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Posted to commits@tvm.apache.org by tq...@apache.org on 2022/06/27 20:13:22 UTC
[tvm-site] branch asf-site updated: deploying docs (apache/tvm@45568c9963fae1ea44a63cfd77b728471503ebff)
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 6296473a0 deploying docs (apache/tvm@45568c9963fae1ea44a63cfd77b728471503ebff)
6296473a0 is described below
commit 6296473a08b9aade3eaf7641be5921691eede0b2
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Mon Jun 27 20:13:14 2022 +0000
deploying docs (apache/tvm@45568c9963fae1ea44a63cfd77b728471503ebff)
---
.../how_to/compile_models/from_coreml.rst.txt | 2 +-
.../how_to/compile_models/from_darknet.rst.txt | 7 +-
.../how_to/compile_models/from_mxnet.rst.txt | 4 +-
.../how_to/compile_models/from_oneflow.rst.txt | 4 +-
.../how_to/compile_models/from_onnx.rst.txt | 2 +-
.../how_to/compile_models/from_paddle.rst.txt | 4 +-
.../how_to/compile_models/from_pytorch.rst.txt | 4 +-
.../how_to/compile_models/from_tensorflow.rst.txt | 4 +-
.../how_to/compile_models/from_tflite.rst.txt | 2 +-
.../compile_models/sg_execution_times.rst.txt | 22 +-
.../deploy_models/deploy_model_on_android.rst.txt | 4 +-
.../deploy_models/deploy_model_on_rasp.rst.txt | 2 +-
.../deploy_object_detection_pytorch.rst.txt | 6 +-
.../deploy_models/deploy_prequantized.rst.txt | 8 +-
.../deploy_prequantized_tflite.rst.txt | 6 +-
.../how_to/deploy_models/deploy_quantized.rst.txt | 4 +-
.../deploy_models/deploy_ssd_gluoncv.rst.txt | 6 +-
.../deploy_models/sg_execution_times.rst.txt | 16 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 12 +-
.../how_to/extend_tvm/sg_execution_times.rst.txt | 8 +-
.../how_to/extend_tvm/use_pass_infra.rst.txt | 10 +-
.../how_to/extend_tvm/use_pass_instrument.rst.txt | 18 +-
.../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 | 4 +-
.../tune_network_arm.rst.txt | 2 +-
.../tune_network_cuda.rst.txt | 6 +-
.../tune_network_mali.rst.txt | 2 +-
.../tune_network_x86.rst.txt | 8 +-
.../tune_sparse_x86.rst.txt | 37 +-
.../tune_with_autotvm/sg_execution_times.rst.txt | 6 +-
.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 98 +--
.../work_with_microtvm/micro_autotune.rst.txt | 20 +-
.../how_to/work_with_microtvm/micro_train.rst.txt | 18 +-
.../work_with_microtvm/sg_execution_times.rst.txt | 8 +-
.../work_with_relay/sg_execution_times.rst.txt | 6 +-
.../work_with_relay/using_external_lib.rst.txt | 4 +-
.../how_to/work_with_schedules/intrin_math.rst.txt | 2 +-
.../work_with_schedules/sg_execution_times.rst.txt | 14 +-
.../how_to/work_with_schedules/tensorize.rst.txt | 2 +-
.../tutorials/autotvm/sg_execution_times.rst.txt | 4 +-
.../vta/tutorials/autotvm/tune_relay_vta.rst.txt | 2 +-
.../frontend/deploy_classification.rst.txt | 4 +-
.../tutorials/frontend/deploy_detection.rst.txt | 4 +-
.../tutorials/frontend/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/matrix_multiply.rst.txt | 2 +-
.../vta/tutorials/optimize/convolution_opt.rst.txt | 2 +-
.../tutorials/optimize/matrix_multiply_opt.rst.txt | 2 +-
.../tutorials/optimize/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/vta_get_started.rst.txt | 2 +-
.../tutorial/auto_scheduler_matmul_x86.rst.txt | 4 +-
docs/_sources/tutorial/autotvm_matmul_x86.rst.txt | 20 +-
docs/_sources/tutorial/autotvm_relay_x86.rst.txt | 60 +-
.../tutorial/cross_compilation_and_rpc.rst.txt | 2 +-
docs/_sources/tutorial/intro_topi.rst.txt | 2 +-
docs/_sources/tutorial/relay_quick_start.rst.txt | 2 +-
docs/_sources/tutorial/sg_execution_times.rst.txt | 20 +-
.../tutorial/tensor_expr_get_started.rst.txt | 65 +-
docs/commit_hash | 2 +-
docs/genindex.html | 6 +-
docs/how_to/compile_models/from_coreml.html | 2 +-
docs/how_to/compile_models/from_darknet.html | 3 +-
docs/how_to/compile_models/from_mxnet.html | 4 +-
docs/how_to/compile_models/from_oneflow.html | 75 +-
docs/how_to/compile_models/from_onnx.html | 2 +-
docs/how_to/compile_models/from_paddle.html | 4 +-
docs/how_to/compile_models/from_pytorch.html | 8 +-
docs/how_to/compile_models/from_tensorflow.html | 4 +-
docs/how_to/compile_models/from_tflite.html | 2 +-
docs/how_to/compile_models/sg_execution_times.html | 26 +-
.../deploy_models/deploy_model_on_android.html | 4 +-
.../how_to/deploy_models/deploy_model_on_rasp.html | 2 +-
.../deploy_object_detection_pytorch.html | 36 +-
docs/how_to/deploy_models/deploy_prequantized.html | 12 +-
.../deploy_models/deploy_prequantized_tflite.html | 6 +-
docs/how_to/deploy_models/deploy_quantized.html | 4 +-
docs/how_to/deploy_models/deploy_ssd_gluoncv.html | 38 +-
docs/how_to/deploy_models/sg_execution_times.html | 16 +-
.../extend_tvm/bring_your_own_datatypes.html | 12 +-
docs/how_to/extend_tvm/sg_execution_times.html | 8 +-
docs/how_to/extend_tvm/use_pass_infra.html | 10 +-
docs/how_to/extend_tvm/use_pass_instrument.html | 18 +-
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 | 4 +-
.../tune_with_autoscheduler/tune_network_arm.html | 2 +-
.../tune_with_autoscheduler/tune_network_cuda.html | 6 +-
.../tune_with_autoscheduler/tune_network_mali.html | 2 +-
.../tune_with_autoscheduler/tune_network_x86.html | 8 +-
.../tune_with_autoscheduler/tune_sparse_x86.html | 37 +-
.../tune_with_autotvm/sg_execution_times.html | 6 +-
.../how_to/tune_with_autotvm/tune_conv2d_cuda.html | 98 +--
docs/how_to/work_with_microtvm/micro_autotune.html | 20 +-
docs/how_to/work_with_microtvm/micro_train.html | 18 +-
.../work_with_microtvm/sg_execution_times.html | 8 +-
.../how_to/work_with_relay/sg_execution_times.html | 6 +-
.../how_to/work_with_relay/using_external_lib.html | 4 +-
docs/how_to/work_with_schedules/intrin_math.html | 2 +-
.../work_with_schedules/sg_execution_times.html | 14 +-
docs/how_to/work_with_schedules/tensorize.html | 2 +-
docs/objects.inv | Bin 22518 -> 22525 bytes
...stvm_1_1meta__schedule_1_1Postproc-members.html | 19 +-
.../classtvm_1_1meta__schedule_1_1Postproc.html | 36 +-
..._1_1meta__schedule_1_1Postproc__coll__graph.svg | 117 +--
...1meta__schedule_1_1Postproc__inherit__graph.svg | 89 +-
docs/reference/api/doxygen/functions_func_r.html | 3 +-
docs/reference/api/doxygen/functions_r.html | 7 +-
docs/reference/api/doxygen/namespacemembers.html | 3 +
.../api/doxygen/namespacemembers_func.html | 3 +
.../api/doxygen/namespacemembers_func_p.html | 6 +-
docs/reference/api/doxygen/namespacemembers_p.html | 6 +-
.../namespacetvm_1_1relay_1_1transform.html | 23 +
docs/reference/api/doxygen/postproc_8h_source.html | 2 +-
.../reference/api/doxygen/relay_2transform_8h.html | 3 +
.../api/doxygen/relay_2transform_8h_source.html | 3 +-
docs/reference/api/doxygen/search/all_11.js | 2 +-
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docs/reference/api/doxygen/search/functions_10.js | 2 +-
docs/reference/api/doxygen/search/functions_12.js | 2 +-
docs/reference/api/python/auto_scheduler.html | 935 +++++++++++----------
.../api/typedoc/classes/bytestreamreader.html | 12 +-
.../api/typedoc/classes/cachedcallstack.html | 34 +-
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 +-
docs/reference/api/typedoc/classes/rpcserver.html | 14 +-
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 +-
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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 +-
.../vta/tutorials/autotvm/tune_relay_vta.html | 2 +-
.../tutorials/frontend/deploy_classification.html | 4 +-
.../vta/tutorials/frontend/deploy_detection.html | 4 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/matrix_multiply.html | 2 +-
.../vta/tutorials/optimize/convolution_opt.html | 2 +-
.../tutorials/optimize/matrix_multiply_opt.html | 2 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/vta_get_started.html | 2 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 3 +-
docs/tutorial/autotvm_matmul_x86.html | 20 +-
docs/tutorial/autotvm_relay_x86.html | 264 +++---
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/relay_quick_start.html | 2 +-
docs/tutorial/sg_execution_times.html | 26 +-
docs/tutorial/tensor_expr_get_started.html | 61 +-
174 files changed, 1730 insertions(+), 1647 deletions(-)
diff --git a/docs/_sources/how_to/compile_models/from_coreml.rst.txt b/docs/_sources/how_to/compile_models/from_coreml.rst.txt
index 9ba283893..220de9daf 100644
--- a/docs/_sources/how_to/compile_models/from_coreml.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_coreml.rst.txt
@@ -129,7 +129,7 @@ We should be familiar with the process right now.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 095f910b7..a2e587166 100644
--- a/docs/_sources/how_to/compile_models/from_darknet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
@@ -164,7 +164,7 @@ compile the model
.. code-block:: none
Compiling the model...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -314,6 +314,11 @@ The process is no different from other examples.
+.. rst-class:: sphx-glr-timing
+
+ **Total running time of the script:** ( 1 minutes 2.172 seconds)
+
+
.. _sphx_glr_download_how_to_compile_models_from_darknet.py:
.. only:: html
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 822d18c0a..541d15664 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -114,7 +114,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip98c04dbf-e0cd-4043-9e3d-e75192fa8da2 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip1df7e179-acbf-4f0c-828a-5f4c922613a1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
@@ -165,7 +165,7 @@ now compile the graph
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 d93faa0e5..cfa72ccfa 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -112,7 +112,7 @@ 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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@@ -209,7 +209,7 @@ Compile the graph to llvm target with given input specification.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/_sources/how_to/compile_models/from_onnx.rst.txt b/docs/_sources/how_to/compile_models/from_onnx.rst.txt
index 131561a7d..5e6ffddbb 100644
--- a/docs/_sources/how_to/compile_models/from_onnx.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_onnx.rst.txt
@@ -154,7 +154,7 @@ provides a static definition of the input size.
==> Context: Bad node spec for node. Name: OpType: Conv
warnings.warn(str(e))
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/_sources/how_to/compile_models/from_paddle.rst.txt b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
index 39e8c8969..e70814a12 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -167,7 +167,7 @@ Compile the model with relay
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -235,7 +235,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 6.008 seconds)
+ **Total running time of the script:** ( 1 minutes 6.757 seconds)
.. _sphx_glr_download_how_to_compile_models_from_paddle.py:
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 ac1647a7b..262a8c73e 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -93,7 +93,7 @@ Load a pretrained PyTorch model
.. code-block:: none
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
-
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77%|#######6 | 34.3M/44.7M [00:00<00:00, 136MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 132MB/s]
+
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100%|##########| 44.7M/44.7M [00:00<00:00, 248MB/s]
@@ -179,7 +179,7 @@ Compile the graph to llvm target with given input specification.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 ff7662c23..cfabf88fd 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -263,7 +263,7 @@ Results:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -422,7 +422,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 0.400 seconds)
+ **Total running time of the script:** ( 1 minutes 5.055 seconds)
.. _sphx_glr_download_how_to_compile_models_from_tensorflow.py:
diff --git a/docs/_sources/how_to/compile_models/from_tflite.rst.txt b/docs/_sources/how_to/compile_models/from_tflite.rst.txt
index f33298f4d..7233c1336 100644
--- a/docs/_sources/how_to/compile_models/from_tflite.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tflite.rst.txt
@@ -210,7 +210,7 @@ Compile the model with relay
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 0b495aa44..017974eea 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
=================
-**05:36.919** total execution time for **how_to_compile_models** files:
+**05:41.893** total execution time for **how_to_compile_models** files:
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:06.008 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:06.757 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:00.400 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:05.055 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 00:56.749 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:02.172 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:32.634 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:31.783 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:31.184 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:27.091 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:24.255 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:23.727 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:22.829 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:22.617 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:21.188 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:21.223 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:19.031 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:18.712 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.641 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.755 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
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 be8589c09..ff88523c2 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
@@ -352,7 +352,7 @@ to run this tutorial with a real device.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -440,7 +440,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.1850 16.2433 16.5122 15.8083 0.2441
+ 15.6855 15.6750 15.8212 15.5999 0.0721
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_rasp.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_rasp.rst.txt
index 7dfc76270..ea87701ff 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_rasp.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_rasp.rst.txt
@@ -294,7 +294,7 @@ to run this tutorial with a real device.
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 1ac3ce9d9..80e61a8ca 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
@@ -122,7 +122,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
.. code-block:: none
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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96
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/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3878: 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)
/usr/local/lib/python3.7/dist-packages/torchvision/models/detection/anchor_utils.py:127: 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').
@@ -229,7 +229,7 @@ torchvision rcnn models.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -291,7 +291,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 52.786 seconds)
+ **Total running time of the script:** ( 2 minutes 51.947 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 d9a98984c..bf154ac41 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -219,7 +219,7 @@ training. Other models require a full post training calibration.
