef"><b>Definition:</b> packed_func.h:812</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793a6ee930a6be374837d4d85dbe1abeb842"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793a6ee930a6be374837d4d85dbe1abeb842">kTVMDataType</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:172</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgs_html_a3b99059e2f1ad08c99b42b5bee82752f"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgs.html#a3b99059e2f1ad08c99b42b5bee82752f">tvm::runtime::TVMArgs::values</a></div><div class="ttdeci">const TVMValue * values</div><div class="ttdef"><b>Definition:</b> packed_func.h:393</div></div>
@@ -128,23 +128,23 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html_a90e90b3f4ba8a590baff78c75807bbc7"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">tvm::runtime::Object::IsInstance</a></div><div class="ttdeci">bool IsInstance() const</div><div class="ttdef"><b>Definition:</b> object.h:829</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_aafc5d18f0ac508fdd8a90b5af9bc1eff"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#aafc5d18f0ac508fdd8a90b5af9bc1eff">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(const TVMArgValue &other)</div><div class="ttdef"><b>Definition:</b> packed_func.h:936</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_abf351bdd97209c8fb656b60abce7fccb"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#abf351bdd97209c8fb656b60abce7fccb">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(double value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:859</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ad249e13ae15927ea1e606e6fdff207f3"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ad249e13ae15927ea1e606e6fdff207f3">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TVMByteArray &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1568</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ad249e13ae15927ea1e606e6fdff207f3"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ad249e13ae15927ea1e606e6fdff207f3">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TVMByteArray &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1567</div></div>
<div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Runtime Array container types. </div></div>
<div class="ttc" id="structTVMArgs_html"><div class="ttname"><a href="structTVMArgs.html">TVMArgs</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:38</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMMovableArgValue___html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMMovableArgValue__.html">tvm::runtime::TVMMovableArgValue_</a></div><div class="ttdoc">Internal auxiliary struct for TypedPackedFunc to indicate a movable argument. </div><div class="ttdef"><b>Definition:</b> packed_func.h:709</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Map_3_01K_00_01V_01_4_01_4_html_a66cc223f8e80086a6396540546b07eed"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Map_3_01K_00_01V_01_4_01_4.html#a66cc223f8e80086a6396540546b07eed">tvm::runtime::ObjectTypeChecker< Map< K, V > >::Check</a></div><div class="ttdeci">static bool Check(const Object *ptr)</div><div class="ttdef"><b>Definition:</b> packed_func.h:521</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a533c034c471f3c09341dcfbfcbb20d9a"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a533c034c471f3c09341dcfbfcbb20d9a">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, T value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1519</div></div>
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<div class="ttc" id="ndarray_8h_html"><div class="ttname"><a href="ndarray_8h.html">ndarray.h</a></div><div class="ttdoc">A device-independent managed NDArray abstraction. </div></div>
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+<div class="ttc" id="namespacetvm_1_1runtime_html_a277f104e659f71cd8885744700016341"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a277f104e659f71cd8885744700016341">tvm::runtime::String2DLDataType</a></div><div class="ttdeci">DLDataType String2DLDataType(std::string s)</div><div class="ttdoc">convert a string to TVM type. </div><div class="ttdef"><b>Definition:</b> data_type.h:348</div></div>
+<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4_html_a9ac48d52f86dc3718590acc119e88741"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4.html#a9ac48d52f86dc3718590acc119e88741">tvm::runtime::PackedFuncValueConverter<::tvm::runtime::String >::From</a></div><div class="ttdeci">static String From(const TVMRetValue &val)</div><div class="ttdef"><b>Definition:</b> [...]
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_html_ab76ba9c638e1d6db8d6f0ba8c4d38670"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray.html#ab76ba9c638e1d6db8d6f0ba8c4d38670">tvm::runtime::NDArray::FFIDataFromHandle</a></div><div class="ttdeci">static ObjectPtr< Object > FFIDataFromHandle(TVMArrayHandle handle)</div><div class="ttdoc">Construct NDArray&#39;s Data field from array handle in FFI. </div><div class="ttdef"><b>Definition:</b> ndarray.h:425</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker.html">tvm::runtime::ObjectTypeChecker</a></div><div class="ttdoc">Type traits for runtime type check during FFI conversion. </div><div class="ttdef"><b>Definition:</b> packed_func.h:430</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a67fdc41da2d772f61a924b8fa2d820e5"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a67fdc41da2d772f61a924b8fa2d820e5">tvm::runtime::TVMPODValue_::IsObjectRef</a></div><div class="ttdeci">bool IsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1792</div></div>
-<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_01Optional_3_01T_01_4_01_4_html_a6748e04a16945df4c15edb53d0aaba70"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_01Optional_3_01T_01_4_01_4.html#a6748e04a16945df4c15edb53d0aaba70">tvm::runtime::PackedFuncValueConverter< Optional< T > >::From</a></div><div class="ttdeci">static Optional< T > From(const TVMArgValue &val)</div><div class="ttdef"><b>Definition:</b> [...]
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a67fdc41da2d772f61a924b8fa2d820e5"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a67fdc41da2d772f61a924b8fa2d820e5">tvm::runtime::TVMPODValue_::IsObjectRef</a></div><div class="ttdeci">bool IsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1791</div></div>
+<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_01Optional_3_01T_01_4_01_4_html_a6748e04a16945df4c15edb53d0aaba70"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_01Optional_3_01T_01_4_01_4.html#a6748e04a16945df4c15edb53d0aaba70">tvm::runtime::PackedFuncValueConverter< Optional< T > >::From</a></div><div class="ttdeci">static Optional< T > From(const TVMArgValue &val)</div><div class="ttdef"><b>Definition:</b> [...]
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html">tvm::runtime::DataType</a></div><div class="ttdoc">Runtime primitive data type. </div><div class="ttdef"><b>Definition:</b> data_type.h:41</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_a17d8d5ad92691f9e18e3e0ae8ef69e4f"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#a17d8d5ad92691f9e18e3e0ae8ef69e4f">tvm::runtime::ObjectRef::defined</a></div><div class="ttdeci">bool defined() const</div><div class="ttdef"><b>Definition:</b> object.h:544</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a784a2e0f1412187befbacf0b23dbcd12"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a784a2e0f1412187befbacf0b23dbcd12">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, Device value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1548</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a784a2e0f1412187befbacf0b23dbcd12"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a784a2e0f1412187befbacf0b23dbcd12">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, Device value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1547</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgs_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgs.html">tvm::runtime::TVMArgs</a></div><div class="ttdoc">Arguments into TVM functions. </div><div class="ttdef"><b>Definition:</b> packed_func.h:391</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_ac4a3850c0989e7c2d5cd8e0f096d0997"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#ac4a3850c0989e7c2d5cd8e0f096d0997">tvm::runtime::TVMRetValue::TVMRetValue</a></div><div class="ttdeci">TVMRetValue(TVMRetValue &&other)</div><div class="ttdoc">move constructor from another return value. </div><div class="ttdef"><b>Definition:</b> packed_func.h:807</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_a8dd1fbae84cb9597c52977b0e8db64dc"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a8dd1fbae84cb9597c52977b0e8db64dc">tvm::runtime::TypedPackedFunc< R(Args...)>::operator=</a></div><div class="ttdeci">TSelf & operator=(FLambda typed_lambda)</div><div class="ttdoc">copy assignment operator from typed lambda </div><div class="ttdef"><b>Definiti [...]
@@ -153,7 +153,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Array_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Array.html">tvm::runtime::Array</a></div><div class="ttdoc">Array, container representing a contiguous sequence of ObjectRefs. </div><div class="ttdef"><b>Definition:</b> array.h:289</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793a3bab8c80e57b1ab2d7ab95962be4d2ec"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793a3bab8c80e57b1ab2d7ab95962be4d2ec">kTVMNDArrayHandle</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:180</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_a8941c80982a1b2a289440f3c79bb0ac8"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a8941c80982a1b2a289440f3c79bb0ac8">tvm::runtime::TypedPackedFunc< R(Args...)>::TypedPackedFunc</a></div><div class="ttdeci">TypedPackedFunc(const FLambda &typed_lambda, std::string name)</div><div class="ttdoc">construct from a lambda function with the same sig [...]
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a2e484d891ed2be751d514bb58e48faa5"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a2e484d891ed2be751d514bb58e48faa5">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, uint64_t value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1523</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a2e484d891ed2be751d514bb58e48faa5"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a2e484d891ed2be751d514bb58e48faa5">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, uint64_t value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1522</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Array_3_01T_01_4_01_4_html_aab22b555cfe16d040c204527c73a3287"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Array_3_01T_01_4_01_4.html#aab22b555cfe16d040c204527c73a3287">tvm::runtime::ObjectTypeChecker< Array< T > >::TypeName</a></div><div class="ttdeci">static std::string TypeName()</div><div class="ttdef"><b>Definition:</b> packed_func.h:500</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_aa590b3e712e06867805b41aaf17019ed"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#aa590b3e712e06867805b41aaf17019ed">tvm::runtime::TypedPackedFunc< R(Args...)>::operator=</a></div><div class="ttdeci">TSelf & operator=(PackedFunc packed)</div><div class="ttdoc">copy assignment operator from PackedFunc. </div><div class="ttdef"><b>Definition:< [...]
<div class="ttc" id="structtvm_1_1runtime_1_1TypeIndex_html_aed93c7318efc8052201d4c404b21a40da23eb6ecfca76a965bf4727a4e931584b"><div class="ttname"><a href="structtvm_1_1runtime_1_1TypeIndex.html#aed93c7318efc8052201d4c404b21a40da23eb6ecfca76a965bf4727a4e931584b">tvm::runtime::TypeIndex::kRuntimePackedFunc</a></div><div class="ttdoc">runtime::PackedFunc. </div><div class="ttdef"><b>Definition:</b> object.h:74</div></div>
@@ -161,23 +161,23 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_1_1Container_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray_1_1Container.html">tvm::runtime::NDArray::Container</a></div><div class="ttdoc">Object container class that backs NDArray. </div><div class="ttdef"><b>Definition:</b> ndarray.h:294</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a4ab194932127e4b1c372e5e58e450721"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a4ab194932127e4b1c372e5e58e450721">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(PackedFunc f)</div><div class="ttdef"><b>Definition:</b> packed_func.h:924</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a063452b7982696b09f35b20993ac3138"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a063452b7982696b09f35b20993ac3138">tvm::runtime::PackedFuncObj::PackedFuncObj</a></div><div class="ttdeci">PackedFuncObj(FCallPacked *f_call_pack)</div><div class="ttdoc">Constructing a packed function object from a function pointer. </div><div class="ttdef"><b>Definition:</b> packed_func.h:103</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a3a8c3436ed1235e1c6bc4825b1e606a8"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a3a8c3436ed1235e1c6bc4825b1e606a8">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TObjectRef &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1589</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a3a8c3436ed1235e1c6bc4825b1e606a8"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a3a8c3436ed1235e1c6bc4825b1e606a8">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TObjectRef &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1588</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgs_html_abdb0f929087b14eb28d75c7a047cef9e"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgs.html#abdb0f929087b14eb28d75c7a047cef9e">tvm::runtime::TVMArgs::type_codes</a></div><div class="ttdeci">const int * type_codes</div><div class="ttdef"><b>Definition:</b> packed_func.h:394</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_ac261cdb80487fb29ac42b28678f8cbef"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#ac261cdb80487fb29ac42b28678f8cbef">tvm::runtime::ObjectRef::data_</a></div><div class="ttdeci">ObjectPtr< Object > data_</div><div class="ttdoc">Internal pointer that backs the reference. </div><div class="ttdef"><b>Definition:</b> object.h:574</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a2c8860df3cbdc52104dca8274abfa219"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a2c8860df3cbdc52104dca8274abfa219">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(DLDataType t)</div><div class="ttdef"><b>Definition:</b> packed_func.h:889</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html_a5c4ed23ffcb6a1874bd6eceb87b40b25"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html#a5c4ed23ffcb6a1874bd6eceb87b40b25">tvm::runtime::PackedFunc::operator==</a></div><div class="ttdeci">bool operator==(std::nullptr_t null) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:178</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a289a65bf255e3d192c60d7b5a8dcf097"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_::AsObjectRef</a></div><div class="ttdeci">TObjectRef AsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1823</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a289a65bf255e3d192c60d7b5a8dcf097"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_::AsObjectRef</a></div><div class="ttdeci">TObjectRef AsObjectRef() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1822</div></div>
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a9f87512cfec647c8011ab9e5c57bb0d1"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a9f87512cfec647c8011ab9e5c57bb0d1">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const std::string &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1564</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a9f87512cfec647c8011ab9e5c57bb0d1"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a9f87512cfec647c8011ab9e5c57bb0d1">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const std::string &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1563</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1String_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html">tvm::runtime::String</a></div><div class="ttdoc">Reference to string objects. </div><div class="ttdef"><b>Definition:</b> string.h:97</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_ac6f4a12b41a1fbb3e23e1bb77bcc3383"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#ac6f4a12b41a1fbb3e23e1bb77bcc3383">tvm::runtime::PackedFuncObj::FCallPacked</a></div><div class="ttdeci">void(const PackedFuncObj *, TVMArgs, TVMRetValue *) FCallPacked</div><div class="ttdoc">The internal callable function type. </div><div class="ttdef"><b>Definition:</b> packed_func.h:97</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc.html">tvm::runtime::TypedPackedFunc</a></div><div class="ttdoc">Please refer to TypedPackedFunc<R(Args..)>. </div><div class="ttdef"><b>Definition:</b> packed_func.h:60</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html">tvm::runtime::PackedFuncObj</a></div><div class="ttdoc">Object container class that backs PackedFunc. </div><div class="ttdef"><b>Definition:</b> packed_func.h:68</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ae4047db2c029877c72c6252fc17fe911"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ae4047db2c029877c72c6252fc17fe911">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DataType dtype) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1556</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ae4047db2c029877c72c6252fc17fe911"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ae4047db2c029877c72c6252fc17fe911">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DataType dtype) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1555</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_afe1837bdbafe8341c2031c5cebcf6e74"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#afe1837bdbafe8341c2031c5cebcf6e74">tvm::runtime::TVMPODValue_::TVMPODValue_</a></div><div class="ttdeci">TVMPODValue_(TVMValue value, int type_code)</div><div class="ttdef"><b>Definition:</b> packed_func.h:632</div></div>
<div class="ttc" id="object_8h_html_ac6e7295a4999e2c8e4a2c990beca887a"><div class="ttname"><a href="object_8h.html#ac6e7295a4999e2c8e4a2c990beca887a">TVM_DEFINE_OBJECT_REF_METHODS</a></div><div class="ttdeci">#define TVM_DEFINE_OBJECT_REF_METHODS(TypeName, ParentType, ObjectName)</div><div class="ttdef"><b>Definition:</b> object.h:713</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a4dec02b60187e36214c20fea675a5b49"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a4dec02b60187e36214c20fea675a5b49">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, double value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1528</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_aa5f1f6cbf78fc255d8a4ceaea58bcb23"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#aa5f1f6cbf78fc255d8a4ceaea58bcb23">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, std::nullptr_t value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1532</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a4dec02b60187e36214c20fea675a5b49"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a4dec02b60187e36214c20fea675a5b49">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, double value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1527</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_aa5f1f6cbf78fc255d8a4ceaea58bcb23"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#aa5f1f6cbf78fc255d8a4ceaea58bcb23">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, std::nullptr_t value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1531</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_ae11428ea0edc6ed08b0c33418052986c"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#ae11428ea0edc6ed08b0c33418052986c">tvm::runtime::TVMPODValue_::ptr</a></div><div class="ttdeci">T * ptr() const</div><div class="ttdoc">return handle as specific pointer type. </div><div class="ttdef"><b>Definition:</b> packed_func.h:617</div></div>
<div class="ttc" id="namespacetvm_html_a7c2095aed90b2129ba631b90103313a2"><div class="ttname"><a href="namespacetvm.html#a7c2095aed90b2129ba631b90103313a2">tvm::Device</a></div><div class="ttdeci">DLDevice Device</div><div class="ttdef"><b>Definition:</b> ndarray.h:43</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793a9387f774bc8453afe4aa4cd17789a405"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793a9387f774bc8453afe4aa4cd17789a405">kTVMOpaqueHandle</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:170</div></div>
@@ -189,7 +189,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a2b8fa6433efeccb77c9a1675ee7a3223"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a2b8fa6433efeccb77c9a1675ee7a3223">tvm::runtime::PackedFuncObj::TVM_DECLARE_FINAL_OBJECT_INFO</a></div><div class="ttdeci">TVM_DECLARE_FINAL_OBJECT_INFO(PackedFuncObj, Object)</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncSubObj_html_a969aa766a25d7e9091e08b3a8e1ea974"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncSubObj.html#a969aa766a25d7e9091e08b3a8e1ea974">tvm::runtime::PackedFuncSubObj::callable_</a></div><div class="ttdeci">TStorage callable_</div><div class="ttdoc">Type-erased filed for storing callable object. </div><div class="ttdef"><b>Definition:</b> packed_func.h:127</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_html_aebb30723fbc8a9530855dfd4f6185e89"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker.html#aebb30723fbc8a9530855dfd4f6185e89">tvm::runtime::ObjectTypeChecker::CheckAndGetMismatch</a></div><div class="ttdeci">static Optional< String > CheckAndGetMismatch(const Object *ptr)</div><div class="ttdoc">Check if an object matches the template type and return the mismatched type if it exists...</div><div [...]
-<div class="ttc" id="classtvm_1_1runtime_1_1String_html_a2ee7733b1c8092383ffab8c67bf8cb20"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html#a2ee7733b1c8092383ffab8c67bf8cb20">tvm::runtime::String::CanConvertFrom</a></div><div class="ttdeci">static bool CanConvertFrom(const TVMArgValue &val)</div><div class="ttdoc">Check if a TVMArgValue can be converted to String, i.e. it can be std::string or String. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1973</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1String_html_a2ee7733b1c8092383ffab8c67bf8cb20"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html#a2ee7733b1c8092383ffab8c67bf8cb20">tvm::runtime::String::CanConvertFrom</a></div><div class="ttdeci">static bool CanConvertFrom(const TVMArgValue &val)</div><div class="ttdoc">Check if a TVMArgValue can be converted to String, i.e. it can be std::string or String. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1972</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></div><div class="ttdoc">Base class of all object reference. </div><div class="ttdef"><b>Definition:</b> object.h:511</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ModuleNode_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ModuleNode.html">tvm::runtime::ModuleNode</a></div><div class="ttdoc">Base container of module. </div><div class="ttdef"><b>Definition:</b> module.h:113</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_ae5f18a03762f4e3e347b624140774855"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#ae5f18a03762f4e3e347b624140774855">tvm::runtime::PackedFuncObj::CallPacked</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void CallPacked(TVMArgs args, TVMRetValue *rv) const</div><div class="ttdoc">Call the function in packed format. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1216</div></div>
@@ -200,9 +200,9 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_ad362b734db5406b02e72476b7f8da779"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#ad362b734db5406b02e72476b7f8da779">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(int64_t value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:874</div></div>
<div class="ttc" id="object_8h_html"><div class="ttname"><a href="object_8h.html">object.h</a></div><div class="ttdoc">A managed object in the TVM runtime. </div></div>
<div class="ttc" id="data__type_8h_html"><div class="ttname"><a href="data__type_8h.html">data_type.h</a></div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_af0f7e76657fd06170c6347f47a42a342"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#af0f7e76657fd06170c6347f47a42a342">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TVMArgValue &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1536</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_af0f7e76657fd06170c6347f47a42a342"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#af0f7e76657fd06170c6347f47a42a342">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TVMArgValue &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1535</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1NDArray_html_a141e032d848c60f8261046304bdc8c4c"><div class="ttname"><a href="classtvm_1_1runtime_1_1NDArray.html#a141e032d848c60f8261046304bdc8c4c">tvm::runtime::NDArray::FFIGetHandle</a></div><div class="ttdeci">static TVMArrayHandle FFIGetHandle(const ObjectRef &nd)</div><div class="ttdoc">Get FFI Array handle from ndarray. </div><div class="ttdef"><b>Definition:</b> ndarray.h:430</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a46970e7b592c6bc08278ba7774ceb3be"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a46970e7b592c6bc08278ba7774ceb3be">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">void operator()(size_t i, const TVMRetValue &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1576</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a46970e7b592c6bc08278ba7774ceb3be"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a46970e7b592c6bc08278ba7774ceb3be">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">void operator()(size_t i, const TVMRetValue &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1575</div></div>
<div class="ttc" id="runtime_2module_8h_html"><div class="ttname"><a href="runtime_2module_8h.html">module.h</a></div><div class="ttdoc">Runtime container of the functions generated by TVM, This is used to support dynamically link...</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_a0e4a4d01d86eca79c5d9e1e90322c5cb"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a0e4a4d01d86eca79c5d9e1e90322c5cb">tvm::runtime::TypedPackedFunc< R(Args...)>::operator==</a></div><div class="ttdeci">bool operator==(std::nullptr_t null) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:360</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Module_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html">tvm::runtime::Module</a></div><div class="ttdoc">Module container of TVM. </div><div class="ttdef"><b>Definition:</b> module.h:50</div></div>
@@ -211,7 +211,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html_a817ba6c23b7ee1821c48a75edf255a30"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">tvm::runtime::Object::TypeIndex2Key</a></div><div class="ttdeci">static std::string TypeIndex2Key(uint32_t tindex)</div><div class="ttdoc">Get the type key of the corresponding index from runtime. </div></div>
<div class="ttc" id="namespacetvm_html_a0da40d3e210aa3b38a17982a7b7866b8"><div class="ttname"><a href="namespacetvm.html#a0da40d3e210aa3b38a17982a7b7866b8">tvm::ret</a></div><div class="ttdeci">PrimExpr ret(PrimExpr value, Span span=Span())</div><div class="ttdoc">Return the value. </div></div>
<div class="ttc" id="map_8h_html"><div class="ttname"><a href="map_8h.html">map.h</a></div><div class="ttdoc">Runtime Map container types. </div></div>
-<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4_html_a1d57124f26aeed2583d3ae24226d89c7"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4.html#a1d57124f26aeed2583d3ae24226d89c7">tvm::runtime::PackedFuncValueConverter<::tvm::runtime::String >::From</a></div><div class="ttdeci">static String From(const TVMArgValue &val)</div><div class="ttdef"><b>Definition:</b> [...]