.. code-block:: none
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
-
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44%|####4 | 6.00M/13.6M [00:00<00:00, 23.6MB/s]
89%|########8 | 12.1M/13.6M [00:00<00:00, 39.3MB/s]
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+
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@@ -314,7 +314,7 @@ standard Relay operators before compilation.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -399,7 +399,7 @@ 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)
- 90.4271 90.1947 109.4979 90.0612 1.9289
+ 90.4856 90.1853 101.7039 90.0492 1.6106
@@ -448,7 +448,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 6.230 seconds)
+ **Total running time of the script:** ( 1 minutes 5.382 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 bc182fd53..a025bd1ea 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
@@ -345,7 +345,7 @@ target platform that you are interested in.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -426,7 +426,7 @@ 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)
- 119.3406 119.2620 125.8968 118.1237 0.7838
+ 119.1273 119.1052 121.3175 118.3462 0.3792
@@ -463,7 +463,7 @@ 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 1.296 seconds)
+ **Total running time of the script:** ( 1 minutes 51.042 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 d1fb6f9be..60573624d 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -243,7 +243,7 @@ We create a Relay VM to build and execute the model.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
@@ -254,7 +254,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 9.842 seconds)
+ **Total running time of the script:** ( 1 minutes 41.030 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 1765d0e15..4d38e8099 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
@@ -157,7 +157,7 @@ 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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+
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@@ -202,7 +202,7 @@ Create TVM runtime and do inference
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -240,7 +240,7 @@ Display result
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 15.999 seconds)
+ **Total running time of the script:** ( 2 minutes 17.215 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 904e017b1..9e9c01112 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
@@ -5,22 +5,22 @@
Computation times
=================
-**10:16.443** total execution time for **how_to_deploy_models** files:
+**10:36.230** 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``) | 02:52.786 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 02:51.947 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 02:15.999 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 02:17.215 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 02:01.296 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 01:51.042 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:09.842 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:41.030 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:06.230 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:05.382 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:28.513 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:28.018 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:21.772 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:21.591 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.006 | 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 517017aa5..75054db24 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
@@ -134,7 +134,7 @@ Finally, we're ready to run the program:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
z: [0.7996937 1.168008 1.4516819]
@@ -401,7 +401,7 @@ while for all other operations, the bit length is the same between the operands
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
z: [0.7996937 1.168008 1.4516819]
x: [0.51729786 0.9469626 0.7654598 ]
@@ -463,7 +463,7 @@ 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.zip5750d5e2-eb50-4c4f-bdbf-e2684b503453 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip558f0a51-16eb-4b4d-9d50-3adfd645b3ce from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
@@ -491,7 +491,7 @@ It's easy to execute MobileNet with native TVM:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
[ -7.5350165 2.0368009 -12.706646 -5.63786 -12.684058 4.0723605
2.618876 3.4049501 -9.867913 -24.53311 ]
@@ -575,7 +575,7 @@ Now, to actually convert the entire network, we have written `a pass in Relay <h
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Check failed: (lower) is false: FloatImm lowering function for target llvm type 150 not found
@@ -703,7 +703,7 @@ Now we can finally run the model:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
[ -7.5350165 2.0368009 -12.706646 -5.63786 -12.684058 4.0723605
2.618876 3.4049501 -9.867913 -24.53311 ]
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 66957fe88..111083dad 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
=================
-**00:38.162** total execution time for **how_to_extend_tvm** files:
+**00:38.898** 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``) | 00:35.029 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:35.711 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.248 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.269 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:00.878 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:00.912 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``) | 00:00.006 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/use_pass_infra.rst.txt b/docs/_sources/how_to/extend_tvm/use_pass_infra.rst.txt
index f3cdac1a0..9e167e49a 100644
--- a/docs/_sources/how_to/extend_tvm/use_pass_infra.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/use_pass_infra.rst.txt
@@ -137,7 +137,7 @@ Manually Apply Optimization Passes
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%0 = nn.conv2d(%x, %weight, padding=[0, 0, 0, 0]) /* ty=Tensor[(1, 64, 54, 54), float32] */;
@@ -281,7 +281,7 @@ pass.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%4 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -326,7 +326,7 @@ for users to customize the optimization level that they want to execute.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%3 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -370,7 +370,7 @@ identical addition operations.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%4 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -560,7 +560,7 @@ a PassInsturment class printing IR before execution of each passes:
}
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Running pass: {} The meta data of the pass - pass name: InferType, opt_level: 0, required passes: []
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 570705a4c..6e0256eea 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
@@ -215,10 +215,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 6714us [6714us] (45.57%; 45.57%)
- FoldScaleAxis: 8021us [6us] (54.43%; 54.43%)
- FoldConstant: 8015us [1647us] (54.40%; 99.93%)
- InferType: 6368us [6368us] (43.22%; 79.45%)
+ InferType: 6777us [6777us] (45.37%; 45.37%)
+ FoldScaleAxis: 8162us [6us] (54.63%; 54.63%)
+ FoldConstant: 8156us [1631us] (54.60%; 99.93%)
+ InferType: 6526us [6526us] (43.68%; 80.01%)
@@ -257,10 +257,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 6370us [6370us] (44.71%; 44.71%)
- FoldScaleAxis: 7876us [5us] (55.29%; 55.29%)
- FoldConstant: 7871us [1617us] (55.25%; 99.94%)
- InferType: 6255us [6255us] (43.90%; 79.46%)
+ InferType: 6586us [6586us] (44.84%; 44.84%)
+ FoldScaleAxis: 8103us [5us] (55.16%; 55.16%)
+ FoldConstant: 8098us [1661us] (55.13%; 99.94%)
+ InferType: 6437us [6437us] (43.82%; 79.49%)
@@ -432,7 +432,7 @@ profile result.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 075d03d5e..e66f97dfa 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
@@ -327,7 +327,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 33.790407 ms
+ Convolution: 54.186354 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 0f7f54e9f..e488d0ff5 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
@@ -658,7 +658,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 8.223372 ms
+ conv2d with tensor core: 8.680402 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 12058dd7f..a662043a4 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -130,8 +130,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.017745
- Baseline: 3.426559
+ Numpy running time: 0.017968
+ Baseline: 3.258221
@@ -226,7 +226,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.295974
+ Opt1: 0.298263
@@ -329,7 +329,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.319055
+ Opt2: 0.325893
@@ -425,7 +425,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.114382
+ Opt3: 0.116564
@@ -550,7 +550,7 @@ flattening.
.. code-block:: none
- Opt4: 0.109475
+ Opt4: 0.110210
@@ -672,7 +672,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.108775
+ Opt5: 0.111226
@@ -797,7 +797,7 @@ Futhermore, we can also utilize multi-core processors to do the thread-level par
.. code-block:: none
- Opt6: 0.142174
+ Opt6: 0.145373
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 c022e5a74..3e70df200 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
=================
-**00:33.859** total execution time for **how_to_optimize_operators** files:
+**00:33.817** total execution time for **how_to_optimize_operators** files:
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:31.646 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:31.519 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.250 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.274 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:00.963 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.024 | 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 ba14620f9..acef204c3 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
=================
-**05:14.471** total execution time for **how_to_tune_with_autoscheduler** files:
+**05:15.632** 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``) | 02:38.831 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 02:39.433 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:18.691 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:19.413 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 00:42.987 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 00:42.663 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:17.327 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:17.525 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:08.385 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:08.414 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:08.251 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:08.184 | 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 a8e90bdeb..03b437d1b 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
@@ -770,7 +770,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.362 ms
+ Execution time of this operator: 0.355 ms
@@ -1377,7 +1377,7 @@ In the example below we resume the status and do more 5 trials.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 38.831 seconds)
+ **Total running time of the script:** ( 2 minutes 39.433 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_arm.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_arm.rst.txt
index a39279d76..e929ed84d 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_arm.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_arm.rst.txt
@@ -330,7 +330,7 @@ The task scheduler will just optimize this objective.
Get model...
Extract tasks...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["1037be767e8e18197e87653d81c34558", [1, 7, 7, 1024], [1, 1, 1024, 1024], [1, 1, 1, 1024], [1, 7, 7, 1024]]) ==========
placeholder = PLACEHOLDER [1, 7, 7, 1024]
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 47df1d79d..678f1fedd 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
@@ -200,7 +200,7 @@ The task scheduler will just optimize this objective.
.. code-block:: none
Extract tasks...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["8654f16aeddf785bad9f028164b3a48d", [1, 56, 56, 64], [1, 1, 64, 64], [1, 56, 56, 64]]) ==========
placeholder = PLACEHOLDER [1, 56, 56, 64]
@@ -641,12 +641,12 @@ so we can read the log file and load the best schedules.
.. code-block:: none
Compile...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 9.9239 9.9329 9.9714 9.8674 0.0429
+ 9.7184 9.7348 9.7544 9.6659 0.0379
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_mali.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_mali.rst.txt
index b26a272ca..b08c35d19 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_mali.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_mali.rst.txt
@@ -229,7 +229,7 @@ The task scheduler will just optimize this objective.
.. code-block:: none
Extract tasks...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["1037be767e8e18197e87653d81c34558", [1, 7, 7, 1024], [1, 1, 1024, 1024], [1, 1, 1, 1024], [1, 7, 7, 1024]]) ==========
placeholder = PLACEHOLDER [1, 7, 7, 1024]
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 94ce91cbb..2a12559a3 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
@@ -223,7 +223,7 @@ The task scheduler will just optimize this objective.
Get model...
Extract tasks...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["8654f16aeddf785bad9f028164b3a48d", [1, 56, 56, 64], [1, 1, 64, 256], [1, 56, 56, 256]]) ==========
placeholder = PLACEHOLDER [1, 56, 56, 64]
@@ -660,12 +660,12 @@ so we can read the log file and load the best schedules.
.. code-block:: none
Compile...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 747.3096 747.2768 748.7538 745.8983 1.1660
+ 754.4603 754.0814 756.0359 753.2634 1.1631
@@ -693,7 +693,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 18.691 seconds)
+ **Total running time of the script:** ( 1 minutes 19.413 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 ba0cce087..b8f415b9d 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
@@ -396,28 +396,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [65536], []),
compute: Buffer(compute_2: Pointer(float32), float32, [65536], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute}
- preflattened_buffer_map = {placeholder_7: placeholder_15: Buffer(placeholder_12, int32, [4916], []), placeholder_5: placeholder_16: Buffer(placeholder_10, float32, [128, 256], []), placeholder_8: placeholder_17: Buffer(placeholder_13, int32, [33], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_9: placeholder_19: Buffer(placeholder_14, float32, [128, 512], [])} {
- for (i0.outer.i1.outer.fused: int32, 0, 256) "parallel" {
- allocate(compute_4: Pointer(global float32), float32, [256]), storage_scope = global {
- for (i.inner.init: int32, 0, 16) {
- for (j.init: int32, 0, 16) {
- compute_5: Buffer(compute_4, float32, [256], [])[((i.inner.init*16) + j.init)] = 0f32
+ preflattened_buffer_map = {placeholder_7: placeholder_15: Buffer(placeholder_12, int32, [4916], []), placeholder_9: placeholder_16: Buffer(placeholder_14, float32, [128, 512], []), placeholder_5: placeholder_17: Buffer(placeholder_10, float32, [128, 256], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_8: placeholder_19: Buffer(placeholder_13, int32, [33], [])} {
+ for (i0.outer.i1.outer.fused: int32, 0, 32) "parallel" {
+ allocate(compute_4: Pointer(global float32), float32, [2048]), storage_scope = global {
+ for (i.outer.inner: int32, 0, 32) {
+ for (i.inner.init: int32, 0, 4) {
+ for (j.init: int32, 0, 16) {
+ compute_5: Buffer(compute_4, float32, [2048], [])[(((i.outer.inner*64) + (i.inner.init*16)) + j.init)] = 0f32
+ }
}
- }
- for (elem_idx: int32, 0, let cse_var_1: int32 = floormod(i0.outer.i1.outer.fused, 32) in (placeholder_3[(cse_var_1 + 1)] - placeholder_3[cse_var_1])) {
- for (i.inner: int32, 0, 16) {
- for (j: int32, 0, 16) {
- let cse_var_2: int32 = floormod(i0.outer.i1.outer.fused, 32)
- if @tir.likely((elem_idx < (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])), dtype=bool) {
- let cse_var_3: int32 = ((i.inner*16) + j)
- compute_5[cse_var_3] = (compute_5[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_2]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 32)*4096) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_2] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, (placeholder_3[(i0.outer.i1.outer.fused + 1)] - placeholder_3[i0.outer.i1.outer.fused])) {
+ for (i.inner: int32, 0, 4) {
+ for (j: int32, 0, 16) {
+ if @tir.likely((elem_idx < (placeholder_3[(i0.outer.i1.outer.fused + 1)] - placeholder_3[i0.outer.i1.outer.fused])), dtype=bool) {
+ let cse_var_1: int32 = (((i.outer.inner*64) + (i.inner*16)) + j)
+ compute_5[cse_var_1] = (compute_5[cse_var_1] + (placeholder_1[(((placeholder_3[i0.outer.i1.outer.fused]*16) + (elem_idx*16)) + j)]*max(placeholder[(((i.outer.inner*1024) + (i.inner*256)) + placeholder_2[(placeholder_3[i0.outer.i1.outer.fused] + elem_idx)])], 0f32)))
+ }
}
}
}
}
- for (i0.inner: int32, 0, 16) {
- let cse_var_4: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*8192) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 32)*16))
- compute[ramp(cse_var_4, 1, 16)] = max((compute_5[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_4, 1, 16)]), broadcast(0f32, 16))
+ for (i0.inner: int32, 0, 128) {
+ let cse_var_2: int32 = ((i0.inner*512) + (i0.outer.i1.outer.fused*16))
+ compute[ramp(cse_var_2, 1, 16)] = max((compute_5[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_2, 1, 16)]), broadcast(0f32, 16))
}
}
}
@@ -473,7 +474,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 1.563 ms
+ Execution time of this operator: 1.465 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 4ede96d3d..a67de6f2a 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
@@ -5,12 +5,12 @@
Computation times
=================
-**00:42.701** total execution time for **how_to_tune_with_autotvm** files:
+**00:43.805** 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``) | 00:42.668 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:43.773 | 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 |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``) | 00:00.019 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``) | 00:00.005 | 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 beb9c9767..ab18a8d13 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
@@ -269,9 +269,9 @@ for this template
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -392,9 +392,9 @@ for this template
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -515,9 +515,9 @@ for this template
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -638,9 +638,9 @@ for this template
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -761,9 +761,9 @@ for this template
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -879,15 +879,15 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4, 32]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2885496
- No: 6 GFLOPS: 67.66/67.66 result: MeasureResult(costs=(0.003421460166666667,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.5774593353271484, timestamp=1656118430.2414901) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
- No: 7 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 6 GFLOPS: 111.99/111.99 result: MeasureResult(costs=(0.0020671165714285715,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8865644931793213, timestamp=1656358761.48969) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
+ No: 7 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1003,14 +1003,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6225319
- No: 8 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 8 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1126,14 +1126,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,943546
- No: 9 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 9 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1249,7 +1249,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 32]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2868708
- No: 10 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 10 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 142, in build
res = future.result()
File "/usr/lib/python3.7/concurrent/futures/_base.py", line 435, in result
@@ -1267,14 +1267,14 @@ for this template
TimeoutError
[('tile_f', [-1, 32, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4691833
- No: 11 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 11 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1390,14 +1390,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1042124
- No: 12 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 12 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1513,14 +1513,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10013405
- No: 13 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 13 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1636,14 +1636,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6732082
- No: 14 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 14 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1759,14 +1759,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7536735
- No: 15 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 15 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1882,14 +1882,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,482121
- No: 16 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 16 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2005,14 +2005,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 32, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2824525
- No: 17 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 17 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2128,14 +2128,14 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4559286
- No: 18 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 18 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2251,7 +2251,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 512]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9677544
- No: 19 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+ No: 19 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 738, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 702, in run_through_rpc
@@ -2339,7 +2339,7 @@ for this template
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007f5da624ffa2
+ 12: 0x00007f912d912fa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2404,7 +2404,7 @@ for this template
21: _PyFunction_FastCallKeywords
20: _PyEval_EvalFrameDefault
19: _PyFunction_FastCall [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6390073
- No: 20 GFLOPS: 144.20/144.20 result: MeasureResult(costs=(0.0016053873300000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3985545635223389, timestamp=1656118456.6012232) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
+ No: 20 GFLOPS: 144.29/144.29 result: MeasureResult(costs=(0.0016043764699999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.421783208847046, timestamp=1656358788.042704) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
@@ -2461,7 +2461,7 @@ and measure running time.