+<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4_html_a1d57124f26aeed2583d3ae24226d89c7"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4.html#a1d57124f26aeed2583d3ae24226d89c7">tvm::runtime::PackedFuncValueConverter<::tvm::runtime::String >::From</a></div><div class="ttdeci">static String From(const TVMArgValue &val)</div><div class="ttdef"><b>Definition:</b> [...]
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Map_3_01K_00_01V_01_4_01_4_html_a9cb994fc6604ad2c287d9e824e67d2e2"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Map_3_01K_00_01V_01_4_01_4.html#a9cb994fc6604ad2c287d9e824e67d2e2">tvm::runtime::ObjectTypeChecker< Map< K, V > >::TypeName</a></div><div class="ttdeci">static std::string TypeName()</div><div class="ttdef"><b>Definition:</b> packed_func.h:531</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793ada22c3d9c62fa8f40d46e80ce83b96a1"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793ada22c3d9c62fa8f40d46e80ce83b96a1">kTVMNullptr</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:171</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_aefca71073146f4be36d6a4a0de33d6e0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#aefca71073146f4be36d6a4a0de33d6e0">tvm::runtime::TVMPODValue_::type_code</a></div><div class="ttdeci">int type_code() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:610</div></div>
@@ -221,11 +221,11 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1Optional_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Optional.html">tvm::runtime::Optional</a></div><div class="ttdoc">Optional container that to represent to a Nullable variant of T. </div><div class="ttdef"><b>Definition:</b> optional.h:51</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgValue_html_a2cf7efec615ddde3c278e85f8c283faf"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgValue.html#a2cf7efec615ddde3c278e85f8c283faf">tvm::runtime::TVMArgValue::value</a></div><div class="ttdeci">const TVMValue & value() const</div><div class="ttdef"><b>Definition:</b> packed_func.h:691</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a3e7898a2ba34f7f171093e217edee131"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a3e7898a2ba34f7f171093e217edee131">tvm::runtime::PackedFuncObj::f_call_packed_</a></div><div class="ttdeci">FCallPacked * f_call_packed_</div><div class="ttdoc">Internal callable function pointer used to call the packed function. </div><div class="ttdef"><b>Definition:</b> packed_func.h:109</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html_a71c712200306656ffdca92629b8172bc"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html#a71c712200306656ffdca92629b8172bc">tvm::runtime::PackedFunc::operator()</a></div><div class="ttdeci">TVMRetValue operator()(Args &&... args) const</div><div class="ttdoc">Call packed function by directly passing in unpacked format. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1610</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1PackedFunc_html_a71c712200306656ffdca92629b8172bc"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFunc.html#a71c712200306656ffdca92629b8172bc">tvm::runtime::PackedFunc::operator()</a></div><div class="ttdeci">TVMRetValue operator()(Args &&... args) const</div><div class="ttdoc">Call packed function by directly passing in unpacked format. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1609</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a8c162670ce34f10ca3dac0b1bbb59292"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a8c162670ce34f10ca3dac0b1bbb59292">tvm::runtime::PackedFuncObj::PackedFuncObj</a></div><div class="ttdeci">PackedFuncObj()=delete</div><div class="ttdoc">Delete the default constructor explicitly. </div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1514</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html">tvm::runtime::TVMArgsSetter</a></div><div class="ttdef"><b>Definition:</b> packed_func.h:1513</div></div>
<div class="ttc" id="namespacetvm_html_aae7034e3e41c18e7fb78ff32bfc6a318"><div class="ttname"><a href="namespacetvm.html#aae7034e3e41c18e7fb78ff32bfc6a318">tvm::NullOpt</a></div><div class="ttdeci">constexpr runtime::NullOptType NullOpt</div><div class="ttdef"><b>Definition:</b> optional.h:160</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a5882f7eda112e825eb5a87e45aeb85b0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a5882f7eda112e825eb5a87e45aeb85b0">tvm::runtime::TVMArgsSetter::TVMArgsSetter</a></div><div class="ttdeci">TVMArgsSetter(TVMValue *values, int *type_codes)</div><div class="ttdef"><b>Definition:</b> packed_func.h:1516</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a5882f7eda112e825eb5a87e45aeb85b0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a5882f7eda112e825eb5a87e45aeb85b0">tvm::runtime::TVMArgsSetter::TVMArgsSetter</a></div><div class="ttdeci">TVMArgsSetter(TVMValue *values, int *type_codes)</div><div class="ttdef"><b>Definition:</b> packed_func.h:1515</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncObj_html_a6a6763ef1b5df7a9afc44733f02e2f30"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncObj.html#a6a6763ef1b5df7a9afc44733f02e2f30">tvm::runtime::PackedFuncObj::_type_key</a></div><div class="ttdeci">static constexpr const char * _type_key</div><div class="ttdef"><b>Definition:</b> packed_func.h:78</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncSubObj_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncSubObj.html">tvm::runtime::PackedFuncSubObj</a></div><div class="ttdoc">Derived object class for constructing PackedFuncObj. </div><div class="ttdef"><b>Definition:</b> packed_func.h:114</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_af45a2ceff92e6f6c394ea766a45027a0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#af45a2ceff92e6f6c394ea766a45027a0">tvm::runtime::TypedPackedFunc< R(Args...)>::TypedPackedFunc</a></div><div class="ttdeci">TypedPackedFunc(std::nullptr_t null)</div><div class="ttdoc">constructor from null </div><div class="ttdef"><b>Definition:</b> packed_func.h: [...]
@@ -236,14 +236,14 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgValue_html_a5fbd71750e5bbba6edc9094178af9276"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgValue.html#a5fbd71750e5bbba6edc9094178af9276">tvm::runtime::TVMArgValue::TVMArgValue</a></div><div class="ttdeci">TVMArgValue(TVMValue value, int type_code)</div><div class="ttdoc">constructor </div><div class="ttdef"><b>Definition:</b> packed_func.h:655</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_ac87c22e4d49e79ce5b36b3aead667fcb"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#ac87c22e4d49e79ce5b36b3aead667fcb">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(const TVMRetValue &other)</div><div class="ttdef"><b>Definition:</b> packed_func.h:932</div></div>
<div class="ttc" id="packed__func_8h_html_ad1e150bb815d5cb964e15d4fa7b5fd93"><div class="ttname"><a href="packed__func_8h.html#ad1e150bb815d5cb964e15d4fa7b5fd93">TVM_CHECK_TYPE_CODE</a></div><div class="ttdeci">#define TVM_CHECK_TYPE_CODE(CODE, T)</div><div class="ttdef"><b>Definition:</b> packed_func.h:422</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a848a0affc4656f2691711543d10704e2"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a848a0affc4656f2691711543d10704e2">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, void *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1540</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a848a0affc4656f2691711543d10704e2"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a848a0affc4656f2691711543d10704e2">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, void *value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1539</div></div>
<div class="ttc" id="namespacetvm_1_1runtime_html_a28022a2dc86007a65b24b8c41e0c7da3"><div class="ttname"><a href="namespacetvm_1_1runtime.html#a28022a2dc86007a65b24b8c41e0c7da3">tvm::runtime::FSig</a></div><div class="ttdeci">std::string() FSig</div><div class="ttdoc">Using static function to output TypedPackedFunc signature. </div><div class="ttdef"><b>Definition:</b> packed_func.h:186</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793a4b2f3688d719f6e7c20ab00659e2383e"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793a4b2f3688d719f6e7c20ab00659e2383e">kTVMBytes</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:179</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1PackedFuncSubObj_html_a2c5d6759714a3674b36bfd64a9f38992"><div class="ttname"><a href="classtvm_1_1runtime_1_1PackedFuncSubObj.html#a2c5d6759714a3674b36bfd64a9f38992">tvm::runtime::PackedFuncSubObj::PackedFuncSubObj</a></div><div class="ttdeci">PackedFuncSubObj(TCallable callable)</div><div class="ttdoc">Derived object class for constructing PackedFuncObj. </div><div class="ttdef"><b>Definition:</b> packed_func.h:124</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a400ab1f50cbbbc1ab24975bf32556d16"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a400ab1f50cbbbc1ab24975bf32556d16">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(std::nullptr_t value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:864</div></div>
<div class="ttc" id="c__runtime__api_8h_html"><div class="ttname"><a href="c__runtime__api_8h.html">c_runtime_api.h</a></div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Array_3_01T_01_4_01_4_html_aecb7f71a675e74979a0ed08202cf09cc"><div class="ttname"><a href="structtvm_1_1runtime_1_1ObjectTypeChecker_3_01Array_3_01T_01_4_01_4.html#aecb7f71a675e74979a0ed08202cf09cc">tvm::runtime::ObjectTypeChecker< Array< T > >::CheckAndGetMismatch</a></div><div class="ttdeci">static Optional< String > CheckAndGetMismatch(const Object *ptr)</div><div class="ttdef"><b>Definition:</b> pack [...]
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="c__runtime__api_8h_html_a190e81769e805cca153514137a66e793af2b95de1a09ed39055edfe8ef5ea484d"><div class="ttname"><a href="c__runtime__api_8h.html#a190e81769e805cca153514137a66e793af2b95de1a09ed39055edfe8ef5ea484d">kTVMStr</a></div><div class="ttdef"><b>Definition:</b> c_runtime_api.h:178</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_afe5a60e856a30894e795d5230b0a7022"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#afe5a60e856a30894e795d5230b0a7022">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(NDArray other)</div><div class="ttdef"><b>Definition:</b> packed_func.h:908</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1PackedFuncValueConverter_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1PackedFuncValueConverter.html">tvm::runtime::PackedFuncValueConverter</a></div><div class="ttdoc">Type trait to specify special value conversion rules from TVMArgValue and TVMRetValue. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1096</div></div>
@@ -253,8 +253,8 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4_html_a4abadc6786dd14a3aed6e2b5b342d1d6"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a4abadc6786dd14a3aed6e2b5b342d1d6">tvm::runtime::TypedPackedFunc< R(Args...)>::TypedPackedFunc</a></div><div class="ttdeci">TypedPackedFunc()</div><div class="ttdoc">default constructor </div><div class="ttdef"><b>Definition:</b> packed_func.h:232</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMMovableArgValueWithContext___html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMMovableArgValueWithContext__.html">tvm::runtime::TVMMovableArgValueWithContext_</a></div><div class="ttdoc">Internal auxiliary struct for TypedPackedFunc to indicate a movable argument with additional context ...</div><div class="ttdef"><b>Definition:</b> packed_func.h:754</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMRetValue_html_a7c16ff5c118b1577a9188ca3f3509167"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMRetValue.html#a7c16ff5c118b1577a9188ca3f3509167">tvm::runtime::TVMRetValue::operator=</a></div><div class="ttdeci">TVMRetValue & operator=(void *value)</div><div class="ttdef"><b>Definition:</b> packed_func.h:869</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a3240122354ebaaa28047ef9ab6f0cd82"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a3240122354ebaaa28047ef9ab6f0cd82">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TypedPackedFunc< FType > &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1573</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ae426f535e03a43ef940c8c14a95625e0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ae426f535e03a43ef940c8c14a95625e0">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DLDataType value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1552</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_a3240122354ebaaa28047ef9ab6f0cd82"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#a3240122354ebaaa28047ef9ab6f0cd82">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, const TypedPackedFunc< FType > &value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1572</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1TVMArgsSetter_html_ae426f535e03a43ef940c8c14a95625e0"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMArgsSetter.html#ae426f535e03a43ef940c8c14a95625e0">tvm::runtime::TVMArgsSetter::operator()</a></div><div class="ttdeci">TVM_ALWAYS_INLINE void operator()(size_t i, DLDataType value) const</div><div class="ttdef"><b>Definition:</b> packed_func.h:1551</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TVMPODValue___html_a2f46b59a6c1d5eb4575d7f583b5f1a0c"><div class="ttname"><a href="classtvm_1_1runtime_1_1TVMPODValue__.html#a2f46b59a6c1d5eb4575d7f583b5f1a0c">tvm::runtime::TVMPODValue_::TVMPODValue_</a></div><div class="ttdeci">TVMPODValue_()</div><div class="ttdef"><b>Definition:</b> packed_func.h:631</div></div>
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diff --git a/docs/reference/api/doxygen/reduction_8h_source.html b/docs/reference/api/doxygen/reduction_8h_source.html
index bca69da88e..0313e6056e 100644
--- a/docs/reference/api/doxygen/reduction_8h_source.html
+++ b/docs/reference/api/doxygen/reduction_8h_source.html
@@ -80,7 +80,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1topi_html_a12a94f9c1103f5e05fb9819e7176bf4c"><div class="ttname"><a href="namespacetvm_1_1topi.html#a12a94f9c1103f5e05fb9819e7176bf4c">tvm::topi::MakeTupleSumReducer</a></div><div class="ttdeci">FCommReduce MakeTupleSumReducer()</div><div class="ttdoc">Create communitive reducer summing over tuples. </div><div class="ttdef"><b>Definition:</b> reduction.h:576</div></div>
<div class="ttc" id="namespacetvm_html_a3b37fa55ea93d6868751a2441996b072"><div class="ttname"><a href="namespacetvm.html#a3b37fa55ea93d6868751a2441996b072">tvm::min_value</a></div><div class="ttdeci">PrimExpr min_value(const DataType &dtype, Span span=Span())</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a4b434e701bc9835e2a7de8f0fadebea5"><div class="ttname"><a href="namespacetvm_1_1topi.html#a4b434e701bc9835e2a7de8f0fadebea5">tvm::topi::MakeArgmaxReducer</a></div><div class="ttdeci">FCommReduce MakeArgmaxReducer(bool select_last_index=false)</div><div class="ttdef"><b>Definition:</b> reduction.h:495</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_ae488679377c78cd5411b7df11c297673"><div class="ttname"><a href="namespacetvm_1_1topi.html#ae488679377c78cd5411b7df11c297673">tvm::topi::min</a></div><div class="ttdeci">Tensor min(const Tensor &data, const Array< Integer > &axis, bool keepdims=false, bool atleast1d=false)</div><div class="ttdoc">Creates an operation that finds the minimum of elements over a given axis. </div><div class="ttdef"><b>Definition:</b> reduction.h:410 [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
diff --git a/docs/reference/api/doxygen/runtime_2module_8h_source.html b/docs/reference/api/doxygen/runtime_2module_8h_source.html
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@@ -68,7 +68,7 @@ $(function() {
<div class="contents">
<a href="runtime_2module_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or [...]
<div class="ttc" id="namespacetvm_1_1runtime_1_1symbol_html_aaad9cf8f51a55b2ec5b19854d692bd21"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1symbol.html#aaad9cf8f51a55b2ec5b19854d692bd21">tvm::runtime::symbol::tvm_set_device</a></div><div class="ttdeci">constexpr const char * tvm_set_device</div><div class="ttdoc">global function to set device </div><div class="ttdef"><b>Definition:</b> module.h:259</div></div>
-<div class="ttc" id="classtvm_1_1runtime_1_1Module_html_a1233f7b896bb299ef07f9e41a4ffdc17"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html#a1233f7b896bb299ef07f9e41a4ffdc17">tvm::runtime::Module::GetFunction</a></div><div class="ttdeci">PackedFunc GetFunction(const std::string &name, bool query_imports=false)</div><div class="ttdoc">Get packed function from current module by name. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1937</div></div>
+<div class="ttc" id="classtvm_1_1runtime_1_1Module_html_a1233f7b896bb299ef07f9e41a4ffdc17"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html#a1233f7b896bb299ef07f9e41a4ffdc17">tvm::runtime::Module::GetFunction</a></div><div class="ttdeci">PackedFunc GetFunction(const std::string &name, bool query_imports=false)</div><div class="ttdoc">Get packed function from current module by name. </div><div class="ttdef"><b>Definition:</b> packed_func.h:1936</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Module_html_afb5a6c9b0e0a541245958456ebe39260"><div class="ttname"><a href="classtvm_1_1runtime_1_1Module.html#afb5a6c9b0e0a541245958456ebe39260">tvm::runtime::Module::Import</a></div><div class="ttdeci">void Import(Module other)</div><div class="ttdoc">Import another module into this module. </div><div class="ttdef"><b>Definition:</b> module.h:276</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectPtr_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectPtr.html">tvm::runtime::ObjectPtr</a></div><div class="ttdoc">A custom smart pointer for Object. </div><div class="ttdef"><b>Definition:</b> object.h:358</div></div>
<div class="ttc" id="structtvm_1_1runtime_1_1TypeIndex_html_aed93c7318efc8052201d4c404b21a40da8ce1dbb49ce074502049c6909061a2ae"><div class="ttname"><a href="structtvm_1_1runtime_1_1TypeIndex.html#aed93c7318efc8052201d4c404b21a40da8ce1dbb49ce074502049c6909061a2ae">tvm::runtime::TypeIndex::kRuntimeModule</a></div><div class="ttdoc">runtime::Module. </div><div class="ttdef"><b>Definition:</b> object.h:62</div></div>
diff --git a/docs/reference/api/doxygen/stmt_8h_source.html b/docs/reference/api/doxygen/stmt_8h_source.html
index 4d603f82f0..75cac45786 100644
--- a/docs/reference/api/doxygen/stmt_8h_source.html
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@@ -66,7 +66,7 @@ $(function() {
<div class="title">stmt.h</div> </div>
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<div class="contents">
-<a href="stmt_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more contri [...]
+<a href="stmt_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more contri [...]
<div class="ttc" id="classtvm_1_1tir_1_1WhileNode_html_ae897db210a499a29a66aef4eaafcd043"><div class="ttname"><a href="classtvm_1_1tir_1_1WhileNode.html#ae897db210a499a29a66aef4eaafcd043">tvm::tir::WhileNode::SEqualReduce</a></div><div class="ttdeci">bool SEqualReduce(const WhileNode *other, SEqualReducer equal) const</div><div class="ttdef"><b>Definition:</b> stmt.h:1045</div></div>
<div class="ttc" id="namespacetvm_1_1tir_1_1attr_html_a2823f2e8c3ae9eec6c8f797752d1f9b5"><div class="ttname"><a href="namespacetvm_1_1tir_1_1attr.html#a2823f2e8c3ae9eec6c8f797752d1f9b5">tvm::tir::attr::pragma_import_c</a></div><div class="ttdeci">constexpr const char * pragma_import_c</div><div class="ttdoc">Import C source or file into the final code gen module. </div><div class="ttdef"><b>Definition:</b> stmt.h:1417</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Store_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Store.html">tvm::tir::Store</a></div><div class="ttdoc">Managed reference to StoreNode. </div><div class="ttdef"><b>Definition:</b> stmt.h:271</div></div>
diff --git a/docs/reference/api/doxygen/stmt__functor_8h_source.html b/docs/reference/api/doxygen/stmt__functor_8h_source.html
index 343cff19e3..c6a856ed80 100644
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@@ -66,7 +66,7 @@ $(function() {
<div class="title">stmt_functor.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="stmt__functor_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or mo [...]
+<a href="stmt__functor_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or mo [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a980c3e5119d1898c9c9a3f5003428aef"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a980c3e5119d1898c9c9a3f5003428aef">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const LetStmtNode *op, Args... args)</div><div class="ttdef"><b [...]
<div class="ttc" id="classtvm_1_1NodeFunctor_html"><div class="ttname"><a href="classtvm_1_1NodeFunctor.html">tvm::NodeFunctor</a></div><div class="ttdoc">A dynamically dispatched functor on the type of the first argument. </div><div class="ttdef"><b>Definition:</b> functor.h:64</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1AttrStmtNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1AttrStmtNode.html">tvm::tir::AttrStmtNode</a></div><div class="ttdoc">Define certain auxiliary attribute for the body to be a symbolic value. This provide auxiliary inform...</div><div class="ttdef"><b>Definition:</b> stmt.h:118</div></div>
@@ -74,30 +74,30 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1PrefetchNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1PrefetchNode.html">tvm::tir::PrefetchNode</a></div><div class="ttdoc">A prefetch hint for a buffer. </div><div class="ttdef"><b>Definition:</b> stmt.h:1073</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1DeclBufferNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1DeclBufferNode.html">tvm::tir::DeclBufferNode</a></div><div class="ttdoc">Declare a buffer that can be used in the body. </div><div class="ttdef"><b>Definition:</b> stmt.h:692</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a58c46e1656ae602ceec742dce4173d13"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a58c46e1656ae602ceec742dce4173d13">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const SeqStmtNode *op, Args... args)</div><div class="ttdef"><b [...]
-<div class="ttc" id="classtvm_1_1tir_1_1StmtExprVisitor_html_a21d7f30350a7aa02cdc0c1b5ee3ffa23"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprVisitor.html#a21d7f30350a7aa02cdc0c1b5ee3ffa23">tvm::tir::StmtExprVisitor::VisitExpr</a></div><div class="ttdeci">void VisitExpr(const PrimExpr &e) override</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:309</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtExprVisitor_html_a21d7f30350a7aa02cdc0c1b5ee3ffa23"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprVisitor.html#a21d7f30350a7aa02cdc0c1b5ee3ffa23">tvm::tir::StmtExprVisitor::VisitExpr</a></div><div class="ttdeci">void VisitExpr(const PrimExpr &e) override</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:308</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectPtr_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectPtr.html">tvm::runtime::ObjectPtr</a></div><div class="ttdoc">A custom smart pointer for Object. </div><div class="ttdef"><b>Definition:</b> object.h:358</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html">tvm::tir::StmtMutator</a></div><div class="ttdoc">StmtMutator that mutates the statements. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:181</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html">tvm::tir::StmtMutator</a></div><div class="ttdoc">StmtMutator that mutates the statements. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:180</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1BlockRealizeNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1BlockRealizeNode.html">tvm::tir::BlockRealizeNode</a></div><div class="ttdoc">A block realization node represents execution of the block at the binding values. ...</div><div class="ttdef"><b>Definition:</b> stmt.h:1325</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_ad7864f64476c846a8023fdba1188b74e"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#ad7864f64476c846a8023fdba1188b74e">tvm::tir::StmtMutator::VisitExpr</a></div><div class="ttdeci">virtual PrimExpr VisitExpr(const PrimExpr &e)</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:257</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprVisitor.html">tvm::tir::StmtExprVisitor</a></div><div class="ttdoc">Visitor that recursively visit stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:300</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_ad7864f64476c846a8023fdba1188b74e"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#ad7864f64476c846a8023fdba1188b74e">tvm::tir::StmtMutator::VisitExpr</a></div><div class="ttdeci">virtual PrimExpr VisitExpr(const PrimExpr &e)</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:256</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprVisitor.html">tvm::tir::StmtExprVisitor</a></div><div class="ttdoc">Visitor that recursively visit stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:299</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a4fb668de3afc283b2a5ea43e3918a0ac"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a4fb668de3afc283b2a5ea43e3918a0ac">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const WhileNode *op, Args... args)</div><div class="ttdef"><b>D [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_ac6b5c52ec5af7c3a0e5bae3943afdfb9"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#ac6b5c52ec5af7c3a0e5bae3943afdfb9">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const AssertStmtNode *op, Args... args)</div><div class="ttdef" [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_ab10dd3ea7414d0c6c415857be5b5ad7b"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#ab10dd3ea7414d0c6c415857be5b5ad7b">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const AllocateConstNode *op, Args... args)</div><div class="ttd [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1ExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprVisitor.html">tvm::tir::ExprVisitor</a></div><div class="ttdoc">ExprVisitor. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:209</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtVisitor_html_a6d35a6081ee7dbc440e5a980f70795c6"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtVisitor.html#a6d35a6081ee7dbc440e5a980f70795c6">tvm::tir::StmtVisitor::VisitExpr</a></div><div class="ttdeci">virtual void VisitExpr(const PrimExpr &e)</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:155</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1ExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprVisitor.html">tvm::tir::ExprVisitor</a></div><div class="ttdoc">ExprVisitor. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:208</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtVisitor_html_a6d35a6081ee7dbc440e5a980f70795c6"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtVisitor.html#a6d35a6081ee7dbc440e5a980f70795c6">tvm::tir::StmtVisitor::VisitExpr</a></div><div class="ttdeci">virtual void VisitExpr(const PrimExpr &e)</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:154</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1SeqStmtNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1SeqStmtNode.html">tvm::tir::SeqStmtNode</a></div><div class="ttdoc">The container of seq statement. Represent a sequence of statements. </div><div class="ttdef"><b>Definition:</b> stmt.h:730</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Var_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Var.html">tvm::tir::Var</a></div><div class="ttdoc">a named variable in TIR </div><div class="ttdef"><b>Definition:</b> var.h:88</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1IfThenElseNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1IfThenElseNode.html">tvm::tir::IfThenElseNode</a></div><div class="ttdoc">IfThenElse statment. </div><div class="ttdef"><b>Definition:</b> stmt.h:828</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html_afc4dedb17cb5f2057fc8200e6c298fab"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html#afc4dedb17cb5f2057fc8200e6c298fab">tvm::tir::StmtExprMutator::VisitExpr</a></div><div class="ttdeci">PrimExpr VisitExpr(const PrimExpr &e) override</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:324</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html_afc4dedb17cb5f2057fc8200e6c298fab"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html#afc4dedb17cb5f2057fc8200e6c298fab">tvm::tir::StmtExprMutator::VisitExpr</a></div><div class="ttdeci">PrimExpr VisitExpr(const PrimExpr &e) override</div><div class="ttdoc">Visitor to Exprs, can be overriden to do recursive changes to Exprs. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:323</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor.html">tvm::tir::StmtFunctor</a></div><div class="ttdoc">Same as ExprFunctor except it is applied on statements. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:46</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a19b12318a9d3cc9cc24786f672d22263"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a19b12318a9d3cc9cc24786f672d22263">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::~StmtFunctor</a></div><div class="ttdeci">virtual ~StmtFunctor()</div><div class="ttdoc">virtual destructor </div><div class [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a7cf9c16fc8435bee82a8d584afda407c"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a7cf9c16fc8435bee82a8d584afda407c">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const StoreNode *op, Args... args)</div><div class="ttdef"><b>D [...]
<div class="ttc" id="tir_2function_8h_html"><div class="ttname"><a href="tir_2function_8h.html">function.h</a></div><div class="ttdoc">TIR Function. </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></div><div class="ttdoc">base class of all object containers. </div><div class="ttdef"><b>Definition:</b> object.h:167</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a18e378023df3122893ffaf50bb89464e"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a18e378023df3122893ffaf50bb89464e">tvm::tir::StmtMutator::operator()</a></div><div class="ttdeci">Stmt operator()(Stmt stmt)</div><div class="ttdoc">Mutate stmt. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:191</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a18e378023df3122893ffaf50bb89464e"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a18e378023df3122893ffaf50bb89464e">tvm::tir::StmtMutator::operator()</a></div><div class="ttdeci">Stmt operator()(Stmt stmt)</div><div class="ttdoc">Mutate stmt. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:190</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a4b5067fa233d111c9db9cc402ed599c3"><div class="ttname"><a href="namespacetvm_1_1tir.html#a4b5067fa233d111c9db9cc402ed599c3">tvm::tir::PostOrderVisit</a></div><div class="ttdeci">void PostOrderVisit(const ObjectRef &node, std::function< void(const ObjectRef &)> fvisit)</div><div class="ttdoc">Recursively visit the ir in post DFS order node, apply fvisit Each node is guaranteed to be visited o...</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a4306d1beba05fa1ac582503498a6d7ce"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a4306d1beba05fa1ac582503498a6d7ce">tvm::tir::StmtMutator::VisitStmt</a></div><div class="ttdeci">Stmt VisitStmt(const Stmt &stmt) override</div><div class="ttdoc">Internal mutator that everyone calls. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:240</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a4306d1beba05fa1ac582503498a6d7ce"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a4306d1beba05fa1ac582503498a6d7ce">tvm::tir::StmtMutator::VisitStmt</a></div><div class="ttdeci">Stmt VisitStmt(const Stmt &stmt) override</div><div class="ttdoc">Internal mutator that everyone calls. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:239</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a2e639c81d1c6875ead7764ab8a7cd553"><div class="ttname"><a href="namespacetvm_1_1tir.html#a2e639c81d1c6875ead7764ab8a7cd553">tvm::tir::RenewDefs</a></div><div class="ttdeci">PrimFunc RenewDefs(const PrimFunc &func)</div><div class="ttdoc">Renew the definition nodes for a TIR, including Var, Buffer and IterVar. This pass works as a simple ...</div></div>
<div class="ttc" id="stmt__functor_8h_html_a57fa0234da58c69003bb980f5405a279"><div class="ttname"><a href="stmt__functor_8h.html#a57fa0234da58c69003bb980f5405a279">IR_STMT_FUNCTOR_DISPATCH</a></div><div class="ttdeci">#define IR_STMT_FUNCTOR_DISPATCH(OP)</div><div class="ttdef"><b>Definition:</b> stmt_functor.h:51</div></div>
<div class="ttc" id="tir_2expr__functor_8h_html"><div class="ttname"><a href="tir_2expr__functor_8h.html">expr_functor.h</a></div><div class="ttdoc">Functors for tir expressions. </div></div>
@@ -116,8 +116,8 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1Stmt_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Stmt.html">tvm::tir::Stmt</a></div><div class="ttdoc">Container of all statements. </div><div class="ttdef"><b>Definition:</b> stmt.h:57</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a82025a966ad57d3a52901f4657a89b70"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a82025a966ad57d3a52901f4657a89b70">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::result_type</a></div><div class="ttdeci">R result_type</div><div class="ttdoc">the result type of this functor </div><div cl [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a825decea3d6c614e64dc09f435db53b5"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a825decea3d6c614e64dc09f435db53b5">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const DeclBufferNode *op, Args... args)</div><div class="ttdef" [...]
-<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a8dfe0e96ba9d3b4cd08e57c20c1eb414"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a8dfe0e96ba9d3b4cd08e57c20c1eb414">tvm::tir::StmtMutator::CopyOnWrite</a></div><div class="ttdeci">ObjectPtr< TNode > CopyOnWrite(const TNode *node)</div><div class="ttdoc">Perform copy on write on node. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:218</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a2e86a6db6acc68d381d49df3e665415a"><div class="ttname"><a href="namespacetvm_1_1tir.html#a2e86a6db6acc68d381d49df3e665415a">tvm::tir::ContainsNode</a></div><div class="ttdeci">bool ContainsNode(const Stmt &stmt)</div><div class="ttdoc">Check if the statement contains the specified node type. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:468</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtMutator_html_a8dfe0e96ba9d3b4cd08e57c20c1eb414"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtMutator.html#a8dfe0e96ba9d3b4cd08e57c20c1eb414">tvm::tir::StmtMutator::CopyOnWrite</a></div><div class="ttdeci">ObjectPtr< TNode > CopyOnWrite(const TNode *node)</div><div class="ttdoc">Perform copy on write on node. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:217</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a2e86a6db6acc68d381d49df3e665415a"><div class="ttname"><a href="namespacetvm_1_1tir.html#a2e86a6db6acc68d381d49df3e665415a">tvm::tir::ContainsNode</a></div><div class="ttdeci">bool ContainsNode(const Stmt &stmt)</div><div class="ttdoc">Check if the statement contains the specified node type. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:467</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1AllocateNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1AllocateNode.html">tvm::tir::AllocateNode</a></div><div class="ttdoc">Allocate a buffer that can be used in body. </div><div class="ttdef"><b>Definition:</b> stmt.h:519</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1EvaluateNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1EvaluateNode.html">tvm::tir::EvaluateNode</a></div><div class="ttdoc">Evaluates an expression. This is mostly used for putting a Call node into Stmt. </div><div class="ttdef"><b>Definition:</b> stmt.h:878</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_a4e7cdb1574b93a59e784d70aa47b8da7"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#a4e7cdb1574b93a59e784d70aa47b8da7">tvm::runtime::ObjectRef::unique</a></div><div class="ttdeci">bool unique() const</div><div class="ttdef"><b>Definition:</b> object.h:550</div></div>
@@ -135,7 +135,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)></a></div><div class="ttdef"><b>Definition:</b> stmt_functor.h:57</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a5d6146f080b95f73d41be3a2af34c934"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a5d6146f080b95f73d41be3a2af34c934">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const IfThenElseNode *op, Args... args)</div><div class="ttdef" [...]
<div class="ttc" id="namespacetvm_1_1tir_html_a34ae87f765e4d8230e3572428cdbe3e1"><div class="ttname"><a href="namespacetvm_1_1tir.html#a34ae87f765e4d8230e3572428cdbe3e1">tvm::tir::Substitute</a></div><div class="ttdeci">Stmt Substitute(Stmt stmt, std::function< Optional< PrimExpr >(const Var &var)> vmap)</div><div class="ttdoc">Substitute the var specified by vmap. </div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html">tvm::tir::StmtExprMutator</a></div><div class="ttdoc">Mutator that recursively mutates stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:315</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtExprMutator.html">tvm::tir::StmtExprMutator</a></div><div class="ttdoc">Mutator that recursively mutates stmts and exprs on them. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:314</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1BufferStoreNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1BufferStoreNode.html">tvm::tir::BufferStoreNode</a></div><div class="ttdoc">Store value to the high dimension buffer. </div><div class="ttdef"><b>Definition:</b> stmt.h:290</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Map_html_a60c1dac32729c4bf8351972da11793e4"><div class="ttname"><a href="classtvm_1_1runtime_1_1Map.html#a60c1dac32729c4bf8351972da11793e4">tvm::runtime::Map::end</a></div><div class="ttdeci">iterator end() const</div><div class="ttdef"><b>Definition:</b> map.h:1381</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_afb4abf8cb69c4a9105eb38e262e96bc7"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#afb4abf8cb69c4a9105eb38e262e96bc7">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const BlockRealizeNode *op, Args... args)</div><div class="ttde [...]
@@ -152,13 +152,13 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a087e79365d118d2de27a8616939e0d55"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a087e79365d118d2de27a8616939e0d55">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const BufferStoreNode *op, Args... args)</div><div class="ttdef [...]
<div class="ttc" id="classtvm_1_1tir_1_1LetStmtNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1LetStmtNode.html">tvm::tir::LetStmtNode</a></div><div class="ttdoc">Let binding, bind var to value, then run body. </div><div class="ttdef"><b>Definition:</b> stmt.h:65</div></div>
<div class="ttc" id="classtvm_1_1PrimExpr_html"><div class="ttname"><a href="classtvm_1_1PrimExpr.html">tvm::PrimExpr</a></div><div class="ttdoc">Reference to PrimExprNode. </div><div class="ttdef"><b>Definition:</b> expr.h:112</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1StmtVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtVisitor.html">tvm::tir::StmtVisitor</a></div><div class="ttdoc">StmtVisitor. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:142</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1StmtVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtVisitor.html">tvm::tir::StmtVisitor</a></div><div class="ttdoc">StmtVisitor. </div><div class="ttdef"><b>Definition:</b> stmt_functor.h:141</div></div>
<div class="ttc" id="namespacetvm_html_aae7034e3e41c18e7fb78ff32bfc6a318"><div class="ttname"><a href="namespacetvm.html#aae7034e3e41c18e7fb78ff32bfc6a318">tvm::NullOpt</a></div><div class="ttdeci">constexpr runtime::NullOptType NullOpt</div><div class="ttdef"><b>Definition:</b> optional.h:160</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1BufferRealizeNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1BufferRealizeNode.html">tvm::tir::BufferRealizeNode</a></div><div class="ttdoc">Annotate the region where the buffer need to be read and write in the body. We only need to allocate ...</div><div class="ttdef"><b>Definition:</b> stmt.h:345</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a5943b89b1ee4b775e84d71eb43055f48"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a5943b89b1ee4b775e84d71eb43055f48">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const EvaluateNode *op, Args... args)</div><div class="ttdef">< [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_ab3302cd65bf351550e383b0320fdb103"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#ab3302cd65bf351550e383b0320fdb103">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const BlockNode *op, Args... args)</div><div class="ttdef"><b>D [...]
<div class="ttc" id="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4_html_a3d1c16d316eac87f2dcaee67152bea84"><div class="ttname"><a href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#a3d1c16d316eac87f2dcaee67152bea84">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)>::VisitStmt_</a></div><div class="ttdeci">virtual R VisitStmt_(const AllocateNode *op, Args... args)</div><div class="ttdef">< [...]
-<div class="ttc" id="classtvm_1_1tir_1_1ExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprMutator.html">tvm::tir::ExprMutator</a></div><div class="ttdoc">ExprMutator that mutates expressions. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:256</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1ExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprMutator.html">tvm::tir::ExprMutator</a></div><div class="ttdoc">ExprMutator that mutates expressions. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:255</div></div>
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diff --git a/docs/reference/api/doxygen/strided__slice_8h_source.html b/docs/reference/api/doxygen/strided__slice_8h_source.html
index 90ac01e98d..22f13556aa 100644
--- a/docs/reference/api/doxygen/strided__slice_8h_source.html
+++ b/docs/reference/api/doxygen/strided__slice_8h_source.html
@@ -69,7 +69,7 @@ $(function() {
<a href="strided__slice_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or m [...]
<div class="ttc" id="namespacetvm_html_ab2a3c98ef29937defd6accb9b171a940"><div class="ttname"><a href="namespacetvm.html#ab2a3c98ef29937defd6accb9b171a940">tvm::abs</a></div><div class="ttdeci">PrimExpr abs(PrimExpr x, Span span=Span())</div><div class="ttdoc">Calculate absolute value of x. </div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_aff75b2e533b654909ca1bd9485ef4e6b"><div class="ttname"><a href="namespacetvm_1_1topi.html#aff75b2e533b654909ca1bd9485ef4e6b">tvm::topi::StridedSliceOutputShape</a></div><div class="ttdeci">Array< PrimExpr > StridedSliceOutputShape(const Array< PrimExpr > &ishape, const Array< Integer > &begin, const Array< Integer > &end, const Array< Integer > &strides, const Array< Integer > &axes, co [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Var_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Var.html">tvm::tir::Var</a></div><div class="ttdoc">a named variable in TIR </div><div class="ttdef"><b>Definition:</b> var.h:88</div></div>
@@ -80,7 +80,7 @@ $(function() {
<div class="ttc" id="tir_2expr_8h_html"><div class="ttname"><a href="tir_2expr_8h.html">expr.h</a></div><div class="ttdoc">TIR expressions. </div></div>
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a7da4c96db87c1459a2b097b87afd811f"><div class="ttname"><a href="namespacetvm_1_1topi.html#a7da4c96db87c1459a2b097b87afd811f">tvm::topi::cast</a></div><div class="ttdeci">Tensor cast(const Tensor &x, DataType type, std::string name="T_cast", std::string tag=kElementWise)</div><div class="ttdoc">Cast each element of x to the given type. If expr is scalar and type is a corresponding vector type...</div><div class="ttdef"><b>Defini [...]