Best config:
[('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
Finish loading 20 records
- Time cost of this operator: 0.001973
+ Time cost of this operator: 0.001995
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 88514237c..4a3113306 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
@@ -323,15 +323,15 @@ Timing the untuned program
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 317.5 98.75 (1, 2, 10, 10, 3) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.097 0.963 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.921 0.286 (1, 1, 10, 10, 3) 1 1
- Total_time - 321.518 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 310.2 98.731 (1, 2, 10, 10, 3) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.085 0.982 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.901 0.287 (1, 1, 10, 10, 3) 1 1
+ Total_time - 314.186 - - - -
@@ -392,15 +392,15 @@ Timing the tuned program
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 119.2 97.748 (1, 6, 10, 10, 1) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.822 1.494 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.924 0.758 (1, 1, 10, 10, 3) 1 1
- Total_time - 121.946 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 192.2 98.424 (1, 1, 10, 10, 6) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.16 1.106 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.918 0.47 (1, 3, 10, 10, 1) 1 1
+ Total_time - 195.278 - - - -
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 4e7bb1d74..36c687f69 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/tmpsjy2eoei/images/random'
+ '/tmp/tmp8dkuez43/images/random'
@@ -325,8 +325,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. code-block:: none
- /tmp/tmpsjy2eoei/images/target contains 8144 images
- /tmp/tmpsjy2eoei/images/random contains 5000 images
+ /tmp/tmp8dkuez43/images/target contains 8144 images
+ /tmp/tmp8dkuez43/images/random contains 5000 images
@@ -501,13 +501,13 @@ the time on our validation set).
.. code-block:: none
Epoch 1/3
- 328/328 - 54s - loss: 0.2170 - accuracy: 0.9258 - val_loss: 0.1394 - val_accuracy: 0.9581
+ 328/328 - 55s - loss: 0.2475 - accuracy: 0.9155 - val_loss: 0.1382 - val_accuracy: 0.9535
Epoch 2/3
- 328/328 - 51s - loss: 0.1005 - accuracy: 0.9610 - val_loss: 0.1354 - val_accuracy: 0.9539
+ 328/328 - 52s - loss: 0.1015 - accuracy: 0.9623 - val_loss: 0.1143 - val_accuracy: 0.9611
Epoch 3/3
- 328/328 - 51s - loss: 0.0683 - accuracy: 0.9746 - val_loss: 0.1263 - val_accuracy: 0.9569
+ 328/328 - 52s - loss: 0.0693 - accuracy: 0.9734 - val_loss: 0.1179 - val_accuracy: 0.9637
- <keras.callbacks.History object at 0x7fa83a1e9f90>
+ <keras.callbacks.History object at 0x7f809239d8d0>
@@ -681,7 +681,7 @@ Relay model into the MLF intermediate representation. From here, we just need to
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -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:** ( 7 minutes 57.481 seconds)
+ **Total running time of the script:** ( 12 minutes 57.097 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 d227f5a03..178eb446f 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
@@ -5,14 +5,14 @@
Computation times
=================
-**08:43.358** total execution time for **how_to_work_with_microtvm** files:
+**13:42.888** total execution time for **how_to_work_with_microtvm** files:
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 07:57.481 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 12:57.097 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:42.472 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:42.363 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.405 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.429 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_microtvm_micro_ethosu.py` (``micro_ethosu.py``) | 00:00.000 | 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 7d9940885..012a47669 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
@@ -5,12 +5,12 @@
Computation times
=================
-**00:11.345** total execution time for **how_to_work_with_relay** files:
+**00:11.489** total execution time for **how_to_work_with_relay** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:09.758 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:09.773 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.582 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.710 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``) | 00:00.006 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_relay/using_external_lib.rst.txt b/docs/_sources/how_to/work_with_relay/using_external_lib.rst.txt
index 6e5ea71a4..1fe942a45 100644
--- a/docs/_sources/how_to/work_with_relay/using_external_lib.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/using_external_lib.rst.txt
@@ -126,7 +126,7 @@ By setting the logging level to DEBUG, the result of Relay graph compilation wil
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -569,7 +569,7 @@ To do that, all we need to do is to append the option " -libs=cudnn" to the targ
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 c76c2a337..7724635ae 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
@@ -259,7 +259,7 @@ The following example customizes CUDA lowering rule for :code:`exp`.
.. code-block:: none
- <function my_cuda_math_rule at 0x7fa7e796c440>
+ <function my_cuda_math_rule at 0x7f8011417440>
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 74ce653fe..e1f08c0f4 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
=================
-**00:03.956** total execution time for **how_to_work_with_schedules** files:
+**00:04.133** total execution time for **how_to_work_with_schedules** files:
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:01.821 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:01.909 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:00.965 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.006 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.508 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.531 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.493 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.515 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.096 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.097 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.034 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.026 | 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_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.013 | 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 1a94c57b8..88dd630b3 100644
--- a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
@@ -346,7 +346,7 @@ The importing needs to happen before the tensorized GEMV being executed.
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C}
preflattened_buffer_map = {A_1: A_3: Buffer(A_2, float32, [1024, 64], []), B_1: B_3: Buffer(B_2, float32, [512, 64], []), C_1: C_3: Buffer(C_2, float32, [1024, 512], [])} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmppb_xo3nw/input0.cc'\nsource_filename = \"/tmp/tmppb_xo3nw/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/tmpzt3v1dua/input0.cc'\nsource_filename = \"/tmp/tmpzt3v1dua/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 af72c5581..cf0b8c4f4 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
=================
-**00:19.812** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:20.279** total execution time for **topic_vta_tutorials_autotvm** files:
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:19.806 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:20.273 | 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/autotvm/tune_relay_vta.rst.txt b/docs/_sources/topic/vta/tutorials/autotvm/tune_relay_vta.rst.txt
index da352f4d6..05b7ec4f8 100644
--- a/docs/_sources/topic/vta/tutorials/autotvm/tune_relay_vta.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/autotvm/tune_relay_vta.rst.txt
@@ -536,7 +536,7 @@ Finally, we launch tuning jobs and evaluate the end-to-end performance.
.. code-block:: none
Extract tasks...
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/target/target.py:261: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
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 8bd9d63c4..896533e77 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -285,13 +285,13 @@ The compilation steps are:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
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 21.22s!
+ resnet18_v1 inference graph built in 22.00s!
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 c7f32bfd2..dc82040d9 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -331,11 +331,11 @@ The compilation steps are:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- yolov3-tiny inference graph built in 14.96s!
+ yolov3-tiny inference graph built in 15.45s!
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 2d6f6667f..d6da9f6b2 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
=================
-**01:27.642** total execution time for **topic_vta_tutorials_frontend** files:
+**01:29.164** total execution time for **topic_vta_tutorials_frontend** files:
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:46.521 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:47.344 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:41.121 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:41.820 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/matrix_multiply.rst.txt b/docs/_sources/topic/vta/tutorials/matrix_multiply.rst.txt
index 272f90207..fd2457a80 100644
--- a/docs/_sources/topic/vta/tutorials/matrix_multiply.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/matrix_multiply.rst.txt
@@ -678,7 +678,7 @@ into a TVM function.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/_sources/topic/vta/tutorials/optimize/convolution_opt.rst.txt b/docs/_sources/topic/vta/tutorials/optimize/convolution_opt.rst.txt
index 4023544e3..fa7858b3e 100644
--- a/docs/_sources/topic/vta/tutorials/optimize/convolution_opt.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/optimize/convolution_opt.rst.txt
@@ -914,7 +914,7 @@ ensure correctness.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Execution statistics:
inp_load_nbytes : 114688
diff --git a/docs/_sources/topic/vta/tutorials/optimize/matrix_multiply_opt.rst.txt b/docs/_sources/topic/vta/tutorials/optimize/matrix_multiply_opt.rst.txt
index d85fc5010..d8738e0b9 100644
--- a/docs/_sources/topic/vta/tutorials/optimize/matrix_multiply_opt.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/optimize/matrix_multiply_opt.rst.txt
@@ -683,7 +683,7 @@ ensure correctness.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Execution statistics:
inp_load_nbytes : 4096
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 505f83a60..933f24a38 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
=================
-**00:03.185** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.278** total execution time for **topic_vta_tutorials_optimize** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.808 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.883 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.377 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.395 | 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 b627251e3..48c4d3079 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
=================
-**00:00.701** total execution time for **topic_vta_tutorials** files:
+**00:00.721** total execution time for **topic_vta_tutorials** files:
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.375 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.386 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.326 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.335 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/vta_get_started.rst.txt b/docs/_sources/topic/vta/tutorials/vta_get_started.rst.txt
index e931eb06c..ac5163c5b 100644
--- a/docs/_sources/topic/vta/tutorials/vta_get_started.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/vta_get_started.rst.txt
@@ -555,7 +555,7 @@ we want to compile to.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index 280d49313..116b77ce2 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -327,7 +327,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 93.728 ms
+ Execution time of this operator: 92.446 ms
@@ -427,7 +427,7 @@ resume the status and do more 5 trials.
Resume search:
/usr/local/lib/python3.7/dist-packages/xgboost/training.py:17: UserWarning: Old style callback is deprecated. See: https://xgboost.readthedocs.io/en/latest/python/callbacks.html
warnings.warn(f'Old style callback is deprecated. See: {link}', UserWarning)
- *E
+
diff --git a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
index b831ad8bf..c051298fc 100644
--- a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
@@ -449,16 +449,16 @@ reduce variance, we take 5 measurements and average them.
waiting for device...
device available
Get devices for measurement successfully!
- No: 1 GFLOPS: 10.34/10.34 result: MeasureResult(costs=(0.0259562372,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5491230487823486, timestamp=1656117296.9030733) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
- No: 2 GFLOPS: 2.77/10.34 result: MeasureResult(costs=(0.0969674538,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6972053050994873, timestamp=1656117299.1309118) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
- No: 3 GFLOPS: 11.82/11.82 result: MeasureResult(costs=(0.022706498999999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5993161201477051, timestamp=1656117299.6973338) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
- No: 4 GFLOPS: 1.85/11.82 result: MeasureResult(costs=(0.1452927854,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4411725997924805, timestamp=1656117302.6916847) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
- No: 5 GFLOPS: 3.67/11.82 result: MeasureResult(costs=(0.073103693,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.301805019378662, timestamp=1656117304.1234105) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
- No: 6 GFLOPS: 1.71/11.82 result: MeasureResult(costs=(0.15696236,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.664360284805298, timestamp=1656117306.8340483) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
- No: 7 GFLOPS: 0.87/11.82 result: MeasureResult(costs=(0.3078180376,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.051161050796509, timestamp=1656117312.44912) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
- No: 8 GFLOPS: 10.71/11.82 result: MeasureResult(costs=(0.025068074200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5381650924682617, timestamp=1656117313.0124152) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
- No: 9 GFLOPS: 1.90/11.82 result: MeasureResult(costs=(0.1416254626,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.361100196838379, timestamp=1656117315.4919925) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
- No: 10 GFLOPS: 2.71/11.82 result: MeasureResult(costs=(0.09921746960000001,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6903772354125977, timestamp=1656117317.2416878) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
+ No: 1 GFLOPS: 9.02/9.02 result: MeasureResult(costs=(0.029773967800000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6079602241516113, timestamp=1656357607.0578802) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
+ No: 2 GFLOPS: 2.40/9.02 result: MeasureResult(costs=(0.1116488642,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.9338338375091553, timestamp=1656357609.009395) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
+ No: 3 GFLOPS: 11.86/11.86 result: MeasureResult(costs=(0.022629014,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5676710605621338, timestamp=1656357610.0525854) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
+ No: 4 GFLOPS: 1.62/11.86 result: MeasureResult(costs=(0.16590396820000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.772679090499878, timestamp=1656357613.3981004) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
+ No: 5 GFLOPS: 3.69/11.86 result: MeasureResult(costs=(0.0728351586,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.300386905670166, timestamp=1656357614.8272932) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
+ No: 6 GFLOPS: 1.89/11.86 result: MeasureResult(costs=(0.1418611314,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.430314540863037, timestamp=1656357617.3039713) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
+ No: 7 GFLOPS: 0.77/11.86 result: MeasureResult(costs=(0.3487647382,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.7042810916900635, timestamp=1656357623.5580387) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
+ No: 8 GFLOPS: 10.62/11.86 result: MeasureResult(costs=(0.025265008,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5482184886932373, timestamp=1656357624.12589) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
+ No: 9 GFLOPS: 1.78/11.86 result: MeasureResult(costs=(0.1507286632,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.5086991786956787, timestamp=1656357626.7537687) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
+ No: 10 GFLOPS: 2.69/11.86 result: MeasureResult(costs=(0.09990336139999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.701523780822754, timestamp=1656357628.5155542) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index d740687ad..cded1666c 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -240,7 +240,7 @@ runtime module from the library.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -314,7 +314,7 @@ standard deviation.