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
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diff --git a/docs/reference/api/doxygen/tir_2expr__functor_8h_source.html b/docs/reference/api/doxygen/tir_2expr__functor_8h_source.html
index 7418bbc05f..3eb5e291b1 100644
--- a/docs/reference/api/doxygen/tir_2expr__functor_8h_source.html
+++ b/docs/reference/api/doxygen/tir_2expr__functor_8h_source.html
@@ -66,7 +66,7 @@ $(function() {
<div class="title">expr_functor.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="tir_2expr__functor_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * [...]
+<a href="tir_2expr__functor_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * [...]
<div class="ttc" id="classtvm_1_1tir_1_1LetNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1LetNode.html">tvm::tir::LetNode</a></div><div class="ttdoc">Let binding. Bind var to value then evaluate body. </div><div class="ttdef"><b>Definition:</b> expr.h:889</div></div>
<div class="ttc" id="classtvm_1_1NodeFunctor_html"><div class="ttname"><a href="classtvm_1_1NodeFunctor.html">tvm::NodeFunctor</a></div><div class="ttdoc">A dynamically dispatched functor on the type of the first argument. </div><div class="ttdef"><b>Definition:</b> functor.h:64</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_a69bf55b39ba603e8aa1d2b029e7215db"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#a69bf55b39ba603e8aa1d2b029e7215db">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const IntImmNode *op, Args... args)</div><div class="ttdef"><b>Definit [...]
@@ -76,7 +76,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_adddfad989a67dea79c5f244ac34cd6fd"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#adddfad989a67dea79c5f244ac34cd6fd">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const NotNode *op, Args... args)</div><div class="ttdef"><b>Definition [...]
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_aa57d47126caef2a706163d086ec76a12"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#aa57d47126caef2a706163d086ec76a12">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const ShuffleNode *op, Args... args)</div><div class="ttdef"><b>Defini [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
-<div class="ttc" id="classtvm_1_1tir_1_1ExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprVisitor.html">tvm::tir::ExprVisitor</a></div><div class="ttdoc">ExprVisitor. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:209</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1ExprVisitor_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprVisitor.html">tvm::tir::ExprVisitor</a></div><div class="ttdoc">ExprVisitor. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:208</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_aaf87a9c9650901e8e88250821c76725c"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#aaf87a9c9650901e8e88250821c76725c">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const FloorModNode *op, Args... args)</div><div class="ttdef"><b>Defin [...]
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_a55c70ed3207e5c48d5b8c0eae989cc41"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#a55c70ed3207e5c48d5b8c0eae989cc41">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const ReduceNode *op, Args... args)</div><div class="ttdef"><b>Definit [...]
<div class="ttc" id="classtvm_1_1tir_1_1StringImmNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1StringImmNode.html">tvm::tir::StringImmNode</a></div><div class="ttdoc">String constants, only used in asserts. </div><div class="ttdef"><b>Definition:</b> expr.h:53</div></div>
@@ -153,7 +153,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_ac4386d82d78c5eec44e01baecd5ccf72"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#ac4386d82d78c5eec44e01baecd5ccf72">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const NENode *op, Args... args)</div><div class="ttdef"><b>Definition: [...]
<div class="ttc" id="classtvm_1_1tir_1_1NENode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1NENode.html">tvm::tir::NENode</a></div><div class="ttdoc">a != b </div><div class="ttdef"><b>Definition:</b> expr.h:365</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4_html_a5f29e35fa0bb60e57bbcb0dec2205f8a"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html#a5f29e35fa0bb60e57bbcb0dec2205f8a">tvm::tir::ExprFunctor< R(const PrimExpr &n, Args...)>::VisitExpr_</a></div><div class="ttdeci">virtual R VisitExpr_(const BufferLoadNode *op, Args... args)</div><div class="ttdef"><b>Def [...]
-<div class="ttc" id="classtvm_1_1tir_1_1ExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprMutator.html">tvm::tir::ExprMutator</a></div><div class="ttdoc">ExprMutator that mutates expressions. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:256</div></div>
+<div class="ttc" id="classtvm_1_1tir_1_1ExprMutator_html"><div class="ttname"><a href="classtvm_1_1tir_1_1ExprMutator.html">tvm::tir::ExprMutator</a></div><div class="ttdoc">ExprMutator that mutates expressions. </div><div class="ttdef"><b>Definition:</b> expr_functor.h:255</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1GENode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1GENode.html">tvm::tir::GENode</a></div><div class="ttdoc">a >= b </div><div class="ttdef"><b>Definition:</b> expr.h:433</div></div>
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diff --git a/docs/reference/api/doxygen/tir_2ir_8h_source.html b/docs/reference/api/doxygen/tir_2ir_8h_source.html
index 9853b39975..e1591468fa 100644
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@@ -149,7 +149,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1script_1_1ir__builder_1_1tir_html_a40266d085b36fddf20d38abd0cdb9616"><div class="ttname"><a href="namespacetvm_1_1script_1_1ir__builder_1_1tir.html#a40266d085b36fddf20d38abd0cdb9616">tvm::script::ir_builder::tir::Else</a></div><div class="ttdeci">ElseFrame Else()</div><div class="ttdoc">Create an else. </div></div>
<div class="ttc" id="namespacetvm_1_1script_1_1ir__builder_1_1tir_html_a2b3df6013772bdd23dfa872b81555272"><div class="ttname"><a href="namespacetvm_1_1script_1_1ir__builder_1_1tir.html#a2b3df6013772bdd23dfa872b81555272">tvm::script::ir_builder::tir::Vectorized</a></div><div class="ttdeci">ForFrame Vectorized(PrimExpr start, PrimExpr stop, Optional< Map< String, ObjectRef >> annotations=NullOpt)</div><div class="ttdoc">The vectorized For statement. </div></div>
<div class="ttc" id="namespacetvm_1_1script_1_1ir__builder_1_1tir_1_1axis_html_a7ced54c699ab9665053615d5c6355ffa"><div class="ttname"><a href="namespacetvm_1_1script_1_1ir__builder_1_1tir_1_1axis.html#a7ced54c699ab9665053615d5c6355ffa">tvm::script::ir_builder::tir::axis::Reduce</a></div><div class="ttdeci">Var Reduce(Range dom, PrimExpr binding, DataType dtype=DataType::Int(32))</div><div class="ttdoc">The reduced block axis defining function. </div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ad1cf4571ee1a22c188c66ee2e6e6c042"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ad1cf4571ee1a22c188c66ee2e6e6c042">tvm::runtime::DataType::UInt</a></div><div class="ttdeci">static DataType UInt(int bits, int lanes=1)</div><div class="ttdoc">Construct an uint type. </div><div class="ttdef"><b>Definition:</b> data_type.h:171</div></div>
<div class="ttc" id="script_2ir__builder_2base_8h_html"><div class="ttname"><a href="script_2ir__builder_2base_8h.html">base.h</a></div></div>
<div class="ttc" id="namespacetvm_1_1script_1_1ir__builder_1_1tir_html_a0e2f9aeceb779e5186af2e9b55fbabca"><div class="ttname"><a href="namespacetvm_1_1script_1_1ir__builder_1_1tir.html#a0e2f9aeceb779e5186af2e9b55fbabca">tvm::script::ir_builder::tir::Grid</a></div><div class="ttdeci">ForFrame Grid(Array< PrimExpr > extents)</div><div class="ttdoc">The grid For statement. </div></div>
diff --git a/docs/reference/api/doxygen/tir_2op_8h.html b/docs/reference/api/doxygen/tir_2op_8h.html
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@@ -772,7 +772,7 @@ Functions</h2></td></tr>
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-<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">float</span> b) { <span class="keywordflow">return</span> Name(a, PrimExpr(b)); } \</div><div class="line"> inline PrimExpr Name(<span class="keywordtype">float</span> a, <span class="keyword">const</span> PrimExpr& b) { <span class="keywordflow">return</span> Name(PrimExpr(a), b); } \</div><div class="li [...]
+<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">float</span> b) { <span class="keywordflow">return</span> Name(a, PrimExpr(b)); } \</div><div class="line"> inline PrimExpr Name(<span class="keywordtype">float</span> a, <span class="keyword">const</span> PrimExpr& b) { <span class="keywordflow">return</span> Name(PrimExpr(a), b); } \</div><div class="li [...]
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@@ -792,7 +792,7 @@ Functions</h2></td></tr>
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<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">float</span> b, <a class="code" href="namespacetvm_1_1relay.html#af40ca6124bc2e88f2323eeb79d326cc0">Span</a> span = <a class="code" href="namespacetvm_1_1relay.html#af40ca6124bc2e88f2323eeb79d326cc0">Span</a>()) { \</div><div class="line"> return Name(a, PrimExpr(b), span); [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
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@@ -811,7 +811,7 @@ Functions</h2></td></tr>
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-<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">int</span> b) { \</div><div class="line"> return Name(a, <a class="code" href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tir::make_const</a>(a.dtype(), b)); \</div><div class="line"> } \</div><div class="line"> inline PrimExpr Name(<span cla [...]
+<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">int</span> b) { \</div><div class="line"> return Name(a, <a class="code" href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tir::make_const</a>(a.dtype(), b)); \</div><div class="line"> } \</div><div class="line"> inline PrimExpr Name(<span cla [...]
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@@ -831,7 +831,7 @@ Functions</h2></td></tr>
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<b>Value:</b><div class="fragment"><div class="line"><span class="keyword">inline</span> PrimExpr Name(<span class="keyword">const</span> PrimExpr& a, <span class="keywordtype">int</span> b, <a class="code" href="namespacetvm_1_1relay.html#af40ca6124bc2e88f2323eeb79d326cc0">Span</a> span = <a class="code" href="namespacetvm_1_1relay.html#af40ca6124bc2e88f2323eeb79d326cc0">Span</a>()) { \</div><div class="line"> return Name(a, <a class="code" href="namespacetvm_1_1tir.html#a1a07120 [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
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diff --git a/docs/reference/api/doxygen/tir_2op_8h_source.html b/docs/reference/api/doxygen/tir_2op_8h_source.html
index 28646605ff..45877d8934 100644
--- a/docs/reference/api/doxygen/tir_2op_8h_source.html
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@@ -66,7 +66,7 @@ $(function() {
<div class="title">op.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="tir_2op_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more con [...]
+<a href="tir_2op_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more con [...]
<div class="ttc" id="namespacetvm_1_1relay_html_af40ca6124bc2e88f2323eeb79d326cc0"><div class="ttname"><a href="namespacetvm_1_1relay.html#af40ca6124bc2e88f2323eeb79d326cc0">tvm::relay::Span</a></div><div class="ttdeci">tvm::Span Span</div><div class="ttdef"><b>Definition:</b> base.h:65</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a246623a4a0c9cd8f8a209ec952a8d1c3"><div class="ttname"><a href="namespacetvm_1_1tir.html#a246623a4a0c9cd8f8a209ec952a8d1c3">tvm::tir::is_const_power_of_two_integer</a></div><div class="ttdeci">bool is_const_power_of_two_integer(const PrimExpr &x, int *shift)</div><div class="ttdoc">Check whether x is a constant power of two If x is power of two, write the power to the shift...</div></div>
<div class="ttc" id="namespacetvm_html_a336b811d7f339f888ad38d2e2657710d"><div class="ttname"><a href="namespacetvm.html#a336b811d7f339f888ad38d2e2657710d">tvm::likely</a></div><div class="ttdeci">PrimExpr likely(PrimExpr cond, Span span=Span())</div><div class="ttdoc">Mark condition as likely. </div></div>
@@ -86,13 +86,13 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a3c9ce1627be2550f656cd37b6c698c7da92916e0b7138b26e222f4b85618bd5b4"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a3c9ce1627be2550f656cd37b6c698c7da92916e0b7138b26e222f4b85618bd5b4">tvm::runtime::DataType::kCustomBegin</a></div><div class="ttdef"><b>Definition:</b> data_type.h:57</div></div>
<div class="ttc" id="namespacetvm_html_a3b37fa55ea93d6868751a2441996b072"><div class="ttname"><a href="namespacetvm.html#a3b37fa55ea93d6868751a2441996b072">tvm::min_value</a></div><div class="ttdeci">PrimExpr min_value(const DataType &dtype, Span span=Span())</div></div>
<div class="ttc" id="namespacetvm_html_ada5ad8338d3144221d8f16380e6c4855"><div class="ttname"><a href="namespacetvm.html#ada5ad8338d3144221d8f16380e6c4855">tvm::indexmod</a></div><div class="ttdeci">PrimExpr indexmod(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute the remainder floor(a / b) where a and b are non-negative. </div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="ir_2expr_8h_html"><div class="ttname"><a href="ir_2expr_8h.html">expr.h</a></div><div class="ttdoc">Base expr nodes in TVM. </div></div>
<div class="ttc" id="namespacetvm_html_ad828bc801c73df761c58d9f8877d52ee"><div class="ttname"><a href="namespacetvm.html#ad828bc801c73df761c58d9f8877d52ee">tvm::sinh</a></div><div class="ttdeci">PrimExpr sinh(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:710</div></div>
<div class="ttc" id="namespacetvm_html_ae2794f261657780b2af4208b95d9cfcb"><div class="ttname"><a href="namespacetvm.html#ae2794f261657780b2af4208b95d9cfcb">tvm::add</a></div><div class="ttdeci">PrimExpr add(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">add operator </div></div>
<div class="ttc" id="tir_2op_8h_html_abc43baea1e8f1c876bfa743a063a5928"><div class="ttname"><a href="tir_2op_8h.html#abc43baea1e8f1c876bfa743a063a5928">TVM_DECLARE_INTRIN_BINARY</a></div><div class="ttdeci">#define TVM_DECLARE_INTRIN_BINARY(OpName)</div><div class="ttdef"><b>Definition:</b> op.h:719</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
-<div class="ttc" id="tir_2op_8h_html_a34c733b88658efba336e09ccd85e576c"><div class="ttname"><a href="tir_2op_8h.html#a34c733b88658efba336e09ccd85e576c">TVM_DEFINE_ASSIGN_OP_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_ASSIGN_OP_OVERLOAD(Name, OpFunc)</div><div class="ttdef"><b>Definition:</b> op.h:970</div></div>
+<div class="ttc" id="tir_2op_8h_html_a34c733b88658efba336e09ccd85e576c"><div class="ttname"><a href="tir_2op_8h.html#a34c733b88658efba336e09ccd85e576c">TVM_DEFINE_ASSIGN_OP_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_ASSIGN_OP_OVERLOAD(Name, OpFunc)</div><div class="ttdef"><b>Definition:</b> op.h:969</div></div>
<div class="ttc" id="namespacetvm_html_af99838098788d40c80b402f29b3c2e8c"><div class="ttname"><a href="namespacetvm.html#af99838098788d40c80b402f29b3c2e8c">tvm::tan</a></div><div class="ttdeci">PrimExpr tan(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:706</div></div>
<div class="ttc" id="namespacetvm_html_a89da021f5e3e2e911acfd96f973e5bc3"><div class="ttname"><a href="namespacetvm.html#a89da021f5e3e2e911acfd96f973e5bc3">tvm::sub</a></div><div class="ttdeci">PrimExpr sub(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">subtraction operator </div></div>
<div class="ttc" id="namespacetvm_html_ab72a6b6a2d0c2aa3f6a95f60dc831493"><div class="ttname"><a href="namespacetvm.html#ab72a6b6a2d0c2aa3f6a95f60dc831493">tvm::atanh</a></div><div class="ttdeci">PrimExpr atanh(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:716</div></div>
@@ -108,17 +108,17 @@ $(function() {
<div class="ttc" id="namespacetvm_html_a4509dece1af96338cc25097855fcecd7"><div class="ttname"><a href="namespacetvm.html#a4509dece1af96338cc25097855fcecd7">tvm::logical_or</a></div><div class="ttdeci">PrimExpr logical_or(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">or </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a71feb294f412836c3d7e012133a3f339"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a71feb294f412836c3d7e012133a3f339">tvm::runtime::DataType::code</a></div><div class="ttdeci">int code() const</div><div class="ttdef"><b>Definition:</b> data_type.h:81</div></div>
<div class="ttc" id="namespacetvm_html_aee8d9c7084d8df28bf6f05e0851a557f"><div class="ttname"><a href="namespacetvm.html#aee8d9c7084d8df28bf6f05e0851a557f">tvm::bitwise_or</a></div><div class="ttdeci">PrimExpr bitwise_or(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take bitwise or of two values </div></div>
-<div class="ttc" id="namespacetvm_html_aa22a313c142a61845ded7fdf77af7046"><div class="ttname"><a href="namespacetvm.html#aa22a313c142a61845ded7fdf77af7046">tvm::max</a></div><div class="ttdeci">PrimExpr max(const PrimExpr &a, double b, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:1042</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a6454dd89e85fc29a7e3b8620df90a6f6"><div class="ttname"><a href="namespacetvm_1_1tir.html#a6454dd89e85fc29a7e3b8620df90a6f6">tvm::tir::foldl</a></div><div class="ttdeci">PrimExpr foldl(FReduce freduce, PrimExpr init_value, const Array< PrimExpr > &values, Span span=Span())</div><div class="ttdoc">Left fold. </div><div class="ttdef"><b>Definition:</b> op.h:959</div></div>
+<div class="ttc" id="namespacetvm_html_aa22a313c142a61845ded7fdf77af7046"><div class="ttname"><a href="namespacetvm.html#aa22a313c142a61845ded7fdf77af7046">tvm::max</a></div><div class="ttdeci">PrimExpr max(const PrimExpr &a, double b, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:1041</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a6454dd89e85fc29a7e3b8620df90a6f6"><div class="ttname"><a href="namespacetvm_1_1tir.html#a6454dd89e85fc29a7e3b8620df90a6f6">tvm::tir::foldl</a></div><div class="ttdeci">PrimExpr foldl(FReduce freduce, PrimExpr init_value, const Array< PrimExpr > &values, Span span=Span())</div><div class="ttdoc">Left fold. </div><div class="ttdef"><b>Definition:</b> op.h:958</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_acbe8f225faaf34c540194921a7ee6a66"><div class="ttname"><a href="namespacetvm_1_1tir.html#acbe8f225faaf34c540194921a7ee6a66">tvm::tir::as_const_int</a></div><div class="ttdeci">const int64_t * as_const_int(const PrimExpr &x)</div><div class="ttdoc">Get x as constant int expression. </div><div class="ttdef"><b>Definition:</b> op.h:791</div></div>
<div class="ttc" id="namespacetvm_html_a7ffc1cdb3a52b680e4b509395c9a252d"><div class="ttname"><a href="namespacetvm.html#a7ffc1cdb3a52b680e4b509395c9a252d">tvm::greater</a></div><div class="ttdeci">PrimExpr greater(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">greater </div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a0db485654cd60d43962f532a1b16026c"><div class="ttname"><a href="namespacetvm_1_1tir.html#a0db485654cd60d43962f532a1b16026c">tvm::tir::MakeConstScalar</a></div><div class="ttdeci">PrimExpr MakeConstScalar(DataType t, ValueType value, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:909</div></div>
<div class="ttc" id="namespacetvm_html_a350f9808d53b5fd9ad5c4c50bb76d700"><div class="ttname"><a href="namespacetvm.html#a350f9808d53b5fd9ad5c4c50bb76d700">tvm::atan2</a></div><div class="ttdeci">PrimExpr atan2(PrimExpr x, PrimExpr y, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:725</div></div>
-<div class="ttc" id="tir_2op_8h_html_ab6a17993efa67183ba992dac29284c80"><div class="ttname"><a href="tir_2op_8h.html#ab6a17993efa67183ba992dac29284c80">TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1006</div></div>
+<div class="ttc" id="tir_2op_8h_html_ab6a17993efa67183ba992dac29284c80"><div class="ttname"><a href="tir_2op_8h.html#ab6a17993efa67183ba992dac29284c80">TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1005</div></div>
<div class="ttc" id="namespacetvm_html_a0447e9aa45f6cab707f6dc9f9281b3f5"><div class="ttname"><a href="namespacetvm.html#a0447e9aa45f6cab707f6dc9f9281b3f5">tvm::GetRuntimeDataType</a></div><div class="ttdeci">runtime::DataType GetRuntimeDataType(const Type &type)</div><div class="ttdoc">Get the implied DataType for storing values with type during runtime. </div></div>
<div class="ttc" id="classtvm_1_1PointerTypeNode_html"><div class="ttname"><a href="classtvm_1_1PointerTypeNode.html">tvm::PointerTypeNode</a></div><div class="ttdoc">Low-level raw pointer type. </div><div class="ttdef"><b>Definition:</b> type.h:150</div></div>
<div class="ttc" id="namespacetvm_html_a52a4f309e25bcb51c6038f6e3ee931ec"><div class="ttname"><a href="namespacetvm.html#a52a4f309e25bcb51c6038f6e3ee931ec">tvm::asinh</a></div><div class="ttdeci">PrimExpr asinh(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:715</div></div>
-<div class="ttc" id="tir_2op_8h_html_a29826503ae15ba83c6bc8e6cbe218a69"><div class="ttname"><a href="tir_2op_8h.html#a29826503ae15ba83c6bc8e6cbe218a69">TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1010</div></div>
+<div class="ttc" id="tir_2op_8h_html_a29826503ae15ba83c6bc8e6cbe218a69"><div class="ttname"><a href="tir_2op_8h.html#a29826503ae15ba83c6bc8e6cbe218a69">TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_LOGICAL_OP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1009</div></div>
<div class="ttc" id="namespacetvm_html_a4bfb789a86d95f6241b50fd26f269c28"><div class="ttname"><a href="namespacetvm.html#a4bfb789a86d95f6241b50fd26f269c28">tvm::cast</a></div><div class="ttdeci">PrimExpr cast(const DataType &t, PrimExpr value, Span span=Span())</div><div class="ttdoc">cast value to type. </div></div>
<div class="ttc" id="namespacetvm_html_ae39f72b12020a4f7ad6b16b66ffdfe1f"><div class="ttname"><a href="namespacetvm.html#ae39f72b12020a4f7ad6b16b66ffdfe1f">tvm::log</a></div><div class="ttdeci">PrimExpr log(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:701</div></div>
<div class="ttc" id="namespacetvm_html_a54d9c399c82d7f384ee93f235496ab64"><div class="ttname"><a href="namespacetvm.html#a54d9c399c82d7f384ee93f235496ab64">tvm::round</a></div><div class="ttdeci">PrimExpr round(PrimExpr x, Span span=Span())</div><div class="ttdoc">Calculate round(x) </div></div>
@@ -131,7 +131,7 @@ $(function() {
<div class="ttc" id="classtvm_1_1Span_html"><div class="ttname"><a href="classtvm_1_1Span.html">tvm::Span</a></div><div class="ttdef"><b>Definition:</b> span.h:115</div></div>
<div class="ttc" id="stmt_8h_html"><div class="ttname"><a href="stmt_8h.html">stmt.h</a></div><div class="ttdoc">TIR statements. </div></div>
<div class="ttc" id="namespacetvm_html_a8683adb542beba8ecc69354e50d62ef6"><div class="ttname"><a href="namespacetvm.html#a8683adb542beba8ecc69354e50d62ef6">tvm::floormod</a></div><div class="ttdeci">PrimExpr floormod(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute the remainder of floordiv </div></div>
-<div class="ttc" id="namespacetvm_html_a51dc569142bf8ce8ea55f73029d3807d"><div class="ttname"><a href="namespacetvm.html#a51dc569142bf8ce8ea55f73029d3807d">tvm::operator/=</a></div><div class="ttdeci">PrimExpr operator/=(const PrimExpr &a, const TB &b)</div><div class="ttdef"><b>Definition:</b> op.h:1103</div></div>
+<div class="ttc" id="namespacetvm_html_a51dc569142bf8ce8ea55f73029d3807d"><div class="ttname"><a href="namespacetvm.html#a51dc569142bf8ce8ea55f73029d3807d">tvm::operator/=</a></div><div class="ttdeci">PrimExpr operator/=(const PrimExpr &a, const TB &b)</div><div class="ttdef"><b>Definition:</b> op.h:1102</div></div>
<div class="ttc" id="namespacetvm_html_a16f9cd9219b505e2cc05c5a7558ac61f"><div class="ttname"><a href="namespacetvm.html#a16f9cd9219b505e2cc05c5a7558ac61f">tvm::div</a></div><div class="ttdeci">PrimExpr div(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute division in C semantics. </div></div>
<div class="ttc" id="namespacetvm_html_a28e456d33229a628a312110db8d45b44"><div class="ttname"><a href="namespacetvm.html#a28e456d33229a628a312110db8d45b44">tvm::hypot</a></div><div class="ttdeci">PrimExpr hypot(PrimExpr x, PrimExpr y, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:728</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a875c28f423ab96ae8f0d21f1263abe14"><div class="ttname"><a href="namespacetvm_1_1tir.html#a875c28f423ab96ae8f0d21f1263abe14">tvm::tir::const_false</a></div><div class="ttdeci">PrimExpr const_false(int lanes=1, Span span=Span())</div><div class="ttdoc">Make a constant false expression. </div><div class="ttdef"><b>Definition:</b> op.h:782</div></div>
@@ -149,17 +149,17 @@ $(function() {
<div class="ttc" id="namespacetvm_html_ac788f9eb54a8971596779537afc6c896"><div class="ttname"><a href="namespacetvm.html#ac788f9eb54a8971596779537afc6c896">tvm::q_multiply_shift</a></div><div class="ttdeci">PrimExpr q_multiply_shift(PrimExpr x, PrimExpr y, PrimExpr q, PrimExpr s, Span span=Span())</div><div class="ttdoc">Execute a multiplication between two Q-numbers x and y followed by a right shift s. The mathematical expression is: </div></div>
<div class="ttc" id="tir_2op_8h_html_a032e3ae6824990aad98b8992f90a83c9"><div class="ttname"><a href="tir_2op_8h.html#a032e3ae6824990aad98b8992f90a83c9">TVM_DECLARE_INTRIN_UNARY</a></div><div class="ttdeci">#define TVM_DECLARE_INTRIN_UNARY(OpName)</div><div class="ttdef"><b>Definition:</b> op.h:679</div></div>
<div class="ttc" id="namespacetvm_html_a096aa20c0df975d089231b2c6fda2e61"><div class="ttname"><a href="namespacetvm.html#a096aa20c0df975d089231b2c6fda2e61">tvm::isfinite</a></div><div class="ttdeci">PrimExpr isfinite(PrimExpr x, Span span=Span())</div><div class="ttdoc">Check if x is finite. </div></div>
-<div class="ttc" id="tir_2op_8h_html_a0ad19625381aae20ca7a930260089c47"><div class="ttname"><a href="tir_2op_8h.html#a0ad19625381aae20ca7a930260089c47">TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1018</div></div>
+<div class="ttc" id="tir_2op_8h_html_a0ad19625381aae20ca7a930260089c47"><div class="ttname"><a href="tir_2op_8h.html#a0ad19625381aae20ca7a930260089c47">TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1017</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1BroadcastNode_html"><div class="ttname"><a href="classtvm_1_1tir_1_1BroadcastNode.html">tvm::tir::BroadcastNode</a></div><div class="ttdoc">Create a vector where all the elements are value. </div><div class="ttdef"><b>Definition:</b> expr.h:847</div></div>
<div class="ttc" id="namespacetvm_html_aeeef6fde2a1352eae8abddd994c657b7"><div class="ttname"><a href="namespacetvm.html#aeeef6fde2a1352eae8abddd994c657b7">tvm::clz</a></div><div class="ttdeci">PrimExpr clz(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:717</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Stmt_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Stmt.html">tvm::tir::Stmt</a></div><div class="ttdoc">Container of all statements. </div><div class="ttdef"><b>Definition:</b> stmt.h:57</div></div>
<div class="ttc" id="namespacetvm_html_a41c8855d1e4f7ea1d01e42e6c214f877"><div class="ttname"><a href="namespacetvm.html#a41c8855d1e4f7ea1d01e42e6c214f877">tvm::cosh</a></div><div class="ttdeci">PrimExpr cosh(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:708</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a0de5803abe309ca66c23adb15c565afb"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a0de5803abe309ca66c23adb15c565afb">tvm::runtime::DataType::is_uint</a></div><div class="ttdeci">bool is_uint() const</div><div class="ttdef"><b>Definition:</b> data_type.h:101</div></div>
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
-<div class="ttc" id="tir_2op_8h_html_aabcf618a12e97c38fccecf7351392154"><div class="ttname"><a href="tir_2op_8h.html#aabcf618a12e97c38fccecf7351392154">TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:976</div></div>
+<div class="ttc" id="tir_2op_8h_html_aabcf618a12e97c38fccecf7351392154"><div class="ttname"><a href="tir_2op_8h.html#aabcf618a12e97c38fccecf7351392154">TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD</a></div><div class="ttdeci">#define TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD(Name)</div><div class="ttdef"><b>Definition:</b> op.h:975</div></div>
<div class="ttc" id="classtvm_1_1IntImmNode_html_a81f4c116ffb5931fdd64639eacad415d"><div class="ttname"><a href="classtvm_1_1IntImmNode.html#a81f4c116ffb5931fdd64639eacad415d">tvm::IntImmNode::value</a></div><div class="ttdeci">int64_t value</div><div class="ttdoc">the Internal value. </div><div class="ttdef"><b>Definition:</b> expr.h:492</div></div>
<div class="ttc" id="namespacetvm_html_a15f25703cfce73c75cb4cd33c74ea8f0"><div class="ttname"><a href="namespacetvm.html#a15f25703cfce73c75cb4cd33c74ea8f0">tvm::shapediv</a></div><div class="ttdeci">PrimExpr shapediv(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute ceil(a / b) where a and b are non-negative. </div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:951</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:950</div></div>
<div class="ttc" id="namespacetvm_html_a3f6d8fba545c2944efc83b57e6190459"><div class="ttname"><a href="namespacetvm.html#a3f6d8fba545c2944efc83b57e6190459">tvm::bitwise_neg</a></div><div class="ttdeci">PrimExpr bitwise_neg(PrimExpr a, Span span=Span())</div><div class="ttdoc">take bitwise negation of two values </div></div>
<div class="ttc" id="namespacetvm_html_a5efd9942cdee5a56cfc438ba523c04f0"><div class="ttname"><a href="namespacetvm.html#a5efd9942cdee5a56cfc438ba523c04f0">tvm::any</a></div><div class="ttdeci">PrimExpr any(PrimExpr source, Array< tir::IterVar > axis, Array< PrimExpr > init={}, Span span=Span())</div><div class="ttdoc">logical Or of source expression over axis </div></div>
<div class="ttc" id="namespacetvm_html_a139870d327497d548e2ef8bddba2f114"><div class="ttname"><a href="namespacetvm.html#a139870d327497d548e2ef8bddba2f114">tvm::erf</a></div><div class="ttdeci">PrimExpr erf(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:696</div></div>
@@ -188,19 +188,19 @@ $(function() {
<div class="ttc" id="namespacetvm_html_a4f1398024c0af23699447ef910b654b8"><div class="ttname"><a href="namespacetvm.html#a4f1398024c0af23699447ef910b654b8">tvm::max_value</a></div><div class="ttdeci">PrimExpr max_value(const DataType &dtype, Span span=Span())</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a5b96c80ce43c8276e39c15787d997651"><div class="ttname"><a href="namespacetvm_1_1tir.html#a5b96c80ce43c8276e39c15787d997651">tvm::tir::is_const_number</a></div><div class="ttdeci">bool is_const_number(const PrimExpr &x)</div><div class="ttdoc">Check whether x is an integer/float constant. </div><div class="ttdef"><b>Definition:</b> op.h:871</div></div>
<div class="ttc" id="namespacetvm_html_a5472f967969aebee254e8e78f2396436"><div class="ttname"><a href="namespacetvm.html#a5472f967969aebee254e8e78f2396436">tvm::trunc</a></div><div class="ttdeci">PrimExpr trunc(PrimExpr x, Span span=Span())</div><div class="ttdoc">Calculate trunc(x) </div></div>
-<div class="ttc" id="tir_2op_8h_html_ac211367ff4e2382caf322a3903f8c629"><div class="ttname"><a href="tir_2op_8h.html#ac211367ff4e2382caf322a3903f8c629">TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1024</div></div>
+<div class="ttc" id="tir_2op_8h_html_ac211367ff4e2382caf322a3903f8c629"><div class="ttname"><a href="tir_2op_8h.html#ac211367ff4e2382caf322a3903f8c629">TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_INT_OP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:1023</div></div>
<div class="ttc" id="namespacetvm_html_a0da40d3e210aa3b38a17982a7b7866b8"><div class="ttname"><a href="namespacetvm.html#a0da40d3e210aa3b38a17982a7b7866b8">tvm::ret</a></div><div class="ttdeci">PrimExpr ret(PrimExpr value, Span span=Span())</div><div class="ttdoc">Return the value. </div></div>
<div class="ttc" id="namespacetvm_html_a532ceddde4b8c713b0b1d7e737fcf5fb"><div class="ttname"><a href="namespacetvm.html#a532ceddde4b8c713b0b1d7e737fcf5fb">tvm::sin</a></div><div class="ttdeci">PrimExpr sin(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:709</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_af0e52ef3c0d8e11bf493d5163033cd0d"><div class="ttname"><a href="namespacetvm_1_1topi.html#af0e52ef3c0d8e11bf493d5163033cd0d">tvm::topi::FReduce</a></div><div class="ttdeci">std::function< PrimExpr(PrimExpr source, const Array< IterVar > &axis, Array< PrimExpr > init, Span span)> FReduce</div><div class="ttdoc">The operation to use for CommReduce. </div><div class="ttdef"><b>Definition:</b> reduction.h:47</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a51d552441331effb387b7c8fb241c454"><div class="ttname"><a href="namespacetvm_1_1tir.html#a51d552441331effb387b7c8fb241c454">tvm::tir::is_negative_const</a></div><div class="ttdeci">bool is_negative_const(const PrimExpr &a)</div><div class="ttdef"><b>Definition:</b> op.h:887</div></div>
-<div class="ttc" id="namespacetvm_html_a31e7a3e4a160a1d048e3ba741966f1a8"><div class="ttname"><a href="namespacetvm.html#a31e7a3e4a160a1d048e3ba741966f1a8">tvm::DivAmbiguityError</a></div><div class="ttdeci">void DivAmbiguityError(const TA &a)</div><div class="ttdoc">Helper function to raise a compiler error about division ambiguity. </div><div class="ttdef"><b>Definition:</b> op.h:1081</div></div>
+<div class="ttc" id="namespacetvm_html_a31e7a3e4a160a1d048e3ba741966f1a8"><div class="ttname"><a href="namespacetvm.html#a31e7a3e4a160a1d048e3ba741966f1a8">tvm::DivAmbiguityError</a></div><div class="ttdeci">void DivAmbiguityError(const TA &a)</div><div class="ttdoc">Helper function to raise a compiler error about division ambiguity. </div><div class="ttdef"><b>Definition:</b> op.h:1080</div></div>
<div class="ttc" id="namespacetvm_html_a18256ba1213ce5ff3cf8037a314354b7"><div class="ttname"><a href="namespacetvm.html#a18256ba1213ce5ff3cf8037a314354b7">tvm::operator/</a></div><div class="ttdeci">PrimExpr operator/(PrimExpr a, PrimExpr b)</div><div class="ttdoc">division operator </div></div>
<div class="ttc" id="namespacetvm_html_aaa28e92b677086d89ebfb77204bf92a2"><div class="ttname"><a href="namespacetvm.html#aaa28e92b677086d89ebfb77204bf92a2">tvm::mul</a></div><div class="ttdeci">PrimExpr mul(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">multiplication operator </div></div>
<div class="ttc" id="namespacetvm_html_a69f67f2d38656a8e663af0912d00cb51"><div class="ttname"><a href="namespacetvm.html#a69f67f2d38656a8e663af0912d00cb51">tvm::copysign</a></div><div class="ttdeci">PrimExpr copysign(PrimExpr x, PrimExpr y, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:727</div></div>
<div class="ttc" id="classtvm_1_1Type_html"><div class="ttname"><a href="classtvm_1_1Type.html">tvm::Type</a></div><div class="ttdoc">Managed reference to TypeNode. </div><div class="ttdef"><b>Definition:</b> type.h:93</div></div>
<div class="ttc" id="namespacetvm_html_a62955df1df48917116efe39d4cd18fec"><div class="ttname"><a href="namespacetvm.html#a62955df1df48917116efe39d4cd18fec">tvm::logical_not</a></div><div class="ttdeci">PrimExpr logical_not(PrimExpr a, Span span=Span())</div><div class="ttdoc">not </div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a782dc226f8b2b537efdc56b1f76351d1"><div class="ttname"><a href="namespacetvm_1_1tir.html#a782dc226f8b2b537efdc56b1f76351d1">tvm::tir::is_positive_const</a></div><div class="ttdeci">bool is_positive_const(const PrimExpr &a)</div><div class="ttdef"><b>Definition:</b> op.h:882</div></div>
-<div class="ttc" id="namespacetvm_html_ab25738e50b37cd07b2d171ca74ba9321"><div class="ttname"><a href="namespacetvm.html#ab25738e50b37cd07b2d171ca74ba9321">tvm::operator%</a></div><div class="ttdeci">PrimExpr operator%(const PrimExpr &a, const TB &b)</div><div class="ttdef"><b>Definition:</b> op.h:1109</div></div>
+<div class="ttc" id="namespacetvm_html_ab25738e50b37cd07b2d171ca74ba9321"><div class="ttname"><a href="namespacetvm.html#ab25738e50b37cd07b2d171ca74ba9321">tvm::operator%</a></div><div class="ttdeci">PrimExpr operator%(const PrimExpr &a, const TB &b)</div><div class="ttdef"><b>Definition:</b> op.h:1108</div></div>
<div class="ttc" id="namespacetvm_html_ae8ecc0382685a855187bede0c97d93e6"><div class="ttname"><a href="namespacetvm.html#ae8ecc0382685a855187bede0c97d93e6">tvm::right_shift</a></div><div class="ttdeci">PrimExpr right_shift(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">right shift operator </div></div>
<div class="ttc" id="namespacetvm_html_a82be70bd7794abca32473604cbb09569"><div class="ttname"><a href="namespacetvm.html#a82be70bd7794abca32473604cbb09569">tvm::exp</a></div><div class="ttdeci">PrimExpr exp(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:693</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_a052732be4d88e9d67dc2cbe83ba6a310"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#a052732be4d88e9d67dc2cbe83ba6a310">tvm::runtime::DataType::is_handle</a></div><div class="ttdeci">bool is_handle() const</div><div class="ttdef"><b>Definition:</b> data_type.h:103</div></div>
@@ -211,11 +211,11 @@ $(function() {
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html_a2d76fa1fb628ff276a284e61123589c5"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html#a2d76fa1fb628ff276a284e61123589c5">tvm::runtime::ObjectRef::as</a></div><div class="ttdeci">const ObjectType * as() const</div><div class="ttdoc">Try to downcast the internal Object to a raw pointer of a corresponding type. </div><div class="ttdef"><b>Definition:</b> object.h:865</div></div>
<div class="ttc" id="namespacetvm_html_ac62b239b36ad259a118bb20cb78a01a2"><div class="ttname"><a href="namespacetvm.html#ac62b239b36ad259a118bb20cb78a01a2">tvm::truncdiv</a></div><div class="ttdeci">PrimExpr truncdiv(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute trunc(a / b) </div></div>
<div class="ttc" id="namespacetvm_html_aa048961a5d19e9f32071c1372809ecbd"><div class="ttname"><a href="namespacetvm.html#aa048961a5d19e9f32071c1372809ecbd">tvm::sigmoid</a></div><div class="ttdeci">PrimExpr sigmoid(PrimExpr x, Span span=Span())</div><div class="ttdef"><b>Definition:</b> op.h:698</div></div>
-<div class="ttc" id="tir_2op_8h_html_a8fc539385c2bb11740d0a6bef19be7b8"><div class="ttname"><a href="tir_2op_8h.html#a8fc539385c2bb11740d0a6bef19be7b8">TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:989</div></div>
+<div class="ttc" id="tir_2op_8h_html_a8fc539385c2bb11740d0a6bef19be7b8"><div class="ttname"><a href="tir_2op_8h.html#a8fc539385c2bb11740d0a6bef19be7b8">TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD_SPANNED</a></div><div class="ttdeci">#define TVM_DEFINE_BINOP_CONST_VAL_OVERLOAD_SPANNED(Name)</div><div class="ttdef"><b>Definition:</b> op.h:988</div></div>
<div class="ttc" id="namespacetvm_html_ad4fceb4266c6e7644fa373eacf73359f"><div class="ttname"><a href="namespacetvm.html#ad4fceb4266c6e7644fa373eacf73359f">tvm::left_shift</a></div><div class="ttdeci">PrimExpr left_shift(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">left shift operator </div></div>
<div class="ttc" id="namespacetvm_html_a32a87ae9eacafb2b5b71b28bcc9ef35e"><div class="ttname"><a href="namespacetvm.html#a32a87ae9eacafb2b5b71b28bcc9ef35e">tvm::prod</a></div><div class="ttdeci">PrimExpr prod(PrimExpr source, Array< tir::IterVar > axis, Array< PrimExpr > init={}, Span span=Span())</div><div class="ttdoc">product of source expression over axis </div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a48bad3db162b334837716bf8e7ba9285"><div class="ttname"><a href="namespacetvm_1_1tir.html#a48bad3db162b334837716bf8e7ba9285">tvm::tir::is_zero</a></div><div class="ttdeci">bool is_zero(const PrimExpr &x)</div><div class="ttdoc">Check whether x is a constant integer 0. </div><div class="ttdef"><b>Definition:</b> op.h:829</div></div>
-<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:399</div></div>
+<div class="ttc" id="namespacetvm_html_a41918af1a1dc386388639a9d3ad06c5d"><div class="ttname"><a href="namespacetvm.html#a41918af1a1dc386388639a9d3ad06c5d">tvm::DataType</a></div><div class="ttdeci">runtime::DataType DataType</div><div class="ttdef"><b>Definition:</b> data_type.h:398</div></div>
<div class="ttc" id="namespacetvm_html_a52fa1dc57423a077eb098960162e7b85"><div class="ttname"><a href="namespacetvm.html#a52fa1dc57423a077eb098960162e7b85">tvm::less</a></div><div class="ttdeci">PrimExpr less(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">less </div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1DataType_html_ad1cf4571ee1a22c188c66ee2e6e6c042"><div class="ttname"><a href="classtvm_1_1runtime_1_1DataType.html#ad1cf4571ee1a22c188c66ee2e6e6c042">tvm::runtime::DataType::UInt</a></div><div class="ttdeci">static DataType UInt(int bits, int lanes=1)</div><div class="ttdoc">Construct an uint type. </div><div class="ttdef"><b>Definition:</b> data_type.h:171</div></div>
<div class="ttc" id="namespacetvm_html_ac06a47be8386f28b313903e174dfe151"><div class="ttname"><a href="namespacetvm.html#ac06a47be8386f28b313903e174dfe151">tvm::isinf</a></div><div class="ttdeci">PrimExpr isinf(PrimExpr x, Span span=Span())</div><div class="ttdoc">Check if x is infinite. </div></div>
diff --git a/docs/reference/api/doxygen/tir_2op__attr__types_8h_source.html b/docs/reference/api/doxygen/tir_2op__attr__types_8h_source.html
index 3a58aeaeb0..7d0597614a 100644
--- a/docs/reference/api/doxygen/tir_2op__attr__types_8h_source.html
+++ b/docs/reference/api/doxygen/tir_2op__attr__types_8h_source.html
@@ -66,7 +66,7 @@ $(function() {
<div class="title">op_attr_types.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="tir_2op__attr__types_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> [...]