.. code-block:: none
- {'mean': 494.34375246999025, 'median': 494.3581909499926, 'std': 0.9444984363007716}
+ {'mean': 493.2739005100075, 'median': 493.0039684500116, 'std': 0.8300160632685638}
@@ -548,33 +548,33 @@ the tuning data to.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 17.41/ 17.41 GFLOPS | Progress: (4/20) | 6.25 s
[Task 1/25] Current/Best: 6.15/ 17.41 GFLOPS | Progress: (8/20) | 9.23 s
[Task 1/25] Current/Best: 11.53/ 22.73 GFLOPS | Progress: (12/20) | 11.68 s
[Task 1/25] Current/Best: 16.87/ 22.73 GFLOPS | Progress: (16/20) | 13.35 s
[Task 1/25] Current/Best: 11.62/ 23.97 GFLOPS | Progress: (20/20) | 15.09 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 12.30/ 12.91 GFLOPS | Progress: (4/20) | 3.76 s
[Task 2/25] Current/Best: 13.84/ 18.26 GFLOPS | Progress: (8/20) | 5.08 s
[Task 2/25] Current/Best: 21.38/ 21.38 GFLOPS | Progress: (12/20) | 6.39 s
[Task 2/25] Current/Best: 12.20/ 21.38 GFLOPS | Progress: (16/20) | 7.64 s
[Task 2/25] Current/Best: 20.21/ 21.38 GFLOPS | Progress: (20/20) | 9.23 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 1.63/ 10.58 GFLOPS | Progress: (4/20) | 5.85 s
[Task 3/25] Current/Best: 15.59/ 16.86 GFLOPS | Progress: (8/20) | 7.75 s
[Task 3/25] Current/Best: 14.91/ 16.86 GFLOPS | Progress: (12/20) | 9.48 s
[Task 3/25] Current/Best: 7.22/ 23.82 GFLOPS | Progress: (16/20) | 11.39 s
[Task 3/25] Current/Best: 12.66/ 23.82 GFLOPS | Progress: (20/20) | 15.88 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 9.56/ 19.75 GFLOPS | Progress: (4/20) | 2.37 s
[Task 4/25] Current/Best: 6.86/ 19.75 GFLOPS | Progress: (8/20) | 6.71 s
[Task 4/25] Current/Best: 22.02/ 22.02 GFLOPS | Progress: (12/20) | 11.13 s
[Task 4/25] Current/Best: 17.37/ 22.02 GFLOPS | Progress: (16/20) | 13.39 s
[Task 4/25] Current/Best: 13.51/ 22.02 GFLOPS | Progress: (20/20) | 15.27 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 9.49/ 10.35 GFLOPS | Progress: (4/20) | 2.58 s
[Task 5/25] Current/Best: 11.60/ 12.49 GFLOPS | Progress: (8/20) | 4.65 s
[Task 5/25] Current/Best: 11.43/ 18.04 GFLOPS | Progress: (12/20) | 7.72 s
[Task 5/25] Current/Best: 11.68/ 22.72 GFLOPS | Progress: (16/20) | 9.13 s
[Task 5/25] Current/Best: 12.04/ 22.72 GFLOPS | Progress: (20/20) | 11.00 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 12.19/ 20.77 GFLOPS | Progress: (4/20) | 3.93 s
[Task 6/25] Current/Best: 18.66/ 20.77 GFLOPS | Progress: (8/20) | 5.68 s
[Task 6/25] Current/Best: 13.20/ 20.77 GFLOPS | Progress: (12/20) | 7.60 s
[Task 6/25] Current/Best: 19.98/ 20.77 GFLOPS | Progress: (16/20) | 9.87 s
[Task 6/25] Current/Best: 3.73/ 20.77 GFLOPS | Progress: (20/20) | 12.41 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 11.22/ 12.13 GFLOPS | Progress: (4/20) | 3.61 s
[Task 7/25] Current/Best: 20.19/ 21.10 GFLOPS | Progress: (8/20) | 5.13 s
[Task 7/25] Current/Best: 14.89/ 21.10 GFLOPS | Progress: (12/20) | 7.04 s
[Task 7/25] Current/Best: 12.26/ 21.10 GFLOPS | Progress: (16/20) | 9.09 s
[Task 7/25] Current/Best: 6.37/ 21.71 GFLOPS | Progress: (20/20) | 11.56 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 10.30/ 13.89 GFLOPS | Progress: (4/20) | 2.90 s
[Task 8/25] Current/Best: 9.60/ 13.89 GFLOPS | Progress: (8/20) | 7.67 s
[Task 8/25] Current/Best: 12.30/ 13.89 GFLOPS | Progress: (12/20) | 13.85 s
[Task 8/25] Current/Best: 18.73/ 18.73 GFLOPS | Progress: (16/20) | 15.94 s
[Task 8/25] Current/Best: 20.20/ 20.20 GFLOPS | Progress: (20/20) | 22.46 s Done.
-
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 14.28/ 15.77 GFLOPS | Progress: (4/20) | 11.93 s
[Task 9/25] Current/Best: 23.49/ 23.49 GFLOPS | Progress: (8/20) | 13.65 s
[Task 9/25] Current/Best: 8.29/ 23.49 GFLOPS | Progress: (12/20) | 15.99 s
[Task 9/25] Current/Best: 17.87/ 23.49 GFLOPS | Progress: (16/20) | 18.61 s
[Task 9/25] Current/Best: 9.03/ 23.49 GFLOPS | Progress: (20/20) | 26.14 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 18.25/ 18.25 GFLOPS | Progress: (4/20) | 2.55 s
[Task 10/25] Current/Best: 15.54/ 18.25 GFLOPS | Progress: (8/20) | 4.14 s
[Task 10/25] Current/Best: 11.90/ 18.93 GFLOPS | Progress: (12/20) | 5.66 s
[Task 10/25] Current/Best: 19.11/ 20.17 GFLOPS | Progress: (16/20) | 6.76 s
[Task 10/25] Current/Best: 8.77/ 20.17 GFLOPS | Progress: (20/20
) | 8.29 s Done.
-
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 12.28/ 18.12 GFLOPS | Progress: (4/20) | 3.28 s
[Task 11/25] Current/Best: 16.97/ 18.12 GFLOPS | Progress: (8/20) | 5.98 s
[Task 11/25] Current/Best: 18.22/ 18.22 GFLOPS | Progress: (12/20) | 8.04 s
[Task 11/25] Current/Best: 11.90/ 21.18 GFLOPS | Progress: (16/20) | 10.82 s
[Task 11/25] Current/Best: 19.44/ 21.50 GFLOPS | Progress: (20/20) | 12.82 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 7.83/ 17.96 GFLOPS | Progress: (4/20) | 5.26 s
[Task 12/25] Current/Best: 5.26/ 17.96 GFLOPS | Progress: (8/20) | 8.98 s
[Task 12/25] Current/Best: 18.78/ 19.00 GFLOPS | Progress: (12/20) | 10.96 s
[Task 12/25] Current/Best: 15.51/ 19.00 GFLOPS | Progress: (16/20) | 13.69 s
[Task 12/25] Current/Best: 15.17/ 19.00 GFLOPS | Progress: (20/20) | 15.61 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 8.62/ 17.14 GFLOPS | Progress: (4/20) | 3.62 s
[Task 13/25] Current/Best: 15.68/ 21.13 GFLOPS | Progress: (8/20) | 6.05 s
[Task 13/25] Current/Best: 19.67/ 21.91 GFLOPS | Progress: (12/20) | 8.92 s
[Task 13/25] Current/Best: 12.31/ 21.91 GFLOPS | Progress: (16/20) | 12.34 s
[Task 13/25] Current/Best: 18.18/ 21.91 GFLOPS | Progress: (20/20) | 14.61 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 12.70/ 13.23 GFLOPS | Progress: (4/20) | 3.34 s
[Task 14/25] Current/Best: 6.12/ 13.39 GFLOPS | Progress: (8/20) | 5.55 s
[Task 14/25] Current/Best: 19.68/ 19.68 GFLOPS | Progress: (12/20) | 8.07 s
[Task 14/25] Current/Best: 16.95/ 19.68 GFLOPS | Progress: (16/20) | 9.70 s Done.
-
[Task 14/25] Current/Best: 17.20/ 19.68 GFLOPS | Progress: (20/20) | 11.40 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 16.10/ 17.69 GFLOPS | Progress: (4/20) | 2.65 s
[Task 15/25] Current/Best: 14.23/ 18.03 GFLOPS | Progress: (8/20) | 3.94 s
[Task 15/25] Current/Best: 10.38/ 22.31 GFLOPS | Progress: (12/20) | 6.02 s
[Task 15/25] Current/Best: 20.43/ 22.31 GFLOPS | Progress: (16/20) | 9.20 s
[Task 15/25] Current/Best: 9.71/ 22.31 GFLOPS | Progress: (20/20) | 10.20 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 20.64/ 20.64 GFLOPS | Progress: (4/20) | 2.91 s
[Task 16/25] Current/Best: 3.04/ 20.64 GFLOPS | Progress: (8/20) | 4.52 s
[Task 16/25] Current/Best: 19.28/ 20.64 GFLOPS | Progress: (12/20) | 5.73 s
[Task 16/25] Current/Best: 17.08/ 20.64 GFLOPS | Progress: (16/20) |
7.05 s
[Task 16/25] Current/Best: 10.04/ 22.12 GFLOPS | Progress: (20/20) | 9.08 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 13.11/ 18.88 GFLOPS | Progress: (4/20) | 4.67 s
[Task 17/25] Current/Best: 14.38/ 23.31 GFLOPS | Progress: (8/20) | 7.51 s
[Task 17/25] Current/Best: 16.85/ 23.31 GFLOPS | Progress: (12/20) | 9.57 s
[Task 17/25] Current/Best: 16.53/ 23.31 GFLOPS | Progress: (16/20) | 11.71 s
[Task 17/25] Current/Best: 10.00/ 23.31 GFLOPS | Progress: (20/20) | 13.81 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 11.37/ 18.09 GFLOPS | Progress: (4/20) | 3.64 s
[Task 18/25] Current/Best: 10.55/ 19.51 GFLOPS | Progress: (8/20) | 7.04 s
[Task 18/25] Current/Best: 18.93/ 19.51 GFLOPS | Progress: (12/20) | 8.97 s
[Task 18/25] Current/Best: 10.06/ 19.51 GFLOPS | Progress: (16/20) | 12.47 s
[Task 18/25] Current/Best: 20.63/ 20.63 GFLOPS | Progress: (20/20) | 13.96 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 7.18/ 20.51 GFLOPS | Progress: (4/20) | 5.98 s
[Task 19/25] Current/Best: 2.61/ 20.51 GFLOPS | Progress: (8/20) | 9.24 s
[Task 19/25] Current/Best: 20.22/ 21.32 GFLOPS | Progress: (12/20) | 11.99 s
[Task 19/25] Current/Best: 14.27/ 21.32 GFLOPS | Progress: (16/20) | 14.86 s
[Task 19/25] Current/Best: 2.70/ 23.86 GFLOPS | Progress: (20/20) | 17.68 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 8.55/ 14.90 GFLOPS | Progress: (4/20) | 3.29 s Done.