+<a href="tir_2op__attr__types_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> [...]
<div class="ttc" id="ir_2expr_8h_html"><div class="ttname"><a href="ir_2expr_8h.html">expr.h</a></div><div class="ttdoc">Base expr nodes in TVM. </div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1tir_html_a8f4a86b205145696c0555fd02bd37f46a2ded73cfb5a05bf0e37b284e42769c9c"><div class="ttname"><a href="namespacetvm_1_1tir.html#a8f4a86b205145696c0555fd02bd37f46a2ded73cfb5a05bf0e37b284e42769c9c">tvm::tir::CallEffectKind::kControlJump</a></div><div class="ttdoc">Function that changes control flow. </div></div>
diff --git a/docs/reference/api/doxygen/topi_2nn_8h_source.html b/docs/reference/api/doxygen/topi_2nn_8h_source.html
index f9047abe27..5ecfcd17ac 100644
--- a/docs/reference/api/doxygen/topi_2nn_8h_source.html
+++ b/docs/reference/api/doxygen/topi_2nn_8h_source.html
@@ -69,7 +69,7 @@ $(function() {
<a href="topi_2nn_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more co [...]
<div class="ttc" id="namespacetvm_1_1topi_html_a582bc98a3956894e8e90a3a3da929568"><div class="ttname"><a href="namespacetvm_1_1topi.html#a582bc98a3956894e8e90a3a3da929568">tvm::topi::divide</a></div><div class="ttdeci">tvm::PrimExpr divide(const tvm::PrimExpr &a, const tvm::PrimExpr &b)</div><div class="ttdef"><b>Definition:</b> broadcast.h:239</div></div>
<div class="ttc" id="namespacetvm_html_ada5ad8338d3144221d8f16380e6c4855"><div class="ttname"><a href="namespacetvm.html#ada5ad8338d3144221d8f16380e6c4855">tvm::indexmod</a></div><div class="ttdeci">PrimExpr indexmod(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute the remainder floor(a / b) where a and b are non-negative. </div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
<div class="ttc" id="namespacetvm_1_1te_html"><div class="ttname"><a href="namespacetvm_1_1te.html">tvm::te</a></div><div class="ttdoc">Tensor expression language DSL. </div><div class="ttdef"><b>Definition:</b> extracted_task.h:33</div></div>
<div class="ttc" id="classtvm_1_1tir_1_1Var_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Var.html">tvm::tir::Var</a></div><div class="ttdoc">a named variable in TIR </div><div class="ttdef"><b>Definition:</b> var.h:88</div></div>
@@ -79,7 +79,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1topi_html_a29e22aa45900dad3b6f9f705bb1dc688"><div class="ttname"><a href="namespacetvm_1_1topi.html#a29e22aa45900dad3b6f9f705bb1dc688">tvm::topi::kInjective</a></div><div class="ttdeci">constexpr auto kInjective</div><div class="ttdef"><b>Definition:</b> tags.h:33</div></div>
<div class="ttc" id="reduction_8h_html"><div class="ttname"><a href="reduction_8h.html">reduction.h</a></div><div class="ttdoc">Reduction op constructors. </div></div>
<div class="ttc" id="classtvm_1_1arith_1_1Analyzer_html_a9b440f852f12ad0a4d8ed5ed97054425"><div class="ttname"><a href="classtvm_1_1arith_1_1Analyzer.html#a9b440f852f12ad0a4d8ed5ed97054425">tvm::arith::Analyzer::Simplify</a></div><div class="ttdeci">PrimExpr Simplify(const PrimExpr &expr, int steps=2)</div><div class="ttdoc">Simplify expr. </div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_a6454dd89e85fc29a7e3b8620df90a6f6"><div class="ttname"><a href="namespacetvm_1_1tir.html#a6454dd89e85fc29a7e3b8620df90a6f6">tvm::tir::foldl</a></div><div class="ttdeci">PrimExpr foldl(FReduce freduce, PrimExpr init_value, const Array< PrimExpr > &values, Span span=Span())</div><div class="ttdoc">Left fold. </div><div class="ttdef"><b>Definition:</b> op.h:959</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a6454dd89e85fc29a7e3b8620df90a6f6"><div class="ttname"><a href="namespacetvm_1_1tir.html#a6454dd89e85fc29a7e3b8620df90a6f6">tvm::tir::foldl</a></div><div class="ttdeci">PrimExpr foldl(FReduce freduce, PrimExpr init_value, const Array< PrimExpr > &values, Span span=Span())</div><div class="ttdoc">Left fold. </div><div class="ttdef"><b>Definition:</b> op.h:958</div></div>
<div class="ttc" id="tir_2op_8h_html"><div class="ttname"><a href="tir_2op_8h.html">op.h</a></div><div class="ttdoc">Common operators defined for Expr. </div></div>
<div class="ttc" id="namespacetvm_html_a4bfb789a86d95f6241b50fd26f269c28"><div class="ttname"><a href="namespacetvm.html#a4bfb789a86d95f6241b50fd26f269c28">tvm::cast</a></div><div class="ttdeci">PrimExpr cast(const DataType &t, PrimExpr value, Span span=Span())</div><div class="ttdoc">cast value to type. </div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_aeb1547800d4b7625326a176ca1dec6e0"><div class="ttname"><a href="namespacetvm_1_1topi.html#aeb1547800d4b7625326a176ca1dec6e0">tvm::topi::nll_loss</a></div><div class="ttdeci">Tensor nll_loss(const Tensor &predictions, const Tensor &targets, const Tensor &weights, std::string reduction="mean", int ignore_index=-100, const std::string name="nll_loss", const std::string tag=kBroadcast)</div><div class="ttdoc">Nega [...]
diff --git a/docs/reference/api/doxygen/topi_2transform_8h_source.html b/docs/reference/api/doxygen/topi_2transform_8h_source.html
index e0dcf5054b..8208f6216b 100644
--- a/docs/reference/api/doxygen/topi_2transform_8h_source.html
+++ b/docs/reference/api/doxygen/topi_2transform_8h_source.html
@@ -74,7 +74,7 @@ $(function() {
<div class="ttc" id="namespacetvm_1_1topi_html_a877e6fdffb6b6c051c29602ec6fe995c"><div class="ttname"><a href="namespacetvm_1_1topi.html#a877e6fdffb6b6c051c29602ec6fe995c">tvm::topi::sparse_to_dense</a></div><div class="ttdeci">Tensor sparse_to_dense(const Tensor &sparse_indices, const Array< PrimExpr > &output_shape, const Tensor &sparse_values, const PrimExpr &default_value, const std::string name="T_sparse_to_dense", const std::string tag=kInjective)</d [...]
<div class="ttc" id="namespacetvm_html_ada5ad8338d3144221d8f16380e6c4855"><div class="ttname"><a href="namespacetvm.html#ada5ad8338d3144221d8f16380e6c4855">tvm::indexmod</a></div><div class="ttdeci">PrimExpr indexmod(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">compute the remainder floor(a / b) where a and b are non-negative. </div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_aff75b2e533b654909ca1bd9485ef4e6b"><div class="ttname"><a href="namespacetvm_1_1topi.html#aff75b2e533b654909ca1bd9485ef4e6b">tvm::topi::StridedSliceOutputShape</a></div><div class="ttdeci">Array< PrimExpr > StridedSliceOutputShape(const Array< PrimExpr > &ishape, const Array< Integer > &begin, const Array< Integer > &end, const Array< Integer > &strides, const Array< Integer > &axes, co [...]
-<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:943</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_a1a071208bbbab6b220cf46f5cdccdd86"><div class="ttname"><a href="namespacetvm_1_1tir.html#a1a071208bbbab6b220cf46f5cdccdd86">tvm::tir::make_const</a></div><div class="ttdeci">PrimExpr make_const(DataType t, ValueType value, Span span=Span())</div><div class="ttdoc">Make a const value with certain data type. </div><div class="ttdef"><b>Definition:</b> op.h:942</div></div>
<div class="ttc" id="classtvm_1_1Range_html_a91e7301ca1d135ca5f8ed199efbb9818"><div class="ttname"><a href="classtvm_1_1Range.html#a91e7301ca1d135ca5f8ed199efbb9818">tvm::Range::FromMinExtent</a></div><div class="ttdeci">static Range FromMinExtent(PrimExpr min, PrimExpr extent, Span span=Span())</div><div class="ttdoc">construct a new range with min and extent The corresponding constructor is removed, because that is counter convention of tradition meaning of range(begin, end) </div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a3230e1735957c2045c89cf190e0f8c34"><div class="ttname"><a href="namespacetvm_1_1topi.html#a3230e1735957c2045c89cf190e0f8c34">tvm::topi::sliding_window</a></div><div class="ttdeci">Tensor sliding_window(const Tensor &x, int axis, Array< Integer > window_shape, Array< Integer > strides, std::string name="T_sliding_window", std::string tag="")</div><div class="ttdoc">Creates an operation to slide a window ove [...]
<div class="ttc" id="namespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript. </div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
@@ -129,7 +129,7 @@ $(function() {
<div class="ttc" id="namespacetvm_html_a0df5ca82d2c566f628ebb2f1e84a3fcb"><div class="ttname"><a href="namespacetvm.html#a0df5ca82d2c566f628ebb2f1e84a3fcb">tvm::max</a></div><div class="ttdeci">PrimExpr max(PrimExpr a, PrimExpr b, Span span=Span())</div><div class="ttdoc">take maximum of two values </div></div>
<div class="ttc" id="classtvm_1_1IntImmNode_html_a81f4c116ffb5931fdd64639eacad415d"><div class="ttname"><a href="classtvm_1_1IntImmNode.html#a81f4c116ffb5931fdd64639eacad415d">tvm::IntImmNode::value</a></div><div class="ttdeci">int64_t value</div><div class="ttdoc">the Internal value. </div><div class="ttdef"><b>Definition:</b> expr.h:492</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1String_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html">tvm::runtime::String</a></div><div class="ttdoc">Reference to string objects. </div><div class="ttdef"><b>Definition:</b> string.h:97</div></div>
-<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:951</div></div>
+<div class="ttc" id="namespacetvm_1_1tir_html_aed3f57cf8d1c3546f075701898c5b70f"><div class="ttname"><a href="namespacetvm_1_1tir.html#aed3f57cf8d1c3546f075701898c5b70f">tvm::tir::make_zero</a></div><div class="ttdeci">PrimExpr make_zero(DataType t, Span span=Span())</div><div class="ttdoc">Make a const zero expr. </div><div class="ttdef"><b>Definition:</b> op.h:950</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_af30c02f3a3f37c7963b3af60fb9c72a1"><div class="ttname"><a href="namespacetvm_1_1topi.html#af30c02f3a3f37c7963b3af60fb9c72a1">tvm::topi::shape</a></div><div class="ttdeci">Tensor shape(const Tensor &src, DataType dtype, const std::string name="T_shape", const std::string tag=kInjective)</div><div class="ttdoc">Get the shape of input tensor. </div><div class="ttdef"><b>Definition:</b> transform.h:1758</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_a453f9f5a35a9852a086ce0228ee22164"><div class="ttname"><a href="namespacetvm_1_1topi.html#a453f9f5a35a9852a086ce0228ee22164">tvm::topi::meshgrid</a></div><div class="ttdeci">Array< Tensor > meshgrid(const Array< Tensor > &inputs, const std::string &indexing, std::string name="T_meshgrid", std::string tag=kInjective)</div><div class="ttdoc">Produce grids by expanding input over dimensions defined by other inputs. [...]
<div class="ttc" id="namespacetvm_1_1te_html_aae384e9b73c2271905486e4a74b69265"><div class="ttname"><a href="namespacetvm_1_1te.html#aae384e9b73c2271905486e4a74b69265">tvm::te::reduce_axis</a></div><div class="ttdeci">IterVar reduce_axis(Range dom, std::string name="rv")</div><div class="ttdoc">Create a new IterVar for reduction operations. </div></div>
diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index 1b5ed520d3..23af291e76 100644
--- a/docs/reference/api/python/auto_scheduler.html
+++ b/docs/reference/api/python/auto_scheduler.html
@@ -1615,7 +1615,7 @@ history states as starting point to perform Evolutionary Search).</p></li>
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy">
-<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
+<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
<dd><p>The search policy that searches in a hierarchical search space defined by sketches.