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 17.53/ 17.53 GFLOPS | Progress: (4/20) | 6.20 s
[Task 1/25] Current/Best: 6.17/ 17.53 GFLOPS | Progress: (8/20) | 9.11 s
[Task 1/25] Current/Best: 11.54/ 22.89 GFLOPS | Progress: (12/20) | 11.51 s
[Task 1/25] Current/Best: 16.80/ 22.89 GFLOPS | Progress: (16/20) | 13.18 s
[Task 1/25] Current/Best: 11.59/ 23.91 GFLOPS | Progress: (20/20) | 14.93 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 12.19/ 13.14 GFLOPS | Progress: (4/20) | 3.62 s
[Task 2/25] Current/Best: 14.15/ 18.75 GFLOPS | Progress: (8/20) | 4.91 s
[Task 2/25] Current/Best: 21.00/ 21.00 GFLOPS | Progress: (12/20) | 6.21 s
[Task 2/25] Current/Best: 12.88/ 21.00 GFLOPS | Progress: (16/20) | 7.49 s
[Task 2/25] Current/Best: 18.90/ 21.00 GFLOPS | Progress: (20/20) | 9.03 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 1.63/ 10.58 GFLOPS | Progress: (4/20) | 5.83 s
[Task 3/25] Current/Best: 15.54/ 16.87 GFLOPS | Progress: (8/20) | 7.75 s
[Task 3/25] Current/Best: 14.94/ 16.87 GFLOPS | Progress: (12/20) | 9.48 s
[Task 3/25] Current/Best: 7.16/ 23.76 GFLOPS | Progress: (16/20) | 11.41 s
[Task 3/25] Current/Best: 12.68/ 23.76 GFLOPS | Progress: (20/20) | 15.88 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 9.58/ 20.41 GFLOPS | Progress: (4/20) | 2.35 s
[Task 4/25] Current/Best: 6.80/ 20.41 GFLOPS | Progress: (8/20) | 6.71 s
[Task 4/25] Current/Best: 22.31/ 22.31 GFLOPS | Progress: (12/20) | 11.11 s
[Task 4/25] Current/Best: 16.60/ 22.31 GFLOPS | Progress: (16/20) | 13.30 s
[Task 4/25] Current/Best: 13.38/ 22.31 GFLOPS | Progress: (20/20) | 15.19 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 9.72/ 10.43 GFLOPS | Progress: (4/20) | 2.58 s
[Task 5/25] Current/Best: 11.80/ 12.08 GFLOPS | Progress: (8/20) | 4.68 s
[Task 5/25] Current/Best: 11.57/ 18.07 GFLOPS | Progress: (12/20) | 7.77 s
[Task 5/25] Current/Best: 11.87/ 22.63 GFLOPS | Progress: (16/20) | 9.21 s
[Task 5/25] Current/Best: 12.05/ 22.63 GFLOPS | Progress: (20/20) | 11.05 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 12.22/ 20.81 GFLOPS | Progress: (4/20) | 3.94 s
[Task 6/25] Current/Best: 18.99/ 20.81 GFLOPS | Progress: (8/20) | 5.68 s
[Task 6/25] Current/Best: 13.34/ 20.81 GFLOPS | Progress: (12/20) | 7.60 s
[Task 6/25] Current/Best: 20.08/ 20.81 GFLOPS | Progress: (16/20) | 9.83 s
[Task 6/25] Current/Best: 3.73/ 20.81 GFLOPS | Progress: (20/20) | 12.34 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 11.30/ 12.83 GFLOPS | Progress: (4/20) | 3.58 s
[Task 7/25] Current/Best: 20.29/ 21.16 GFLOPS | Progress: (8/20) | 5.07 s
[Task 7/25] Current/Best: 14.05/ 21.16 GFLOPS | Progress: (12/20) | 7.03 s
[Task 7/25] Current/Best: 12.28/ 21.16 GFLOPS | Progress: (16/20) | 9.07 s
[Task 7/25] Current/Best: 5.82/ 21.79 GFLOPS | Progress: (20/20) | 11.54 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 9.98/ 14.30 GFLOPS | Progress: (4/20) | 2.87 s
[Task 8/25] Current/Best: 9.75/ 14.30 GFLOPS | Progress: (8/20) | 7.62 s
[Task 8/25] Current/Best: 12.82/ 14.30 GFLOPS | Progress: (12/20) | 13.68 s
[Task 8/25] Current/Best: 18.74/ 18.74 GFLOPS | Progress: (16/20) | 15.75 s
[Task 8/25] Current/Best: 18.14/ 18.74 GFLOPS | Progress: (20/20) | 22.22 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 14.37/ 15.92 GFLOPS | Progress: (4/20) | 11.94 s
[Task 9/25] Current/Best: 22.76/ 22.76 GFLOPS | Progress: (8/20) | 13.67 s
[Task 9/25] Current/Best: 8.29/ 22.76 GFLOPS | Progress: (12/20) | 15.98 s
[Task 9/25] Current/Best: 18.03/ 22.76 GFLOPS | Progress: (16/20) | 18.61 s
[Task 9/25] Current/Best: 9.07/ 22.76 GFLOPS | Progress: (20/20) | 26.22 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 18.18/ 18.18 GFLOPS | Progress: (4/20) | 2.53 s
[Task 10/25] Current/Best: 15.54/ 18.18 GFLOPS | Progress: (8/20) | 4.13 s
[Task 10/25] Current/Best: 11.75/ 19.00 GFLOPS | Progress: (12/20) | 5.65 s
[Task 10/25] Current/Best: 19.16/ 20.38 GFLOPS | Progress: (16/20) | 6.75 s
[Task 10/25] Current/Best: 8.91/ 20.38 GFLOPS | Progress: (20/20
) | 8.29 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 12.18/ 18.02 GFLOPS | Progress: (4/20) | 3.24 s
[Task 11/25] Current/Best: 16.99/ 18.02 GFLOPS | Progress: (8/20) | 5.96 s
[Task 11/25] Current/Best: 18.12/ 18.12 GFLOPS | Progress: (12/20) | 7.99 s
[Task 11/25] Current/Best: 13.51/ 21.24 GFLOPS | Progress: (16/20) | 10.75 s
[Task 11/25] Current/Best: 19.48/ 21.59 GFLOPS | Progress: (20/20) | 12.77 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 7.84/ 18.02 GFLOPS | Progress: (4/20) | 5.29 s
[Task 12/25] Current/Best: 5.32/ 18.02 GFLOPS | Progress: (8/20) | 8.92 s
[Task 12/25] Current/Best: 18.92/ 18.94 GFLOPS | Progress: (12/20) | 10.92 s
[Task 12/25] Current/Best: 15.43/ 18.94 GFLOPS | Progress: (16/20) | 13.65 s
[Task 12/25] Current/Best: 15.13/ 18.94 GFLOPS | Progress: (20/20) | 15.61 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 8.80/ 17.31 GFLOPS | Progress: (4/20) | 3.61 s
[Task 13/25] Current/Best: 15.88/ 21.02 GFLOPS | Progress: (8/20) | 6.02 s
[Task 13/25] Current/Best: 19.76/ 21.61 GFLOPS | Progress: (12/20) | 8.91 s
[Task 13/25] Current/Best: 12.27/ 21.61 GFLOPS | Progress: (16/20) | 12.32 s
[Task 13/25] Current/Best: 18.66/ 21.61 GFLOPS | Progress: (20/20) | 14.59 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 13.61/ 13.61 GFLOPS | Progress: (4/20) | 3.23 s
[Task 14/25] Current/Best: 6.07/ 13.61 GFLOPS | Progress: (8/20) | 5.44 s
[Task 14/25] Current/Best: 20.85/ 20.85 GFLOPS | Progress: (12/20) | 7.96 s
[Task 14/25] Current/Best: 16.92/ 20.85 GFLOPS | Progress: (16/20) | 9.62 s Done.
+
[Task 14/25] Current/Best: 15.77/ 20.85 GFLOPS | Progress: (20/20) | 11.37 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 16.13/ 17.64 GFLOPS | Progress: (4/20) | 2.69 s
[Task 15/25] Current/Best: 12.99/ 18.10 GFLOPS | Progress: (8/20) | 4.02 s
[Task 15/25] Current/Best: 10.39/ 22.30 GFLOPS | Progress: (12/20) | 6.06 s
[Task 15/25] Current/Best: 20.41/ 22.30 GFLOPS | Progress: (16/20) | 9.49 s
[Task 15/25] Current/Best: 9.71/ 22.30 GFLOPS | Progress: (20/20) | 10.50 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 20.36/ 20.36 GFLOPS | Progress: (4/20) | 2.99 s
[Task 16/25] Current/Best: 3.04/ 20.36 GFLOPS | Progress: (8/20) | 4.60 s
[Task 16/25] Current/Best: 19.63/ 20.36 GFLOPS | Progress: (12/20) | 5.81 s
[Task 16/25] Current/Best: 17.75/ 20.36 GFLOPS | Progress: (16/20) |
7.14 s
[Task 16/25] Current/Best: 10.06/ 22.03 GFLOPS | Progress: (20/20) | 9.16 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 13.15/ 18.88 GFLOPS | Progress: (4/20) | 4.68 s
[Task 17/25] Current/Best: 14.46/ 23.39 GFLOPS | Progress: (8/20) | 7.41 s
[Task 17/25] Current/Best: 16.81/ 23.39 GFLOPS | Progress: (12/20) | 9.43 s
[Task 17/25] Current/Best: 16.55/ 23.39 GFLOPS | Progress: (16/20) | 11.54 s
[Task 17/25] Current/Best: 10.06/ 23.39 GFLOPS | Progress: (20/20) | 13.65 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 11.46/ 17.93 GFLOPS | Progress: (4/20) | 3.64 s
[Task 18/25] Current/Best: 10.59/ 18.89 GFLOPS | Progress: (8/20) | 7.01 s
[Task 18/25] Current/Best: 19.23/ 19.23 GFLOPS | Progress: (12/20) | 8.93 s
[Task 18/25] Current/Best: 10.02/ 19.23 GFLOPS | Progress: (16/20) | 12.42 s
[Task 18/25] Current/Best: 20.83/ 20.83 GFLOPS | Progress: (20/20) | 13.91 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 7.23/ 20.49 GFLOPS | Progress: (4/20) | 5.94 s
[Task 19/25] Current/Best: 2.60/ 20.49 GFLOPS | Progress: (8/20) | 9.24 s
[Task 19/25] Current/Best: 20.04/ 21.79 GFLOPS | Progress: (12/20) | 12.05 s
[Task 19/25] Current/Best: 13.04/ 21.79 GFLOPS | Progress: (16/20) | 14.91 s
[Task 19/25] Current/Best: 2.70/ 23.79 GFLOPS | Progress: (20/20) | 17.74 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 9.01/ 15.27 GFLOPS | Progress: (4/20) | 3.30 s Done.
Done.
-
[Task 20/25] Current/Best: 9.57/ 14.90 GFLOPS | Progress: (8/20) | 6.72 s
[Task 20/25] Current/Best: 2.32/ 16.26 GFLOPS | Progress: (12/20) | 10.55 s
[Task 20/25] Current/Best: 12.46/ 16.26 GFLOPS | Progress: (16/20) | 14.09 s
[Task 20/25] Current/Best: 12.38/ 22.33 GFLOPS | Progress: (20/20) | 16.14 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 6.43/ 17.76 GFLOPS | Progress: (4/20) | 3.17 s
[Task 21/25] Current/Best: 14.60/ 17.76 GFLOPS | Progress: (8/20) | 4.71 s
[Task 21/25] Current/Best: 1.61/ 17.76 GFLOPS | Progress: (12/20) | 6.85 s
[Task 21/25] Current/Best: 17.98/ 17.98 GFLOPS | Progress: (16/20) | 10.27 s
[Task 21/25] Current/Best: 4.46/ 17.98 GFLOPS | Progress: (20/20) | 17.31 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 2.71/ 17.00 GFLOPS | Progress: (4/20
) | 2.63 s
[Task 22/25] Current/Best: 8.71/ 22.09 GFLOPS | Progress: (8/20) | 4.62 s
[Task 22/25] Current/Best: 20.12/ 22.09 GFLOPS | Progress: (12/20) | 6.89 s
[Task 22/25] Current/Best: 15.38/ 22.09 GFLOPS | Progress: (16/20) | 9.00 s
[Task 22/25] Current/Best: 14.05/ 22.09 GFLOPS | Progress: (20/20) | 10.64 s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 17.63/ 20.63 GFLOPS | Progress: (4/20) | 3.20 s
[Task 23/25] Current/Best: 14.35/ 20.63 GFLOPS | Progress: (8/20) | 6.45 s
[Task 23/25] Current/Best: 21.07/ 21.83 GFLOPS | Progress: (12/20) | 8.21 s
[Task 23/25] Current/Best: 6.41/ 21.83 GFLOPS | Progress: (16/20) | 15.21 s
[Task 23/25] Current/Best: 7.77/ 21.83 GFLOPS | Progress: (20/20) | 19.41 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 8.43/ 8.43 GFLOPS | Progress: (4/20) | 11.77 s
[Task 24/25] Current/Best: 3.66/ 8.43 GFLOPS | Progress: (8/20) | 22.99 s
[Task 24/25] Current/Best: 4.15/ 8.43 GFLOPS | Progress: (12/20) | 33.69 s Done.
+
[Task 20/25] Current/Best: 9.65/ 15.27 GFLOPS | Progress: (8/20) | 6.73 s
[Task 20/25] Current/Best: 2.32/ 16.64 GFLOPS | Progress: (12/20) | 10.66 s
[Task 20/25] Current/Best: 12.39/ 16.64 GFLOPS | Progress: (16/20) | 14.33 s
[Task 20/25] Current/Best: 12.62/ 22.13 GFLOPS | Progress: (20/20) | 16.40 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 6.41/ 17.71 GFLOPS | Progress: (4/20) | 3.21 s
[Task 21/25] Current/Best: 14.66/ 17.71 GFLOPS | Progress: (8/20) | 4.75 s
[Task 21/25] Current/Best: 1.61/ 17.71 GFLOPS | Progress: (12/20) | 6.89 s
[Task 21/25] Current/Best: 17.80/ 17.80 GFLOPS | Progress: (16/20) | 10.31 s
[Task 21/25] Current/Best: 4.47/ 17.80 GFLOPS | Progress: (20/20) | 17.33 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 2.70/ 17.02 GFLOPS | Progress: (4/20
) | 2.67 s
[Task 22/25] Current/Best: 8.76/ 21.96 GFLOPS | Progress: (8/20) | 4.56 s
[Task 22/25] Current/Best: 20.01/ 21.96 GFLOPS | Progress: (12/20) | 6.88 s
[Task 22/25] Current/Best: 15.49/ 21.96 GFLOPS | Progress: (16/20) | 8.91 s
[Task 22/25] Current/Best: 14.27/ 21.96 GFLOPS | Progress: (20/20) | 10.62 s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 17.70/ 20.93 GFLOPS | Progress: (4/20) | 3.23 s
[Task 23/25] Current/Best: 14.22/ 20.93 GFLOPS | Progress: (8/20) | 6.59 s
[Task 23/25] Current/Best: 20.90/ 21.75 GFLOPS | Progress: (12/20) | 8.38 s
[Task 23/25] Current/Best: 6.41/ 21.75 GFLOPS | Progress: (16/20) | 15.28 s
[Task 23/25] Current/Best: 7.94/ 21.75 GFLOPS | Progress: (20/20) | 19.46 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 8.55/ 8.55 GFLOPS | Progress: (4/20) | 11.78 s
[Task 24/25] Current/Best: 2.11/ 8.55 GFLOPS | Progress: (8/20) | 22.82 s
[Task 24/25] Current/Best: 4.53/ 8.55 GFLOPS | Progress: (12/20) | 34.33 s Done.
Done.
-
[Task 24/25] Current/Best: 6.09/ 9.00 GFLOPS | Progress: (16/20) | 39.05 s
[Task 24/25] Current/Best: 3.21/ 9.00 GFLOPS | Progress: (20/20) | 44.91 s Done.
-
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 1.55/ 2.78 GFLOPS | Progress: (4/20) | 11.56 s
[Task 25/25] Current/Best: 6.32/ 8.53 GFLOPS | Progress: (8/20) | 22.79 s
[Task 25/25] Current/Best: 6.12/ 8.53 GFLOPS | Progress: (12/20) | 34.21 s
[Task 25/25] Current/Best: 5.93/ 8.84 GFLOPS | Progress: (16/20) | 36.02 s
[Task 25/25] Current/Best: 2.96/ 9.34 GFLOPS | Progress: (20/20) | 46.74 s
+
[Task 24/25] Current/Best: 5.91/ 8.70 GFLOPS | Progress: (16/20) | 39.72 s
[Task 24/25] Current/Best: 3.41/ 8.78 GFLOPS | Progress: (20/20) | 45.52 s Done.
+
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 1.55/ 2.76 GFLOPS | Progress: (4/20) | 11.57 s
[Task 25/25] Current/Best: 6.14/ 8.29 GFLOPS | Progress: (8/20) | 22.86 s
[Task 25/25] Current/Best: 5.98/ 8.29 GFLOPS | Progress: (12/20) | 34.15 s
[Task 25/25] Current/Best: 5.82/ 8.90 GFLOPS | Progress: (16/20) | 36.05 s
[Task 25/25] Current/Best: 2.83/ 9.26 GFLOPS | Progress: (20/20) | 46.73 s
@@ -642,7 +642,7 @@ model using optimized operators to speed up our computations.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -735,8 +735,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 412.64101150999977, 'median': 412.11191500001405, 'std': 1.6191610398155065}
- unoptimized: {'mean': 494.34375246999025, 'median': 494.3581909499926, 'std': 0.9444984363007716}
+ optimized: {'mean': 408.12680654999895, 'median': 407.4677640000118, 'std': 1.5531821657855862}
+ unoptimized: {'mean': 493.2739005100075, 'median': 493.0039684500116, 'std': 0.8300160632685638}
@@ -759,7 +759,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 10 minutes 10.157 seconds)
+ **Total running time of the script:** ( 10 minutes 8.987 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 98b06ecd1..ac54f46f5 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -269,7 +269,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.678e-07 secs/op
+ 1.346e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index 493f1b470..43413989e 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -262,7 +262,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0x20ccb3c0)), stage(b, placeholder(b, 0xff7adc0)), 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, 0xf940b30)), stage(b, placeholder(b, 0x26eb8db0)), 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 [...]
diff --git a/docs/_sources/tutorial/relay_quick_start.rst.txt b/docs/_sources/tutorial/relay_quick_start.rst.txt
index d28ed6ba1..bd6bfd75f 100644
--- a/docs/_sources/tutorial/relay_quick_start.rst.txt
+++ b/docs/_sources/tutorial/relay_quick_start.rst.txt
@@ -246,7 +246,7 @@ in this example. Then the machine code will be generated as the module library.
/workspace/python/tvm/target/target.py:377: UserWarning: Try specifying cuda arch by adding 'arch=sm_xx' to your target.
warnings.warn("Try specifying cuda arch by adding 'arch=sm_xx' to your target.")
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index c096c56b7..a52a7d869 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,29 +5,29 @@
Computation times
=================
-**13:02.719** total execution time for **tutorial** files:
+**12:54.775** total execution time for **tutorial** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 10:10.157 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 10:08.987 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:00.901 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 00:58.673 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 00:58.655 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 00:52.935 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:27.941 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:27.664 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:23.742 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:24.907 | 0.0 MB |
++------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.774 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.682 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.508 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.152 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.133 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``) | 00:00.000 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_install.py` (``install.py``) | 00:00.000 | 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 54de4779f..f1ad5d6aa 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -201,7 +201,7 @@ the inputs and outputs) as well as target language we want to compile to.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
@@ -289,7 +289,7 @@ helper function to run a profile of the TVM generated code.
.. code-block:: none
Numpy running time: 0.000007
- naive: 0.000007
+ naive: 0.000006
@@ -388,7 +388,7 @@ compile and run this new schedule with the parallel operation applied:
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
parallel: 0.000006
@@ -445,7 +445,7 @@ factor to be the number of threads on your CPU.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
vector: 0.000025
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
@@ -499,10 +499,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 7.052989999465353e-06 1.0
- naive 6.7129e-06 0.9517807342005116
- parallel 6.0362e-06 0.8558356102103604
- vector 2.46616e-05 3.4966163289426833
+ numpy 6.7325199961487665e-06 1.0
+ naive 5.8615e-06 0.870624967078149
+ parallel 6.052e-06 0.8989204641741803
+ vector 2.45162e-05 3.6414596635470984
@@ -923,7 +923,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.019149
+ Numpy running time: 0.017890
@@ -981,9 +981,9 @@ optimizations.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- none: 3.410052
+ none: 3.255034
@@ -1086,9 +1086,9 @@ schedule.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- blocking: 0.300462
+ blocking: 0.297283
@@ -1184,9 +1184,9 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- vectorization: 0.336541
+ vectorization: 0.333843
@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, [1048576], []),
@@ -1260,9 +1260,9 @@ more cache friendly.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- loop permutation: 0.117097
+ loop permutation: 0.116820
@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, [1048576], []),
@@ -1361,9 +1361,9 @@ optimized schedule.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- array packing: 0.111708
+ array packing: 0.110421
@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, [1048576], []),
@@ -1456,9 +1456,9 @@ to `C` when all the block results are ready.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- block caching: 0.111311
+ block caching: 0.111059
@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, [1048576], []),
@@ -1544,9 +1544,9 @@ of thread-level parallelization.
.. code-block:: none
- /workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+ /workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- parallelization: 0.143680
+ parallelization: 0.143716
@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, [1048576], []),
@@ -1627,13 +1627,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.4100518081000004 1.0
- blocking 0.3004623758 0.08811079499915589
- vectorization 0.3365409461 0.09869086015074727
- loop permutation 0.11709737199999999 0.03433888356823642
- array packing 0.11170753340000002 0.03275830975196849
- block caching 0.111310507 0.032641881491536504
- parallelization 0.1436801223 0.04213429307986236
+ none 3.2550339356 1.0
+ blocking 0.29728293250000004 0.09133020987850374
+ vectorization 0.3338428512 0.1025620186471152
+ loop permutation 0.11681979180000002 0.03588896279155585
+ array packing 0.1104211219 0.033923186081820704
+ block caching 0.11105910379999999 0.0341191846221193
+ parallelization 0.1437163352 0.04415202361738473
@@ -1673,11 +1673,6 @@ operations with tunable parameters that allows you to automatically optimize
the computation for specific platforms.
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 0.901 seconds)
-
-
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
.. only:: html
diff --git a/docs/commit_hash b/docs/commit_hash
index 674719251..0ab93eea1 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-12dad9a4a184d4717e07f0f669dd6a6f12c37c69
+45568c9963fae1ea44a63cfd77b728471503ebff
diff --git a/docs/genindex.html b/docs/genindex.html
index 07541d58d..5306d5a24 100644
--- a/docs/genindex.html
+++ b/docs/genindex.html
@@ -3259,10 +3259,10 @@
<li><a href="reference/api/python/tir.html#tvm.tir.Schedule.reorder">(tvm.tir.Schedule method)</a>
</li>
</ul></li>
- </ul></td>
- <td style="width: 33%; vertical-align: top;"><ul>
<li><a href="reference/api/python/autotvm.html#tvm.autotvm.task.space.ReorderEntity">ReorderEntity (class in tvm.autotvm.task.space)</a>
</li>
+ </ul></td>
+ <td style="width: 33%; vertical-align: top;"><ul>
<li><a href="reference/api/python/autotvm.html#tvm.autotvm.task.space.ReorderSpace">ReorderSpace (class in tvm.autotvm.task.space)</a>
</li>
<li><a href="reference/api/python/tir.html#tvm.tir.ScheduleState.replace">replace() (tvm.tir.ScheduleState method)</a>
@@ -3328,6 +3328,8 @@
<li><a href="reference/api/python/auto_scheduler.html#tvm.auto_scheduler.rewrite_compute_body">rewrite_compute_body() (in module tvm.auto_scheduler)</a>
</li>
<li><a href="reference/api/python/auto_scheduler.html#tvm.auto_scheduler.ComputeDAG.rewrite_layout_from_state">rewrite_layout_from_state() (tvm.auto_scheduler.ComputeDAG method)</a>
+</li>
+ <li><a href="reference/api/python/auto_scheduler.html#tvm.auto_scheduler.rewrite_tensor_shape">rewrite_tensor_shape() (in module tvm.auto_scheduler)</a>
</li>
<li><a href="reference/api/python/tir.html#tvm.tir.transform.RewriteUnsafeSelect">RewriteUnsafeSelect() (in module tvm.tir.transform)</a>
</li>
diff --git a/docs/how_to/compile_models/from_coreml.html b/docs/how_to/compile_models/from_coreml.html
index eaacf5168..514684b86 100644
--- a/docs/how_to/compile_models/from_coreml.html
+++ b/docs/how_to/compile_models/from_coreml.html
@@ -421,7 +421,7 @@ provided by apple in this example</p>
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="p">,</span> <a href="https://docs.python.org/3/library [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index 2a41363bd..592621695 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -455,7 +455,7 @@ pip install opencv-python
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Compiling the model...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -569,6 +569,7 @@ class:['truck 0.9266'] left:471 right:83 top:689 bottom:169
class:['bicycle 0.9984'] left:111 right:113 top:577 bottom:447
</pre></div>
</div>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 2.172 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 47a1c48da..7ec6144ad 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -422,7 +422,7 @@ 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.zip98c04dbf-e0cd-4043-9e3d-e75192fa8da2 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.zip1df7e179-acbf-4f0c-828a-5f4c922613a1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
</pre></div>
</div>
@@ -445,7 +445,7 @@ We support MXNet static graph(symbol) and HybridBlock in mxnet.gluon</p>
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="p">,</span> <a href="https://docs.python.org/3/librar [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index 02f906a92..f29749732 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -427,44 +427,41 @@ python3 -m pip install -f https://release.oneflow.info <span class="nv">oneflow<
<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
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@@ -522,7 +519,7 @@ python3 -m pip install -f https://release.oneflow.info <span class="nv">oneflow<
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="o">=</span><a href="https://docs.python.org/3/library/ [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_onnx.html b/docs/how_to/compile_models/from_onnx.html
index 05e5e2f38..8508876d3 100644
--- a/docs/how_to/compile_models/from_onnx.html
+++ b/docs/how_to/compile_models/from_onnx.html
@@ -446,7 +446,7 @@ provides a static definition of the input size.</p>
==> Context: Bad node spec for node. Name: OpType: Conv
warnings.warn(str(e))
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_paddle.html b/docs/how_to/compile_models/from_paddle.html
index 8ad5def34..cb221be65 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -453,7 +453,7 @@ A quick solution is</p>
<span class="p">)</span><span class="o">.</span><span class="n">evaluate</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -488,7 +488,7 @@ A quick solution is</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>TVM prediction top-1 id: 282, class name: 282: 'tiger cat',
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.008 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.757 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-paddle-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/16269b77359771348d507395692524cf/from_paddle.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_paddle.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/from_pytorch.html b/docs/how_to/compile_models/from_pytorch.html
index c03134c07..bb41b6c25 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -409,10 +409,8 @@ be unstable.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
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</pre></div>
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@@ -459,7 +457,7 @@ be unstable.</p>
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="../../reference/api/python/target.html#tvm.target.Target" title="tvm.target.Target" class="sphx-glr-backref-module-tvm-target sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="o">=</span><a href="../../reference/api/py [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index 88252965b..2a58dffbf 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -521,7 +521,7 @@ lib: target library which can be deployed on target with TVM runtime.</p>
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="../../reference/api/python/target.html#tvm.target.Target" title="tvm.target.Target" class="sphx-glr-backref-module-tvm-target sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="p">,</span> <a href="https://docs.python.o [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -631,7 +631,7 @@ 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 0.400 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 5.055 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/from_tflite.html b/docs/how_to/compile_models/from_tflite.html
index 4d48826d0..7b87314c0 100644
--- a/docs/how_to/compile_models/from_tflite.html
+++ b/docs/how_to/compile_models/from_tflite.html
@@ -487,7 +487,7 @@ flatc --python schema.fbs
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class="p">,</span> <a href="https://docs.python.org/3/library [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/sg_execution_times.html b/docs/how_to/compile_models/sg_execution_times.html
index 8c723bb67..4c3fbe760 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>05:36.919</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>05:41.893</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -331,43 +331,43 @@
</colgroup>
<tbody>
<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>
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+<td><p>01:06.757</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>
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+<td><p>01:05.055</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:56.749</p></td>
+<td><p>01:02.172</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><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>00:32.634</p></td>
+<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>00:31.783</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><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>00:31.184</p></td>
+<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>00:27.091</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>00:24.255</p></td>
+<td><p>00:23.727</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>00:22.829</p></td>
+<td><p>00:22.617</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>00:21.188</p></td>
+<td><p>00:21.223</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:19.031</p></td>
+<td><p>00:18.712</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>00:02.641</p></td>
+<td><p>00:02.755</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
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 0fc9a454e..7cf58873e 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -589,7 +589,7 @@ to run this tutorial with a real device.</p>
<span class="n">lib</span><span class="o">.</span><span class="n">export_library</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">lib_fname</span></a><span class="p">,</span> <span class="n">fcompile</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -648,7 +648,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.1850 16.2433 16.5122 15.8083 0.2441
+ 15.6855 15.6750 15.8212 15.5999 0.0721
</pre></div>
</div>
</div>
diff --git a/docs/how_to/deploy_models/deploy_model_on_rasp.html b/docs/how_to/deploy_models/deploy_model_on_rasp.html
index 4de34a92e..fba1ac58c 100644
--- a/docs/how_to/deploy_models/deploy_model_on_rasp.html
+++ b/docs/how_to/deploy_models/deploy_model_on_rasp.html
@@ -521,7 +521,7 @@ to run this tutorial with a real device.</p>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></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 b1b45a8da..4b0fd39e1 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -431,18 +431,26 @@ be unstable.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>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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/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3878: 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)
/usr/local/lib/python3.7/dist-packages/torchvision/models/detection/anchor_utils.py:127: 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').