The policy randomly samples programs from the space defined by sketches and use evolutionary
search to fine-tune them.</p>
@@ -1899,7 +1899,7 @@ Candidates:
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.auto_schedule">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
<dd><p>THIS API IS DEPRECATED.</p>
<p>Run auto scheduling search for a task.</p>
<dl class="field-list simple">
diff --git a/docs/reference/api/typedoc/classes/bytestreamreader.html b/docs/reference/api/typedoc/classes/bytestreamreader.html
index 426cdfbb54..148ec29d93 100644
--- a/docs/reference/api/typedoc/classes/bytestreamreader.html
+++ b/docs/reference/api/typedoc/classes/bytestreamreader.html
@@ -119,7 +119,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
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<div class="tsd-signature tsd-kind-icon">bytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Uint8Array</span></div>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
</ul>
</aside>
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<div class="tsd-signature tsd-kind-icon">offset<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 0</span></div>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L42">rpc_server.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L42">rpc_server.ts:42</a></li>
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@@ -168,7 +168,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L63">rpc_server.ts:63</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L63">rpc_server.ts:63</a></li>
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@@ -185,7 +185,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L49">rpc_server.ts:49</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L49">rpc_server.ts:49</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L57">rpc_server.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L57">rpc_server.ts:57</a></li>
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diff --git a/docs/reference/api/typedoc/classes/cachedcallstack.html b/docs/reference/api/typedoc/classes/cachedcallstack.html
index cf10e450c8..b14317b503 100644
--- a/docs/reference/api/typedoc/classes/cachedcallstack.html
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L223">memory.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L223">memory.ts:223</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L208">memory.ts:208</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L208">memory.ts:208</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L312">memory.ts:312</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L312">memory.ts:312</a></li>
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@@ -226,7 +226,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L284">memory.ts:284</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L284">memory.ts:284</a></li>
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@@ -262,7 +262,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L388">memory.ts:388</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L388">memory.ts:388</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L376">memory.ts:376</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L376">memory.ts:376</a></li>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L267">memory.ts:267</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L243">memory.ts:243</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L243">memory.ts:243</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L321">memory.ts:321</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L321">memory.ts:321</a></li>
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@@ -422,7 +422,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L252">memory.ts:252</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L252">memory.ts:252</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L359">memory.ts:359</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L359">memory.ts:359</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L342">memory.ts:342</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L342">memory.ts:342</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L350">memory.ts:350</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L350">memory.ts:350</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L326">memory.ts:326</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L326">memory.ts:326</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L363">memory.ts:363</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L363">memory.ts:363</a></li>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L346">memory.ts:346</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L334">memory.ts:334</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L334">memory.ts:334</a></li>
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index d11f587f4f..7a1050bafc 100644
--- a/docs/reference/api/typedoc/classes/dldatatype.html
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L262">runtime.ts:262</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L262">runtime.ts:262</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L260">runtime.ts:260</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L260">runtime.ts:260</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L258">runtime.ts:258</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L258">runtime.ts:258</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L262">runtime.ts:262</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L262">runtime.ts:262</a></li>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L279">runtime.ts:279</a></li>
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index cb8ec53eda..da1a5328a7 100644
--- a/docs/reference/api/typedoc/classes/dldevice.html
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -146,7 +146,7 @@
<div class="tsd-signature tsd-kind-icon">device<wbr>Id<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L200">runtime.ts:200</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L200">runtime.ts:200</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -161,7 +161,7 @@
<div class="tsd-signature tsd-kind-icon">device<wbr>Type<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L198">runtime.ts:198</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L198">runtime.ts:198</a></li>
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<div class="tsd-comment tsd-typography">
@@ -183,7 +183,7 @@
<li class="tsd-description">
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L223">runtime.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L223">runtime.ts:223</a></li>
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<div class="tsd-comment tsd-typography">
@@ -205,7 +205,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L230">runtime.ts:230</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L230">runtime.ts:230</a></li>
</ul>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4>
diff --git a/docs/reference/api/typedoc/classes/environment.html b/docs/reference/api/typedoc/classes/environment.html
index b434317fbb..a430a631ec 100644
--- a/docs/reference/api/typedoc/classes/environment.html
+++ b/docs/reference/api/typedoc/classes/environment.html
@@ -125,7 +125,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L86">environment.ts:86</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L86">environment.ts:86</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -169,7 +169,7 @@
<aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/libraryprovider.html">LibraryProvider</a>.<a href="../interfaces/libraryprovider.html#imports">imports</a></p>
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L70">environment.ts:70</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L70">environment.ts:70</a></li>
</ul>
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@@ -179,7 +179,7 @@
<div class="tsd-signature tsd-kind-icon">logger<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>msg<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L69">environment.ts:69</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L69">environment.ts:69</a></li>
</ul>
</aside>
<div class="tsd-type-declaration">
@@ -210,7 +210,7 @@
<div class="tsd-signature tsd-kind-icon">packedCFunc<wbr>Table<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Array</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">ctypes.FTVMWasmPackedCFunc</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">undefined</span><span class="tsd-signature-symbol">></span><span class="tsd-signature-symbol"> = [undefined,]</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L78">environment.ts:78</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L78">environment.ts:78</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -228,7 +228,7 @@
<div class="tsd-signature tsd-kind-icon">packedCFunc<wbr>Table<wbr>Free<wbr>Id<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Array</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">></span><span class="tsd-signature-symbol"> = []</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L84">environment.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L84">environment.ts:84</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -250,7 +250,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L105">environment.ts:105</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L105">environment.ts:105</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/ffilibrary.html b/docs/reference/api/typedoc/classes/ffilibrary.html
index b46729de7d..06e50dfb33 100644
--- a/docs/reference/api/typedoc/classes/ffilibrary.html
+++ b/docs/reference/api/typedoc/classes/ffilibrary.html
@@ -131,7 +131,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L49">runtime.ts:49</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L49">runtime.ts:49</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -156,7 +156,7 @@
<div class="tsd-signature tsd-kind-icon">exports<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">></span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L46">runtime.ts:46</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L46">runtime.ts:46</a></li>
</ul>
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@@ -166,7 +166,7 @@
<div class="tsd-signature tsd-kind-icon">memory<span class="tsd-signature-symbol">:</span> <a href="memory.html" class="tsd-signature-type">Memory</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L45">runtime.ts:45</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L45">runtime.ts:45</a></li>
</ul>
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</section>
@@ -176,7 +176,7 @@
<div class="tsd-signature tsd-kind-icon">wasm32<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L44">runtime.ts:44</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L44">runtime.ts:44</a></li>
</ul>
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@@ -186,7 +186,7 @@
<div class="tsd-signature tsd-kind-icon">webGPUContext<span class="tsd-signature-symbol">:</span> <a href="webgpucontext.html" class="tsd-signature-type">WebGPUContext</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L47">runtime.ts:47</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L47">runtime.ts:47</a></li>
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@@ -203,7 +203,7 @@
<li class="tsd-description">
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L76">runtime.ts:76</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L76">runtime.ts:76</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -226,7 +226,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L66">runtime.ts:66</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L66">runtime.ts:66</a></li>
</ul>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -243,7 +243,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L84">runtime.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L84">runtime.ts:84</a></li>
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<h4 class="tsd-returns-title">Returns <a href="cachedcallstack.html" class="tsd-signature-type">CachedCallStack</a></h4>
@@ -260,7 +260,7 @@
<li class="tsd-description">
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L95">runtime.ts:95</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L95">runtime.ts:95</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -283,7 +283,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L72">runtime.ts:72</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L72">runtime.ts:72</a></li>
</ul>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4>
diff --git a/docs/reference/api/typedoc/classes/graphexecutor.html b/docs/reference/api/typedoc/classes/graphexecutor.html
index 50e97c13f6..ae198208c9 100644
--- a/docs/reference/api/typedoc/classes/graphexecutor.html
+++ b/docs/reference/api/typedoc/classes/graphexecutor.html
@@ -130,7 +130,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L583">runtime.ts:583</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L583">runtime.ts:583</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -162,7 +162,7 @@
<div class="tsd-signature tsd-kind-icon">module<span class="tsd-signature-symbol">:</span> <a href="module.html" class="tsd-signature-type">Module</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L579">runtime.ts:579</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L579">runtime.ts:579</a></li>
</ul>
</aside>
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@@ -179,7 +179,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L654">runtime.ts:654</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L654">runtime.ts:654</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -224,7 +224,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L597">runtime.ts:597</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L597">runtime.ts:597</a></li>
</ul>
</aside>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -241,7 +241,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L631">runtime.ts:631</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L631">runtime.ts:631</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -279,7 +279,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L644">runtime.ts:644</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L644">runtime.ts:644</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -310,7 +310,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L621">runtime.ts:621</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L621">runtime.ts:621</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -332,7 +332,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L609">runtime.ts:609</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L609">runtime.ts:609</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/instance.html b/docs/reference/api/typedoc/classes/instance.html
index 5bc1b7163a..648f50aa69 100644
--- a/docs/reference/api/typedoc/classes/instance.html
+++ b/docs/reference/api/typedoc/classes/instance.html
@@ -139,7 +139,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L692">runtime.ts:692</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L692">runtime.ts:692</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -202,7 +202,7 @@
<div class="tsd-signature tsd-kind-icon">exports<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">></span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L684">runtime.ts:684</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L684">runtime.ts:684</a></li>
</ul>
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@@ -212,7 +212,7 @@
<div class="tsd-signature tsd-kind-icon">memory<span class="tsd-signature-symbol">:</span> <a href="memory.html" class="tsd-signature-type">Memory</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L683">runtime.ts:683</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L683">runtime.ts:683</a></li>
</ul>
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@@ -229,7 +229,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L932">runtime.ts:932</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L932">runtime.ts:932</a></li>
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<div class="tsd-comment tsd-typography">
@@ -260,7 +260,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L994">runtime.ts:994</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L994">runtime.ts:994</a></li>
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<div class="tsd-comment tsd-typography">
@@ -303,7 +303,7 @@
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<ul>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L924">runtime.ts:924</a></li>
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<div class="tsd-comment tsd-typography">
@@ -341,7 +341,7 @@
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<ul>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L732">runtime.ts:732</a></li>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -358,7 +358,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L952">runtime.ts:952</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L952">runtime.ts:952</a></li>
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<div class="tsd-comment tsd-typography">
@@ -402,7 +402,7 @@
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L816">runtime.ts:816</a></li>
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<div class="tsd-comment tsd-typography">
@@ -434,7 +434,7 @@
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L1033">runtime.ts:1033</a></li>
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<div class="tsd-comment tsd-typography">
@@ -465,7 +465,7 @@
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L846">runtime.ts:846</a></li>
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<div class="tsd-comment tsd-typography">
@@ -497,7 +497,7 @@
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L750">runtime.ts:750</a></li>
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<div class="tsd-comment tsd-typography">
@@ -520,7 +520,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L1013">runtime.ts:1013</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L1013">runtime.ts:1013</a></li>
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@@ -568,7 +568,7 @@
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<ul>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L789">runtime.ts:789</a></li>
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<div class="tsd-comment tsd-typography">
@@ -608,7 +608,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L914">runtime.ts:914</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L914">runtime.ts:914</a></li>
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<div class="tsd-comment tsd-typography">
@@ -646,7 +646,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L1145">runtime.ts:1145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L1145">runtime.ts:1145</a></li>
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<div class="tsd-comment tsd-typography">
@@ -698,7 +698,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L740">runtime.ts:740</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L740">runtime.ts:740</a></li>
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@@ -722,7 +722,7 @@
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<ul>
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+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L868">runtime.ts:868</a></li>
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@@ -754,7 +754,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L857">runtime.ts:857</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L857">runtime.ts:857</a></li>
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<div class="tsd-comment tsd-typography">
@@ -786,7 +786,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L940">runtime.ts:940</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L940">runtime.ts:940</a></li>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/memory.html b/docs/reference/api/typedoc/classes/memory.html
index 0801e4c6ac..ce3dabb1b0 100644
--- a/docs/reference/api/typedoc/classes/memory.html
+++ b/docs/reference/api/typedoc/classes/memory.html
@@ -130,7 +130,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L40">memory.ts:40</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L40">memory.ts:40</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -152,7 +152,7 @@
<div class="tsd-signature tsd-kind-icon">memory<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Memory</span></div>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L32">memory.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L32">memory.ts:32</a></li>
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@@ -162,7 +162,7 @@
<div class="tsd-signature tsd-kind-icon">wasm32<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span><span class="tsd-signature-symbol"> = true</span></div>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L33">memory.ts:33</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L33">memory.ts:33</a></li>
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@@ -179,7 +179,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L154">memory.ts:154</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L154">memory.ts:154</a></li>
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<div class="tsd-comment tsd-typography">
@@ -210,7 +210,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L90">memory.ts:90</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L90">memory.ts:90</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -233,7 +233,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L97">memory.ts:97</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L97">memory.ts:97</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -256,7 +256,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L74">memory.ts:74</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L74">memory.ts:74</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -279,7 +279,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L81">memory.ts:81</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L81">memory.ts:81</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -302,7 +302,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L104">memory.ts:104</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L104">memory.ts:104</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -325,7 +325,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L132">memory.ts:132</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L132">memory.ts:132</a></li>
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<div class="tsd-comment tsd-typography">
@@ -362,7 +362,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L145">memory.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L145">memory.ts:145</a></li>
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<div class="tsd-comment tsd-typography">
@@ -393,7 +393,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L60">memory.ts:60</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L60">memory.ts:60</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -416,7 +416,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L67">memory.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L67">memory.ts:67</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -439,7 +439,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L53">memory.ts:53</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L53">memory.ts:53</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -462,7 +462,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L114">memory.ts:114</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L114">memory.ts:114</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -485,7 +485,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L124">memory.ts:124</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L124">memory.ts:124</a></li>
</ul>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4>
@@ -502,7 +502,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/memory.ts#L175">memory.ts:175</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/memory.ts#L175">memory.ts:175</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/module.html b/docs/reference/api/typedoc/classes/module.html
index e7a1116562..bbca307aed 100644
--- a/docs/reference/api/typedoc/classes/module.html
+++ b/docs/reference/api/typedoc/classes/module.html
@@ -124,7 +124,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L504">runtime.ts:504</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L504">runtime.ts:504</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -170,7 +170,7 @@
<div class="tsd-signature tsd-kind-icon">handle<span class="tsd-signature-symbol">:</span> <a href="../index.html#pointer" class="tsd-signature-type">Pointer</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L502">runtime.ts:502</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L502">runtime.ts:502</a></li>
</ul>
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@@ -187,7 +187,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L516">runtime.ts:516</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L516">runtime.ts:516</a></li>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -204,7 +204,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L530">runtime.ts:530</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L530">runtime.ts:530</a></li>
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<div class="tsd-comment tsd-typography">
@@ -236,7 +236,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L561">runtime.ts:561</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L561">runtime.ts:561</a></li>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/ndarray.html b/docs/reference/api/typedoc/classes/ndarray.html
index 1c84d631b7..aa6139ab04 100644
--- a/docs/reference/api/typedoc/classes/ndarray.html
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@@ -130,7 +130,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L304">runtime.ts:304</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L304">runtime.ts:304</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -158,7 +158,7 @@
<div class="tsd-signature tsd-kind-icon">device<span class="tsd-signature-symbol">:</span> <a href="dldevice.html" class="tsd-signature-type">DLDevice</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L297">runtime.ts:297</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L297">runtime.ts:297</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -173,7 +173,7 @@
<div class="tsd-signature tsd-kind-icon">dtype<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L293">runtime.ts:293</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L293">runtime.ts:293</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -188,7 +188,7 @@
<div class="tsd-signature tsd-kind-icon">handle<span class="tsd-signature-symbol">:</span> <a href="../index.html#pointer" class="tsd-signature-type">Pointer</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L289">runtime.ts:289</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L289">runtime.ts:289</a></li>
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<div class="tsd-comment tsd-typography">
@@ -203,7 +203,7 @@
<div class="tsd-signature tsd-kind-icon">ndim<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L291">runtime.ts:291</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L291">runtime.ts:291</a></li>
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<div class="tsd-comment tsd-typography">
@@ -218,7 +218,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L295">runtime.ts:295</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L295">runtime.ts:295</a></li>
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<div class="tsd-comment tsd-typography">
@@ -240,7 +240,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L370">runtime.ts:370</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L370">runtime.ts:370</a></li>
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<div class="tsd-comment tsd-typography">
@@ -273,7 +273,7 @@
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L414">runtime.ts:414</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L414">runtime.ts:414</a></li>
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<div class="tsd-comment tsd-typography">
@@ -305,7 +305,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L355">runtime.ts:355</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L355">runtime.ts:355</a></li>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -322,7 +322,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L474">runtime.ts:474</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L474">runtime.ts:474</a></li>
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<div class="tsd-comment tsd-typography">
@@ -346,7 +346,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L443">runtime.ts:443</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L443">runtime.ts:443</a></li>
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<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/packedfunccell.html b/docs/reference/api/typedoc/classes/packedfunccell.html
index 1b8905ac1b..0e7d0ced9f 100644
--- a/docs/reference/api/typedoc/classes/packedfunccell.html
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@@ -122,7 +122,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L158">runtime.ts:158</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L158">runtime.ts:158</a></li>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -147,7 +147,7 @@
<div class="tsd-signature tsd-kind-icon">handle<span class="tsd-signature-symbol">:</span> <a href="../index.html#pointer" class="tsd-signature-type">Pointer</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L157">runtime.ts:157</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L157">runtime.ts:157</a></li>
</ul>
</aside>
</section>
@@ -164,7 +164,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L165">runtime.ts:165</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L165">runtime.ts:165</a></li>
</ul>
</aside>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
diff --git a/docs/reference/api/typedoc/classes/rpcserver.html b/docs/reference/api/typedoc/classes/rpcserver.html
index 63d49fcb6d..6c1314f40e 100644
--- a/docs/reference/api/typedoc/classes/rpcserver.html
+++ b/docs/reference/api/typedoc/classes/rpcserver.html
@@ -115,7 +115,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L92">rpc_server.ts:92</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L92">rpc_server.ts:92</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -176,7 +176,7 @@
<div class="tsd-signature tsd-kind-icon">get<wbr>Imports<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">unknown</span><span class="tsd-signat [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li>
</ul>
</aside>
<div class="tsd-type-declaration">
@@ -201,7 +201,7 @@
<div class="tsd-signature tsd-kind-icon">key<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li>
</ul>
</aside>
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@@ -211,7 +211,7 @@
<div class="tsd-signature tsd-kind-icon">logger<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>msg<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li>
</ul>
</aside>
<div class="tsd-type-declaration">
@@ -242,7 +242,7 @@
<div class="tsd-signature tsd-kind-icon">socket<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">WebSocket</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li>
</ul>
</aside>
</section>
@@ -252,7 +252,7 @@
<div class="tsd-signature tsd-kind-icon">state<span class="tsd-signature-symbol">:</span> <a href="../enums/rpcserverstate.html" class="tsd-signature-type">RPCServerState</a><span class="tsd-signature-symbol"> = RPCServerState.InitHeader</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li>
</ul>
</aside>
</section>
@@ -262,7 +262,7 @@
<div class="tsd-signature tsd-kind-icon">url<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/classes/scalar.html b/docs/reference/api/typedoc/classes/scalar.html
index 357f5a150a..aa86050156 100644
--- a/docs/reference/api/typedoc/classes/scalar.html
+++ b/docs/reference/api/typedoc/classes/scalar.html
@@ -112,7 +112,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L145">runtime.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L145">runtime.ts:145</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -137,7 +137,7 @@
<div class="tsd-signature tsd-kind-icon">dtype<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L145">runtime.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L145">runtime.ts:145</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -152,7 +152,7 @@
<div class="tsd-signature tsd-kind-icon">value<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L143">runtime.ts:143</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L143">runtime.ts:143</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/classes/webgpucontext.html b/docs/reference/api/typedoc/classes/webgpucontext.html
index 97f21819dc..f4c0e37093 100644
--- a/docs/reference/api/typedoc/classes/webgpucontext.html
+++ b/docs/reference/api/typedoc/classes/webgpucontext.html
@@ -120,7 +120,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L57">webgpu.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L57">webgpu.ts:57</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -145,7 +145,7 @@
<div class="tsd-signature tsd-kind-icon">device<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">GPUDevice</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L50">webgpu.ts:50</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L50">webgpu.ts:50</a></li>
</ul>
</aside>
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@@ -155,7 +155,7 @@
<div class="tsd-signature tsd-kind-icon">memory<span class="tsd-signature-symbol">:</span> <a href="memory.html" class="tsd-signature-type">Memory</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L51">webgpu.ts:51</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L51">webgpu.ts:51</a></li>
</ul>
</aside>
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@@ -172,7 +172,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L84">webgpu.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L84">webgpu.ts:84</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -209,7 +209,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L170">webgpu.ts:170</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L170">webgpu.ts:170</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -238,7 +238,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L67">webgpu.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L67">webgpu.ts:67</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/enums/argtypecode.html b/docs/reference/api/typedoc/enums/argtypecode.html
index b84231ce12..31319a1017 100644
--- a/docs/reference/api/typedoc/enums/argtypecode.html
+++ b/docs/reference/api/typedoc/enums/argtypecode.html
@@ -106,7 +106,7 @@
<div class="tsd-signature tsd-kind-icon">DLDevice<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 6</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L220">ctypes.ts:220</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L220">ctypes.ts:220</a></li>