@@ -506,7 +514,7 @@ torchvision rcnn models.</p>
<span class="n">vm_exec</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">vm</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span class= [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -537,7 +545,7 @@ 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> ( 2 minutes 52.786 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 51.947 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 2caf58111..6fabbdd9c 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -472,11 +472,7 @@ training. Other models require a full post training calibration.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
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+100%|##########| 13.6M/13.6M [00:00<00:00, 182MB/s]
</pre></div>
</div>
</div>
@@ -526,7 +522,7 @@ standard Relay operators before compilation.</p>
<span class="n">tvm_result</span><span class="p">,</span> <a href="../../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-contrib-graph_executor sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">rt_mod</span></a> <span class="o">=</span> <span class="n">run_tvm_model</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a hr [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -565,7 +561,7 @@ 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)
- 90.4271 90.1947 109.4979 90.0612 1.9289
+ 90.4856 90.1853 101.7039 90.0492 1.6106
</pre></div>
</div>
<div class="admonition note">
@@ -604,7 +600,7 @@ 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 6.230 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 5.382 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 fcc09efdd..b5923c6d6 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -532,7 +532,7 @@ target platform that you are interested in.</p>
<span class="n">lib</span> <span class="o">=</span> <span class="n">relay</span><span class="o">.</span><span class="n">build_module</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">mod</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a><span cl [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -565,7 +565,7 @@ 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)
- 119.3406 119.2620 125.8968 118.1237 0.7838
+ 119.1273 119.1052 121.3175 118.3462 0.3792
</pre></div>
</div>
<div class="admonition note">
@@ -593,7 +593,7 @@ 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 1.296 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 51.042 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 2237caab7..938d2cda4 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -498,13 +498,13 @@ for calibration. But the accuracy might be impacted.</p>
<span class="n">main</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 9.842 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.030 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 14400c800..5186ce221 100644
--- a/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
+++ b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
@@ -436,23 +436,23 @@ 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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+ 39%|###9 | 52264/132723 [00:00<00:01, 74158.62KB/s]
+ 45%|####5 | 59943/132723 [00:00<00:00, 74980.37KB/s]
+ 51%|##### | 67454/132723 [00:00<00:00, 67907.21KB/s]
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+ 63%|######3 | 83798/132723 [00:01<00:00, 74697.29KB/s]
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+ 76%|#######5 | 100244/132723 [00:01<00:00, 78469.19KB/s]
+ 82%|########1 | 108448/132723 [00:01<00:00, 79526.60KB/s]
+ 88%|########7 | 116611/132723 [00:01<00:00, 80151.09KB/s]
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+100%|##########| 132723/132723 [00:01<00:00, 76095.79KB/s]
</pre></div>
</div>
<p>Create TVM runtime and do inference
@@ -480,7 +480,7 @@ Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from h
<span class="n">class_IDs</span><span class="p">,</span> <span class="n">scores</span><span class="p">,</span> <span class="n">bounding_boxs</span> <span class="o">=</span> <span class="n">run</span><span class="p">(</span><span class="n">lib</span><span class="p">,</span> <span class="n">dev</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -495,7 +495,7 @@ 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> ( 2 minutes 15.999 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> ( 2 minutes 17.215 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 06c938684..23c9597ab 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
+++ b/docs/how_to/deploy_models/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>10:16.443</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>10:36.230</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 86%" />
@@ -331,31 +331,31 @@
</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>02:52.786</p></td>
+<td><p>02:51.947</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>02:15.999</p></td>
+<td><p>02:17.215</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>02:01.296</p></td>
+<td><p>01:51.042</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>01:09.842</p></td>
+<td><p>01:41.030</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>01:06.230</p></td>
+<td><p>01:05.382</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>00:28.513</p></td>
+<td><p>00:28.018</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>00:21.772</p></td>
+<td><p>00:21.591</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>
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 6a9c1e161..a365ebba7 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -421,7 +421,7 @@ y: [0.28239584 0.22104536 0.6862221 ]
<span class="nb">print</span><span class="p">(</span><span class="s2">"z: </span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">z_output</span><span class="p">))</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
z: [0.7996937 1.168008 1.4516819]
</pre></div>
@@ -561,7 +561,7 @@ while for all other operations, the bit length is the same between the operands
<span class="c1"># Perhaps as expected, the ``myfloat32`` results and ``float32`` are exactly the same!</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
z: [0.7996937 1.168008 1.4516819]
x: [0.51729786 0.9469626 0.7654598 ]
@@ -604,7 +604,7 @@ 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.zip5750d5e2-eb50-4c4f-bdbf-e2684b503453 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.zip558f0a51-16eb-4b4d-9d50-3adfd645b3ce 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>
@@ -615,7 +615,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
<span class="nb">print</span><span class="p">(</span><span class="n">result</span><span class="o">.</span><span class="n">flatten</span><span class="p">()[:</span><span class="mi">10</span><span class="p">])</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
[ -7.5350165 2.0368009 -12.706646 -5.63786 -12.684058 4.0723605
2.618876 3.4049501 -9.867913 -24.53311 ]
@@ -666,7 +666,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
<span class="nb">print</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Check failed: (lower) is false: FloatImm lowering function for target llvm type 150 not found
</pre></div>
@@ -760,7 +760,7 @@ where the minimum representable custom datatype value is implemented using calls
<span class="n">np</span><span class="o">.</span><span class="n">testing</span><span class="o">.</span><span class="n">assert_array_equal</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="n">result_myfloat</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
[ -7.5350165 2.0368009 -12.706646 -5.63786 -12.684058 4.0723605
2.618876 3.4049501 -9.867913 -24.53311 ]
diff --git a/docs/how_to/extend_tvm/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index 5a3d1d954..074489e3c 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>00:38.162</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:38.898</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -331,15 +331,15 @@
</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>00:35.029</p></td>
+<td><p>00:35.711</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>00:02.248</p></td>
+<td><p>00:02.269</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>00:00.878</p></td>
+<td><p>00:00.912</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_infra.html b/docs/how_to/extend_tvm/use_pass_infra.html
index e39017acd..a3cb3c75d 100644
--- a/docs/how_to/extend_tvm/use_pass_infra.html
+++ b/docs/how_to/extend_tvm/use_pass_infra.html
@@ -428,7 +428,7 @@ examples for each of them.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">mod</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%0 = nn.conv2d(%x, %weight, padding=[0, 0, 0, 0]) /* ty=Tensor[(1, 64, 54, 54), float32] */;
@@ -517,7 +517,7 @@ pass.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">mod1</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%4 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -543,7 +543,7 @@ for users to customize the optimization level that they want to execute.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">mod2</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%3 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -567,7 +567,7 @@ identical addition operations.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">mod3</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
def @main(%x: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %weight: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */) -> Tensor[(1, 64, 54, 54), float32] {
%4 = fn (%p0: Tensor[(1, 64, 56, 56), float32] /* ty=Tensor[(1, 64, 56, 56), float32] */, %p1: Tensor[(64, 64, 3, 3), float32] /* ty=Tensor[(64, 64, 3, 3), float32] */, %p2: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, %p3: Tensor[(1, 64, 54, 54), float32] /* ty=Tensor[(1, 64, 54, 54), float32] */, Primitive=1) -> Tensor[(1, 64, 54, 54), float32] {
@@ -704,7 +704,7 @@ def @main(%x: Tensor[(1, 64, 56, 56), float32], %weight: Tensor[(64, 64, 3, 3),
}
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Running pass: {} The meta data of the pass - pass name: InferType, opt_level: 0, required passes: []
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index f4278a306..3c83695cd 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -507,10 +507,10 @@ 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: 6714us [6714us] (45.57%; 45.57%)
-FoldScaleAxis: 8021us [6us] (54.43%; 54.43%)
- FoldConstant: 8015us [1647us] (54.40%; 99.93%)
- InferType: 6368us [6368us] (43.22%; 79.45%)
+InferType: 6777us [6777us] (45.37%; 45.37%)
+FoldScaleAxis: 8162us [6us] (54.63%; 54.63%)
+ FoldConstant: 8156us [1631us] (54.60%; 99.93%)
+ InferType: 6526us [6526us] (43.68%; 80.01%)
</pre></div>
</div>
</div>
@@ -532,10 +532,10 @@ 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: 6370us [6370us] (44.71%; 44.71%)
-FoldScaleAxis: 7876us [5us] (55.29%; 55.29%)
- FoldConstant: 7871us [1617us] (55.25%; 99.94%)
- InferType: 6255us [6255us] (43.90%; 79.46%)
+InferType: 6586us [6586us] (44.84%; 44.84%)
+FoldScaleAxis: 8103us [5us] (55.16%; 55.16%)
+ FoldConstant: 8098us [1661us] (55.13%; 99.94%)
+ InferType: 6437us [6437us] (43.82%; 79.49%)
</pre></div>
</div>
<p>Register empty list to clear existing instruments.</p>
@@ -659,7 +659,7 @@ profile result.</p>
<span class="c1"># print(profiles)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/optimize_operators/opt_conv_cuda.html b/docs/how_to/optimize_operators/opt_conv_cuda.html
index b01f15ceb..d9fdb25af 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -556,7 +556,7 @@ 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: 33.790407 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 54.186354 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 b30a7cfcc..d3bfa6dea 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -898,7 +898,7 @@ 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: 8.223372 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 8.680402 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 83f9c5bb3..e6e511a38 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -453,8 +453,8 @@ 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: 0.017745
-Baseline: 3.426559
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.017968
+Baseline: 3.258221
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -514,7 +514,7 @@ 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: 0.295974
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.298263
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -581,7 +581,7 @@ 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: 0.319055
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.325893
</pre></div>
</div>
<p>Here is the generated IR after vectorization.</p>
@@ -642,7 +642,7 @@ 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: 0.114382
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.116564
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -725,7 +725,7 @@ 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: 0.109475
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.110210
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -811,7 +811,7 @@ 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: 0.108775
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.111226
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -901,7 +901,7 @@ 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: 0.142174
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.145373
</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 59c8cabba..f7649a1b0 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>00:33.859</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:33.817</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -331,15 +331,15 @@
</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>00:31.646</p></td>
+<td><p>00:31.519</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>00:01.250</p></td>
+<td><p>00:01.274</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>00:00.963</p></td>
+<td><p>00:01.024</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 eb47dd60a..6b6883a9b 100644
--- a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
+++ b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>05:14.471</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>05:15.632</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -331,27 +331,27 @@
</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>02:38.831</p></td>
+<td><p>02:39.433</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>01:18.691</p></td>
+<td><p>01:19.413</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>00:42.987</p></td>
+<td><p>00:42.663</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>00:17.327</p></td>
+<td><p>00:17.525</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:08.385</p></td>
+<td><p>00:08.414</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>00:08.251</p></td>
+<td><p>00:08.184</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 decdcf8bb..af8ba6695 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
@@ -999,7 +999,7 @@ 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: 0.362 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.355 ms
</pre></div>
</div>
</div>
@@ -1562,7 +1562,7 @@ 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> ( 2 minutes 38.831 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 39.433 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_arm.html b/docs/how_to/tune_with_autoscheduler/tune_network_arm.html
index 4b2c0fb81..726bedacf 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_arm.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_arm.html
@@ -597,7 +597,7 @@ The task scheduler will just optimize this objective.</p>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get model...
Extract tasks...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["1037be767e8e18197e87653d81c34558", [1, 7, 7, 1024], [1, 1, 1024, 1024], [1, 1, 1, 1024], [1, 7, 7, 1024]]) ==========
placeholder = PLACEHOLDER [1, 7, 7, 1024]
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 e4e2b312d..f6d70e76c 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -495,7 +495,7 @@ The task scheduler will just optimize this objective.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Extract tasks...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["8654f16aeddf785bad9f028164b3a48d", [1, 56, 56, 64], [1, 1, 64, 64], [1, 56, 56, 64]]) ==========
placeholder = PLACEHOLDER [1, 56, 56, 64]
@@ -896,12 +896,12 @@ so we can read the log file and load the best schedules.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Compile...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 9.9239 9.9329 9.9714 9.8674 0.0429
+ 9.7184 9.7348 9.7544 9.6659 0.0379
</pre></div>
</div>
</div>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_mali.html b/docs/how_to/tune_with_autoscheduler/tune_network_mali.html
index 922dd76ba..7bd4cb9f9 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_mali.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_mali.html
@@ -510,7 +510,7 @@ The task scheduler will just optimize this objective.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Extract tasks...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["1037be767e8e18197e87653d81c34558", [1, 7, 7, 1024], [1, 1, 1024, 1024], [1, 1, 1, 1024], [1, 7, 7, 1024]]) ==========
placeholder = PLACEHOLDER [1, 7, 7, 1024]
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 d8052a654..f56bf34d7 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -518,7 +518,7 @@ The task scheduler will just optimize this objective.</p>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get model...