</ul>
</aside>
</section>
@@ -116,7 +116,7 @@
<div class="tsd-signature tsd-kind-icon">Float<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 2</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L216">ctypes.ts:216</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L216">ctypes.ts:216</a></li>
</ul>
</aside>
</section>
@@ -126,7 +126,7 @@
<div class="tsd-signature tsd-kind-icon">Int<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 0</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L214">ctypes.ts:214</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L214">ctypes.ts:214</a></li>
</ul>
</aside>
</section>
@@ -136,7 +136,7 @@
<div class="tsd-signature tsd-kind-icon">Null<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L218">ctypes.ts:218</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L218">ctypes.ts:218</a></li>
</ul>
</aside>
</section>
@@ -146,7 +146,7 @@
<div class="tsd-signature tsd-kind-icon">TVMBytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 12</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L226">ctypes.ts:226</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L226">ctypes.ts:226</a></li>
</ul>
</aside>
</section>
@@ -156,7 +156,7 @@
<div class="tsd-signature tsd-kind-icon">TVMDLTensor<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 7</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L221">ctypes.ts:221</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L221">ctypes.ts:221</a></li>
</ul>
</aside>
</section>
@@ -166,7 +166,7 @@
<div class="tsd-signature tsd-kind-icon">TVMData<wbr>Type<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 5</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L219">ctypes.ts:219</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L219">ctypes.ts:219</a></li>
</ul>
</aside>
</section>
@@ -176,7 +176,7 @@
<div class="tsd-signature tsd-kind-icon">TVMModule<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 9</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L223">ctypes.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L223">ctypes.ts:223</a></li>
</ul>
</aside>
</section>
@@ -186,7 +186,7 @@
<div class="tsd-signature tsd-kind-icon">TVMNDArray<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 13</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L227">ctypes.ts:227</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L227">ctypes.ts:227</a></li>
</ul>
</aside>
</section>
@@ -196,7 +196,7 @@
<div class="tsd-signature tsd-kind-icon">TVMObject<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 8</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L222">ctypes.ts:222</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L222">ctypes.ts:222</a></li>
</ul>
</aside>
</section>
@@ -206,7 +206,7 @@
<div class="tsd-signature tsd-kind-icon">TVMObjectRValue<wbr>Ref<wbr>Arg<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 14</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L228">ctypes.ts:228</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L228">ctypes.ts:228</a></li>
</ul>
</aside>
</section>
@@ -216,7 +216,7 @@
<div class="tsd-signature tsd-kind-icon">TVMOpaque<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 3</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L217">ctypes.ts:217</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L217">ctypes.ts:217</a></li>
</ul>
</aside>
</section>
@@ -226,7 +226,7 @@
<div class="tsd-signature tsd-kind-icon">TVMPacked<wbr>Func<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 10</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L224">ctypes.ts:224</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L224">ctypes.ts:224</a></li>
</ul>
</aside>
</section>
@@ -236,7 +236,7 @@
<div class="tsd-signature tsd-kind-icon">TVMStr<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 11</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L225">ctypes.ts:225</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L225">ctypes.ts:225</a></li>
</ul>
</aside>
</section>
@@ -246,7 +246,7 @@
<div class="tsd-signature tsd-kind-icon">UInt<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 1</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L215">ctypes.ts:215</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L215">ctypes.ts:215</a></li>
</ul>
</aside>
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diff --git a/docs/reference/api/typedoc/enums/aynccallbackcode.html b/docs/reference/api/typedoc/enums/aynccallbackcode.html
index fc9af751c5..9b07d15d8a 100644
--- a/docs/reference/api/typedoc/enums/aynccallbackcode.html
+++ b/docs/reference/api/typedoc/enums/aynccallbackcode.html
@@ -93,7 +93,7 @@
<div class="tsd-signature tsd-kind-icon">k<wbr>Exception<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 5</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L676">runtime.ts:676</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L676">runtime.ts:676</a></li>
</ul>
</aside>
</section>
@@ -103,7 +103,7 @@
<div class="tsd-signature tsd-kind-icon">k<wbr>Return<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L675">runtime.ts:675</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L675">runtime.ts:675</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/enums/dldatatypecode.html b/docs/reference/api/typedoc/enums/dldatatypecode.html
index 8f397664ab..c5522bf6a0 100644
--- a/docs/reference/api/typedoc/enums/dldatatypecode.html
+++ b/docs/reference/api/typedoc/enums/dldatatypecode.html
@@ -95,7 +95,7 @@
<div class="tsd-signature tsd-kind-icon">Float<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 2</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L242">runtime.ts:242</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L242">runtime.ts:242</a></li>
</ul>
</aside>
</section>
@@ -105,7 +105,7 @@
<div class="tsd-signature tsd-kind-icon">Int<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 0</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L240">runtime.ts:240</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L240">runtime.ts:240</a></li>
</ul>
</aside>
</section>
@@ -115,7 +115,7 @@
<div class="tsd-signature tsd-kind-icon">Opaque<wbr>Handle<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 3</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L243">runtime.ts:243</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L243">runtime.ts:243</a></li>
</ul>
</aside>
</section>
@@ -125,7 +125,7 @@
<div class="tsd-signature tsd-kind-icon">UInt<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 1</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L241">runtime.ts:241</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L241">runtime.ts:241</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/enums/rpcserverstate.html b/docs/reference/api/typedoc/enums/rpcserverstate.html
index 61b39e429f..0a520cca5a 100644
--- a/docs/reference/api/typedoc/enums/rpcserverstate.html
+++ b/docs/reference/api/typedoc/enums/rpcserverstate.html
@@ -90,7 +90,7 @@
<div class="tsd-signature tsd-kind-icon">Init<wbr>Header<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L27">rpc_server.ts:27</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L27">rpc_server.ts:27</a></li>
</ul>
</aside>
</section>
@@ -100,7 +100,7 @@
<div class="tsd-signature tsd-kind-icon">Init<wbr>Header<wbr>Key<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L28">rpc_server.ts:28</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L28">rpc_server.ts:28</a></li>
</ul>
</aside>
</section>
@@ -110,7 +110,7 @@
<div class="tsd-signature tsd-kind-icon">Init<wbr>Server<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li>
</ul>
</aside>
</section>
@@ -120,7 +120,7 @@
<div class="tsd-signature tsd-kind-icon">Receive<wbr>Packet<wbr>Body<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L32">rpc_server.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L32">rpc_server.ts:32</a></li>
</ul>
</aside>
</section>
@@ -130,7 +130,7 @@
<div class="tsd-signature tsd-kind-icon">Receive<wbr>Packet<wbr>Header<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L31">rpc_server.ts:31</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L31">rpc_server.ts:31</a></li>
</ul>
</aside>
</section>
@@ -140,7 +140,7 @@
<div class="tsd-signature tsd-kind-icon">Wait<wbr>For<wbr>Callback<span class="tsd-signature-symbol">:</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L30">rpc_server.ts:30</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L30">rpc_server.ts:30</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/enums/sizeof.html b/docs/reference/api/typedoc/enums/sizeof.html
index 07163daf66..f0522b25fb 100644
--- a/docs/reference/api/typedoc/enums/sizeof.html
+++ b/docs/reference/api/typedoc/enums/sizeof.html
@@ -100,7 +100,7 @@
<div class="tsd-signature tsd-kind-icon">DLData<wbr>Type<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = I32</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L206">ctypes.ts:206</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L206">ctypes.ts:206</a></li>
</ul>
</aside>
</section>
@@ -110,7 +110,7 @@
<div class="tsd-signature tsd-kind-icon">DLDevice<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = I32 + I32</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L207">ctypes.ts:207</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L207">ctypes.ts:207</a></li>
</ul>
</aside>
</section>
@@ -120,7 +120,7 @@
<div class="tsd-signature tsd-kind-icon">F32<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L203">ctypes.ts:203</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L203">ctypes.ts:203</a></li>
</ul>
</aside>
</section>
@@ -130,7 +130,7 @@
<div class="tsd-signature tsd-kind-icon">F64<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 8</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L204">ctypes.ts:204</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L204">ctypes.ts:204</a></li>
</ul>
</aside>
</section>
@@ -140,7 +140,7 @@
<div class="tsd-signature tsd-kind-icon">I32<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L201">ctypes.ts:201</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L201">ctypes.ts:201</a></li>
</ul>
</aside>
</section>
@@ -150,7 +150,7 @@
<div class="tsd-signature tsd-kind-icon">I64<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 8</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L202">ctypes.ts:202</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L202">ctypes.ts:202</a></li>
</ul>
</aside>
</section>
@@ -160,7 +160,7 @@
<div class="tsd-signature tsd-kind-icon">TVMValue<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 8</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L205">ctypes.ts:205</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L205">ctypes.ts:205</a></li>
</ul>
</aside>
</section>
@@ -170,7 +170,7 @@
<div class="tsd-signature tsd-kind-icon">U16<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 2</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L200">ctypes.ts:200</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L200">ctypes.ts:200</a></li>
</ul>
</aside>
</section>
@@ -180,7 +180,7 @@
<div class="tsd-signature tsd-kind-icon">U8<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol"> = 1</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L199">ctypes.ts:199</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L199">ctypes.ts:199</a></li>
</ul>
</aside>
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diff --git a/docs/reference/api/typedoc/index.html b/docs/reference/api/typedoc/index.html
index 6dd2f28185..4db383b144 100644
--- a/docs/reference/api/typedoc/index.html
+++ b/docs/reference/api/typedoc/index.html
@@ -174,7 +174,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMArray<wbr>Alloc<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>shape<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, ndim<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span>, dtypeCode<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span>, dtypeBits<span class="tsd [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L112">ctypes.ts:112</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L112">ctypes.ts:112</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -238,7 +238,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMArray<wbr>Copy<wbr>From<wbr>Bytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>handle<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, data<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, nbytes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">num [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L128">ctypes.ts:128</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L128">ctypes.ts:128</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -282,7 +282,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMArray<wbr>Copy<wbr>From<wbr>To<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>from<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, to<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, stream<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-sig [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L144">ctypes.ts:144</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L144">ctypes.ts:144</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -326,7 +326,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMArray<wbr>Copy<wbr>ToBytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>handle<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, data<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, nbytes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</sp [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L136">ctypes.ts:136</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L136">ctypes.ts:136</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -370,7 +370,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMArray<wbr>Free<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>handle<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L121">ctypes.ts:121</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L121">ctypes.ts:121</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -406,7 +406,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMBackend<wbr>PackedCFunc<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>argValues<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, argCodes<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, nargs<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number< [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L160">ctypes.ts:160</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L160">ctypes.ts:160</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -458,7 +458,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMCFunc<wbr>Set<wbr>Return<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>ret<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, value<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, typeCode<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signa [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L77">ctypes.ts:77</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L77">ctypes.ts:77</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -506,7 +506,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMCb<wbr>Arg<wbr>ToReturn<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>value<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, code<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span c [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L83">ctypes.ts:83</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L83">ctypes.ts:83</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -545,7 +545,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMFunc<wbr>Call<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>func<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, argValues<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, typeCode<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-t [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L67">ctypes.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L67">ctypes.ts:67</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -601,7 +601,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMFunc<wbr>Free<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>func<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L57">ctypes.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L57">ctypes.ts:57</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -637,7 +637,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMFunc<wbr>Get<wbr>Global<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>name<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, out<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span cla [...]
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L100">ctypes.ts:100</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L100">ctypes.ts:100</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -676,7 +676,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMFunc<wbr>List<wbr>Global<wbr>Names<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>outSize<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, outArray<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> =&g [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L88">ctypes.ts:88</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L88">ctypes.ts:88</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -715,7 +715,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMFunc<wbr>Register<wbr>Global<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>name<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, f<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, override<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</spa [...]
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L94">ctypes.ts:94</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L94">ctypes.ts:94</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -758,7 +758,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMGet<wbr>Last<wbr>Error<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L34">ctypes.ts:34</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L34">ctypes.ts:34</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -788,7 +788,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMMod<wbr>Free<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>mod<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L52">ctypes.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L52">ctypes.ts:52</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -824,7 +824,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMMod<wbr>Get<wbr>Function<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>mod<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, funcName<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, queryImports<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">numbe [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L42">ctypes.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L42">ctypes.ts:42</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -872,7 +872,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMMod<wbr>Import<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>mod<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, dep<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-si [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L48">ctypes.ts:48</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L48">ctypes.ts:48</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -912,7 +912,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMSynchronize<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>deviceType<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span>, deviceId<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span>, stream<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signatur [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L150">ctypes.ts:150</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L150">ctypes.ts:150</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -954,7 +954,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMWasm<wbr>Alloc<wbr>Space<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>size<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L167">ctypes.ts:167</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L167">ctypes.ts:167</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -990,7 +990,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMWasm<wbr>Free<wbr>Space<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>ptr<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L170">ctypes.ts:170</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L170">ctypes.ts:170</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1026,7 +1026,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMWasm<wbr>Func<wbr>Create<wbr>FromCFunc<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>resource<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, out<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> =&g [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L187">ctypes.ts:187</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L187">ctypes.ts:187</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1066,7 +1066,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMWasm<wbr>PackedCFunc<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>args<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, typeCodes<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a>, nargs<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span>, [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L179">ctypes.ts:179</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L179">ctypes.ts:179</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1118,7 +1118,7 @@
<div class="tsd-signature tsd-kind-icon">FTVMWasm<wbr>PackedCFunc<wbr>Finalizer<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>resourceHandle<span class="tsd-signature-symbol">: </span><a href="index.html#pointer" class="tsd-signature-type">Pointer</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L193">ctypes.ts:193</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L193">ctypes.ts:193</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1154,7 +1154,7 @@
<div class="tsd-signature tsd-kind-icon">GPUPointer<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L25">webgpu.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L25">webgpu.ts:25</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1169,7 +1169,7 @@
<div class="tsd-signature tsd-kind-icon">Packed<wbr>Func<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">...</span>args<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> & </span><a href="interfaces/disp [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L36">runtime.ts:36</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L36">runtime.ts:36</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1184,7 +1184,7 @@
<div class="tsd-signature tsd-kind-icon">Pointer<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L25">ctypes.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L25">ctypes.ts:25</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1199,7 +1199,7 @@
<div class="tsd-signature tsd-kind-icon">Ptr<wbr>Offset<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/ctypes.ts#L28">ctypes.ts:28</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/ctypes.ts#L28">ctypes.ts:28</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1217,7 +1217,7 @@
<div class="tsd-signature tsd-kind-icon">RPC_<wbr>MAGIC<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">1045105</span><span class="tsd-signature-symbol"> = 1045105</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/rpc_server.ts#L36">rpc_server.ts:36</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/rpc_server.ts#L36">rpc_server.ts:36</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1239,7 +1239,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/support.ts#L25">support.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/support.ts#L25">support.ts:25</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1271,7 +1271,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/support.ts#L39">support.ts:39</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/support.ts#L39">support.ts:39</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1300,7 +1300,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/support.ts#L52">support.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/support.ts#L52">support.ts:52</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1337,7 +1337,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/compact.ts#L38">compact.ts:38</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/compact.ts#L38">compact.ts:38</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1368,7 +1368,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L30">webgpu.ts:30</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L30">webgpu.ts:30</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1390,7 +1390,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/environment.ts#L32">environment.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/environment.ts#L32">environment.ts:32</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1421,7 +1421,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/compact.ts#L24">compact.ts:24</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/compact.ts#L24">compact.ts:24</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1443,7 +1443,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L1367">runtime.ts:1367</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L1367">runtime.ts:1367</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1508,7 +1508,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/support.ts#L62">support.ts:62</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/support.ts#L62">support.ts:62</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -1530,7 +1530,7 @@
<div class="tsd-signature tsd-kind-icon">DLData<wbr>Type<wbr>Code<wbr>ToStr<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">object</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L246">runtime.ts:246</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L246">runtime.ts:246</a></li>
</ul>
</aside>
<section class="tsd-panel tsd-member tsd-kind-variable tsd-parent-kind-object-literal">
@@ -1539,7 +1539,7 @@
<div class="tsd-signature tsd-kind-icon">0<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "int"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L247">runtime.ts:247</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L247">runtime.ts:247</a></li>
</ul>
</aside>
</section>
@@ -1549,7 +1549,7 @@
<div class="tsd-signature tsd-kind-icon">1<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "uint"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L248">runtime.ts:248</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L248">runtime.ts:248</a></li>
</ul>
</aside>
</section>
@@ -1559,7 +1559,7 @@
<div class="tsd-signature tsd-kind-icon">2<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "float"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L249">runtime.ts:249</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L249">runtime.ts:249</a></li>
</ul>
</aside>
</section>
@@ -1569,7 +1569,7 @@
<div class="tsd-signature tsd-kind-icon">3<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "handle"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L250">runtime.ts:250</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L250">runtime.ts:250</a></li>
</ul>
</aside>
</section>
@@ -1580,7 +1580,7 @@
<div class="tsd-signature tsd-kind-icon">Device<wbr>Enum<wbr>ToStr<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">object</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L175">runtime.ts:175</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L175">runtime.ts:175</a></li>
</ul>
</aside>
<section class="tsd-panel tsd-member tsd-kind-variable tsd-parent-kind-object-literal">
@@ -1589,7 +1589,7 @@
<div class="tsd-signature tsd-kind-icon">1<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "cpu"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L176">runtime.ts:176</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L176">runtime.ts:176</a></li>
</ul>
</aside>
</section>
@@ -1599,7 +1599,7 @@
<div class="tsd-signature tsd-kind-icon">15<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "webgpu"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L180">runtime.ts:180</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L180">runtime.ts:180</a></li>
</ul>
</aside>
</section>
@@ -1609,7 +1609,7 @@
<div class="tsd-signature tsd-kind-icon">2<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "cuda"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L177">runtime.ts:177</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L177">runtime.ts:177</a></li>
</ul>
</aside>
</section>
@@ -1619,7 +1619,7 @@
<div class="tsd-signature tsd-kind-icon">4<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "opencl"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L178">runtime.ts:178</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L178">runtime.ts:178</a></li>
</ul>
</aside>
</section>
@@ -1629,7 +1629,7 @@
<div class="tsd-signature tsd-kind-icon">8<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = "metal"</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L179">runtime.ts:179</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L179">runtime.ts:179</a></li>
</ul>
</aside>
</section>
@@ -1640,7 +1640,7 @@
<div class="tsd-signature tsd-kind-icon">Device<wbr>Str<wbr>ToEnum<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">object</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L183">runtime.ts:183</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L183">runtime.ts:183</a></li>
</ul>
</aside>
<section class="tsd-panel tsd-member tsd-kind-variable tsd-parent-kind-object-literal">
@@ -1649,7 +1649,7 @@
<div class="tsd-signature tsd-kind-icon">cl<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L186">runtime.ts:186</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L186">runtime.ts:186</a></li>
</ul>
</aside>
</section>
@@ -1659,7 +1659,7 @@
<div class="tsd-signature tsd-kind-icon">cpu<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 1</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L184">runtime.ts:184</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L184">runtime.ts:184</a></li>
</ul>
</aside>
</section>
@@ -1669,7 +1669,7 @@
<div class="tsd-signature tsd-kind-icon">cuda<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 2</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L185">runtime.ts:185</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L185">runtime.ts:185</a></li>
</ul>
</aside>
</section>
@@ -1679,7 +1679,7 @@
<div class="tsd-signature tsd-kind-icon">metal<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 8</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L189">runtime.ts:189</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L189">runtime.ts:189</a></li>
</ul>
</aside>
</section>
@@ -1689,7 +1689,7 @@
<div class="tsd-signature tsd-kind-icon">opencl<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 4</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L187">runtime.ts:187</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L187">runtime.ts:187</a></li>
</ul>
</aside>
</section>
@@ -1699,7 +1699,7 @@
<div class="tsd-signature tsd-kind-icon">vulkan<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 7</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L188">runtime.ts:188</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L188">runtime.ts:188</a></li>
</ul>
</aside>
</section>
@@ -1709,7 +1709,7 @@
<div class="tsd-signature tsd-kind-icon">webgpu<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 15</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/runtime.ts#L190">runtime.ts:190</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/runtime.ts#L190">runtime.ts:190</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/interfaces/disposable.html b/docs/reference/api/typedoc/interfaces/disposable.html
index 0d4cba6ee2..d18634345e 100644
--- a/docs/reference/api/typedoc/interfaces/disposable.html
+++ b/docs/reference/api/typedoc/interfaces/disposable.html
@@ -113,7 +113,7 @@
<div class="tsd-signature tsd-kind-icon">dispose<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/types.ts#L52">types.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/types.ts#L52">types.ts:52</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
diff --git a/docs/reference/api/typedoc/interfaces/functioninfo.html b/docs/reference/api/typedoc/interfaces/functioninfo.html
index b7d0037bb2..802c248e3e 100644
--- a/docs/reference/api/typedoc/interfaces/functioninfo.html
+++ b/docs/reference/api/typedoc/interfaces/functioninfo.html
@@ -95,7 +95,7 @@
<div class="tsd-signature tsd-kind-icon">arg_<wbr>types<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Array</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">></span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L41">webgpu.ts:41</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L41">webgpu.ts:41</a></li>
</ul>
</aside>
</section>
@@ -105,7 +105,7 @@
<div class="tsd-signature tsd-kind-icon">launch_<wbr>param_<wbr>tags<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Array</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">></span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L42">webgpu.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L42">webgpu.ts:42</a></li>
</ul>
</aside>
</section>
@@ -115,7 +115,7 @@
<div class="tsd-signature tsd-kind-icon">name<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/webgpu.ts#L40">webgpu.ts:40</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/webgpu.ts#L40">webgpu.ts:40</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/interfaces/libraryprovider.html b/docs/reference/api/typedoc/interfaces/libraryprovider.html
index 3faf600944..24917ab906 100644
--- a/docs/reference/api/typedoc/interfaces/libraryprovider.html
+++ b/docs/reference/api/typedoc/interfaces/libraryprovider.html
@@ -112,7 +112,7 @@
<div class="tsd-signature tsd-kind-icon">imports<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol">></span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/types.ts#L34">types.ts:34</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/types.ts#L34">types.ts:34</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -127,7 +127,7 @@
<div class="tsd-signature tsd-kind-icon">start<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span>inst<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Instance</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/d31a1fb0d/web/src/types.ts#L39">types.ts:39</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/3a81aef40/web/src/types.ts#L39">types.ts:39</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
diff --git a/docs/searchindex.js b/docs/searchindex.js
index 5bee7c1e4e..b517a93980 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
... 803 lines suppressed ...