Extract tasks...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
========== Task 0 (workload key: ["8654f16aeddf785bad9f028164b3a48d", [1, 56, 56, 64], [1, 1, 64, 256], [1, 56, 56, 256]]) ==========
placeholder = PLACEHOLDER [1, 56, 56, 64]
@@ -915,12 +915,12 @@ so we can read the log file and load the best schedules.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Compile...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 747.3096 747.2768 748.7538 745.8983 1.1660
+ 754.4603 754.0814 756.0359 753.2634 1.1631
</pre></div>
</div>
</div>
@@ -942,7 +942,7 @@ 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 18.691 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 19.413 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 fdd082d7d..a830f892f 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
@@ -620,28 +620,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [65536], []),
compute: Buffer(compute_2: Pointer(float32), float32, [65536], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute}
- preflattened_buffer_map = {placeholder_7: placeholder_15: Buffer(placeholder_12, int32, [4916], []), placeholder_5: placeholder_16: Buffer(placeholder_10, float32, [128, 256], []), placeholder_8: placeholder_17: Buffer(placeholder_13, int32, [33], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_9: placeholder_19: Buffer(placeholder_14, float32, [128, 512], [])} {
- for (i0.outer.i1.outer.fused: int32, 0, 256) "parallel" {
- allocate(compute_4: Pointer(global float32), float32, [256]), storage_scope = global {
- for (i.inner.init: int32, 0, 16) {
- for (j.init: int32, 0, 16) {
- compute_5: Buffer(compute_4, float32, [256], [])[((i.inner.init*16) + j.init)] = 0f32
+ preflattened_buffer_map = {placeholder_7: placeholder_15: Buffer(placeholder_12, int32, [4916], []), placeholder_9: placeholder_16: Buffer(placeholder_14, float32, [128, 512], []), placeholder_5: placeholder_17: Buffer(placeholder_10, float32, [128, 256], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_8: placeholder_19: Buffer(placeholder_13, int32, [33], [])} {
+ for (i0.outer.i1.outer.fused: int32, 0, 32) "parallel" {
+ allocate(compute_4: Pointer(global float32), float32, [2048]), storage_scope = global {
+ for (i.outer.inner: int32, 0, 32) {
+ for (i.inner.init: int32, 0, 4) {
+ for (j.init: int32, 0, 16) {
+ compute_5: Buffer(compute_4, float32, [2048], [])[(((i.outer.inner*64) + (i.inner.init*16)) + j.init)] = 0f32
+ }
}
- }
- for (elem_idx: int32, 0, let cse_var_1: int32 = floormod(i0.outer.i1.outer.fused, 32) in (placeholder_3[(cse_var_1 + 1)] - placeholder_3[cse_var_1])) {
- for (i.inner: int32, 0, 16) {
- for (j: int32, 0, 16) {
- let cse_var_2: int32 = floormod(i0.outer.i1.outer.fused, 32)
- if @tir.likely((elem_idx < (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])), dtype=bool) {
- let cse_var_3: int32 = ((i.inner*16) + j)
- compute_5[cse_var_3] = (compute_5[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_2]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 32)*4096) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_2] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, (placeholder_3[(i0.outer.i1.outer.fused + 1)] - placeholder_3[i0.outer.i1.outer.fused])) {
+ for (i.inner: int32, 0, 4) {
+ for (j: int32, 0, 16) {
+ if @tir.likely((elem_idx < (placeholder_3[(i0.outer.i1.outer.fused + 1)] - placeholder_3[i0.outer.i1.outer.fused])), dtype=bool) {
+ let cse_var_1: int32 = (((i.outer.inner*64) + (i.inner*16)) + j)
+ compute_5[cse_var_1] = (compute_5[cse_var_1] + (placeholder_1[(((placeholder_3[i0.outer.i1.outer.fused]*16) + (elem_idx*16)) + j)]*max(placeholder[(((i.outer.inner*1024) + (i.inner*256)) + placeholder_2[(placeholder_3[i0.outer.i1.outer.fused] + elem_idx)])], 0f32)))
+ }
}
}
}
}
- for (i0.inner: int32, 0, 16) {
- let cse_var_4: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*8192) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 32)*16))
- compute[ramp(cse_var_4, 1, 16)] = max((compute_5[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_4, 1, 16)]), broadcast(0f32, 16))
+ for (i0.inner: int32, 0, 128) {
+ let cse_var_2: int32 = ((i0.inner*512) + (i0.outer.i1.outer.fused*16))
+ compute[ramp(cse_var_2, 1, 16)] = max((compute_5[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_2, 1, 16)]), broadcast(0f32, 16))
}
}
}
@@ -679,7 +680,7 @@ 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: 1.563 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.465 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 0f3aba329..cc1a6020f 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>00:42.701</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:43.805</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -331,11 +331,11 @@
</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>00:42.668</p></td>
+<td><p>00:43.773</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>
-<td><p>00:00.020</p></td>
+<td><p>00:00.019</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-cuda-py"><span class="std std-ref">Auto-tuning a Convolutional Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_cuda.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 1bcc28ea8..9cde19a86 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -554,9 +554,9 @@ No: 1 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -677,9 +677,9 @@ No: 2 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -800,9 +800,9 @@ No: 3 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -923,9 +923,9 @@ No: 4 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1046,9 +1046,9 @@ No: 5 GFLOPS: 0.00/0.00 result: Traceback (most recent call last):
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1164,15 +1164,15 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4, 32]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2885496
-No: 6 GFLOPS: 67.66/67.66 result: MeasureResult(costs=(0.003421460166666667,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.5774593353271484, timestamp=1656118430.2414901) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
-No: 7 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 6 GFLOPS: 111.99/111.99 result: MeasureResult(costs=(0.0020671165714285715,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8865644931793213, timestamp=1656358761.48969) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
+No: 7 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1288,14 +1288,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6225319
-No: 8 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 8 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1411,14 +1411,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,943546
-No: 9 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 9 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1534,7 +1534,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 32]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2868708
-No: 10 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 10 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 142, in build
res = future.result()
File "/usr/lib/python3.7/concurrent/futures/_base.py", line 435, in result
@@ -1552,14 +1552,14 @@ No: 10 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
TimeoutError
[('tile_f', [-1, 32, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4691833
-No: 11 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 11 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1675,14 +1675,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1042124
-No: 12 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 12 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1798,14 +1798,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10013405
-No: 13 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 13 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -1921,14 +1921,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6732082
-No: 14 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 14 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2044,14 +2044,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7536735
-No: 15 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 15 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2167,14 +2167,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,482121
-No: 16 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 16 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2290,14 +2290,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 32, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2824525
-No: 17 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 17 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2413,14 +2413,14 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4559286
-No: 18 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 18 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
func = build(s, args, target_host=task.target_host, runtime=runtime)
- File "/workspace/python/tvm/driver/build_module.py", line 225, in build
+ File "/workspace/python/tvm/driver/build_module.py", line 228, in build
input_mod = lower(inputs, args, name=name, binds=binds)
- File "/workspace/python/tvm/driver/build_module.py", line 133, in lower
+ 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 276, in tvm._ffi._cy3.core.FuncCall
@@ -2536,7 +2536,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, 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, 32, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 512]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9677544
-No: 19 GFLOPS: 0.00/67.66 result: Traceback (most recent call last):
+No: 19 GFLOPS: 0.00/111.99 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 738, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 702, in run_through_rpc
@@ -2624,7 +2624,7 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007f5da624ffa2
+ 12: 0x00007f912d912fa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2689,7 +2689,7 @@ Traceback (most recent call last):
21: _PyFunction_FastCallKeywords
20: _PyEval_EvalFrameDefault
19: _PyFunction_FastCall [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6390073
-No: 20 GFLOPS: 144.20/144.20 result: MeasureResult(costs=(0.0016053873300000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3985545635223389, timestamp=1656118456.6012232) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
+No: 20 GFLOPS: 144.29/144.29 result: MeasureResult(costs=(0.0016043764699999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.421783208847046, timestamp=1656358788.042704) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
</pre></div>
</div>
<p>Finally we can inspect the best config from log file, check correctness,
@@ -2730,7 +2730,7 @@ and measure running time.</p>
Best config:
[('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
Finish loading 20 records
-Time cost of this operator: 0.001973
+Time cost of this operator: 0.001995
</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 df7e18898..175f51d3d 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -573,15 +573,15 @@ the tuned operator.</p>
<span class="k">del</span> <span class="n">debug_module</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 317.5 98.75 (1, 2, 10, 10, 3) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.097 0.963 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.921 0.286 (1, 1, 10, 10, 3) 1 1
-Total_time - 321.518 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 310.2 98.731 (1, 2, 10, 10, 3) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.085 0.982 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.901 0.287 (1, 1, 10, 10, 3) 1 1
+Total_time - 314.186 - - - -
</pre></div>
</div>
</div>
@@ -629,15 +629,15 @@ Total_time -
<span class="k">del</span> <span class="n">debug_module</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 119.2 97.748 (1, 6, 10, 10, 1) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.822 1.494 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.924 0.758 (1, 1, 10, 10, 3) 1 1
-Total_time - 121.946 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 192.2 98.424 (1, 1, 10, 10, 6) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.16 1.106 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.918 0.47 (1, 3, 10, 10, 1) 1 1
+Total_time - 195.278 - - - -
</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_train.html b/docs/how_to/work_with_microtvm/micro_train.html
index acd3573ba..75f72e8bb 100644
--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -510,7 +510,7 @@ 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/tmpsjy2eoei/images/random'
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>'/tmp/tmp8dkuez43/images/random'
</pre></div>
</div>
</div>
@@ -570,8 +570,8 @@ 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="[1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [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/tmpsjy2eoei/images/target contains 8144 images
-/tmp/tmpsjy2eoei/images/random contains 5000 images
+<img src="../../_images/sphx_glr_micro_train_001.png" srcset="../../_images/sphx_glr_micro_train_001.png" alt="[1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [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/tmp8dkuez43/images/target contains 8144 images
+/tmp/tmp8dkuez43/images/random contains 5000 images
</pre></div>
</div>
</div>
@@ -683,13 +683,13 @@ 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 - 54s - loss: 0.2170 - accuracy: 0.9258 - val_loss: 0.1394 - val_accuracy: 0.9581
+328/328 - 55s - loss: 0.2475 - accuracy: 0.9155 - val_loss: 0.1382 - val_accuracy: 0.9535
Epoch 2/3
-328/328 - 51s - loss: 0.1005 - accuracy: 0.9610 - val_loss: 0.1354 - val_accuracy: 0.9539
+328/328 - 52s - loss: 0.1015 - accuracy: 0.9623 - val_loss: 0.1143 - val_accuracy: 0.9611
Epoch 3/3
-328/328 - 51s - loss: 0.0683 - accuracy: 0.9746 - val_loss: 0.1263 - val_accuracy: 0.9569
+328/328 - 52s - loss: 0.0693 - accuracy: 0.9734 - val_loss: 0.1179 - val_accuracy: 0.9637
-<keras.callbacks.History object at 0x7fa83a1e9f90>
+<keras.callbacks.History object at 0x7f809239d8d0>
</pre></div>
</div>
</div>
@@ -813,7 +813,7 @@ Relay model into the MLF intermediate representation. From here, we just need to
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -951,7 +951,7 @@ 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> ( 7 minutes 57.481 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 12 minutes 57.097 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 1bfe4b02d..fe9accaf3 100644
--- a/docs/how_to/work_with_microtvm/sg_execution_times.html
+++ b/docs/how_to/work_with_microtvm/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>08:43.358</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
+<p><strong>13:42.888</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -331,15 +331,15 @@
</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>
-<td><p>07:57.481</p></td>
+<td><p>12:57.097</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>
-<td><p>00:42.472</p></td>
+<td><p>00:42.363</p></td>
<td><p>0.0 MB</p></td>
</tr>
<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>00:03.429</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="micro_ethosu.html#sphx-glr-how-to-work-with-microtvm-micro-ethosu-py"><span class="std std-ref">Running TVM on bare metal Arm(R) Cortex(R)-M55 CPU and Ethos(TM)-U55 NPU with CMSIS-NN</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_ethosu.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 0e39164b1..f89992d43 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>00:11.345</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:11.489</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -331,11 +331,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><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>
-<td><p>00:09.758</p></td>
+<td><p>00:09.773</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>
-<td><p>00:01.582</p></td>
+<td><p>00:01.710</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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_relay/using_external_lib.html b/docs/how_to/work_with_relay/using_external_lib.html
index c9b871c6f..e702667d5 100644
--- a/docs/how_to/work_with_relay/using_external_lib.html
+++ b/docs/how_to/work_with_relay/using_external_lib.html
@@ -424,7 +424,7 @@ By setting the logging level to DEBUG, the result of Relay graph compilation wil
<span class="n">out_cuda</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -848,7 +848,7 @@ To do that, all we need to do is to append the option ” -libs=cudnn” to the
<span class="n">out_cudnn</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/how_to/work_with_schedules/intrin_math.html b/docs/how_to/work_with_schedules/intrin_math.html
index c26aa6f40..70ca6163f 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -515,7 +515,7 @@ 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 0x7fa7e796c440>
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7f8011417440>
</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 f1374bc1b..c9ad9aa0a 100644
--- a/docs/how_to/work_with_schedules/sg_execution_times.html
+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -322,7 +322,7 @@
<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>00:03.956</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:04.133</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -331,23 +331,23 @@
</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>00:01.821</p></td>
+<td><p>00:01.909</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>00:00.965</p></td>
+<td><p>00:01.006</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>00:00.508</p></td>
+<td><p>00:00.531</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>
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<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>
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<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>
@@ -355,7 +355,7 @@
<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>
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+<td><p>00:00.028</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>
diff --git a/docs/how_to/work_with_schedules/tensorize.html b/docs/how_to/work_with_schedules/tensorize.html
index 0b170ef9e..3cc074b62 100644
--- a/docs/how_to/work_with_schedules/tensorize.html
+++ b/docs/how_to/work_with_schedules/tensorize.html
@@ -571,7 +571,7 @@ The importing needs to happen before the tensorized GEMV being executed.</p>
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C}
preflattened_buffer_map = {A_1: A_3: Buffer(A_2, float32, [1024, 64], []), B_1: B_3: Buffer(B_2, float32, [512, 64], []), C_1: C_3: Buffer(C_2, float32, [1024, 512], [])} {
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+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpzt3v1dua/input0.cc'\nsource_filename = \"/tmp/tmpzt3v1dua/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/objects.inv b/docs/objects.inv
index 49ecc3e4a..21c38cc89 100644
Binary files a/docs/objects.inv and b/docs/objects.inv differ
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc-members.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc-members.html
index 1b3654339..990645d88 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc-members.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc-members.html
@@ -88,15 +88,16 @@ $(function() {
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#affdf1b8cdb36e140de7b3ad7064e4617">operator==</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a303f216285e5f317f35a3abf9be28285">PyPostproc</a>(PyPostprocNode::FInitializeWithTuneContext f_initialize_with_tune_context, PyPostprocNode::FApply f_apply, PyPostprocNode::FAsString f_as_string)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a8a8e8e047dcdcf89ad9d96eed47c293a">RewriteCooperativeFetch</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#ad9ba0ccb7c8c2340ce64d8b0cb4d141c">RewriteParallelVectorizeUnroll</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a08348595d8c50afe0167a986e034d616">RewriteReductionBlock</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a95db036cfced4c2575367a26a41498ff">RewriteTensorize</a>(bool vectorize_init_loop=false)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a1836b2278bc24fdc227c490896d92980">RewriteUnboundBlock</a>(int max_threadblocks)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#ae31a5b9f40781d60a2901994ead700e8">same_as</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a3f1d6e8bd5753810d8baa0cfb899581a">TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS</a>(Postproc, ObjectRef, PostprocNode)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a4e7cdb1574b93a59e784d70aa47b8da7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a0ae0da21d247cd87ea94fe3777c4405e">use_count</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a7106b1742068c45966d6be5f4b8394aa">VerifyGPUCode</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a855ed7567cf6af092d19b59ceea52426">RewriteLayout</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#ad9ba0ccb7c8c2340ce64d8b0cb4d141c">RewriteParallelVectorizeUnroll</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a08348595d8c50afe0167a986e034d616">RewriteReductionBlock</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a95db036cfced4c2575367a26a41498ff">RewriteTensorize</a>(bool vectorize_init_loop=false)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a1836b2278bc24fdc227c490896d92980">RewriteUnboundBlock</a>(int max_threadblocks)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#ae31a5b9f40781d60a2901994ead700e8">same_as</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a3f1d6e8bd5753810d8baa0cfb899581a">TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS</a>(Postproc, ObjectRef, PostprocNode)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a4e7cdb1574b93a59e784d70aa47b8da7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a0ae0da21d247cd87ea94fe3777c4405e">use_count</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a7106b1742068c45966d6be5f4b8394aa">VerifyGPUCode</a>()</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
</table></div><!-- contents -->
<!-- start footer part -->
<hr class="footer"/><address class="footer"><small>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc.html
index b0e5c663f..60234233e 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc.html
@@ -78,13 +78,13 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::meta_schedule::Postproc:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1Postproc__inherit__graph.svg" width="220" height="610"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1Postproc__inherit__graph.svg" width="220" height="624"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::meta_schedule::Postproc:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1Postproc__coll__graph.svg" width="220" height="898"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1Postproc__coll__graph.svg" width="220" height="912"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<table class="memberdecls">
@@ -152,6 +152,9 @@ Static Public Member Functions</h2></td></tr>
<tr class="memitem:a7106b1742068c45966d6be5f4b8394aa"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">Postproc</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a7106b1742068c45966d6be5f4b8394aa">VerifyGPUCode</a> ()</td></tr>
<tr class="memdesc:a7106b1742068c45966d6be5f4b8394aa"><td class="mdescLeft"> </td><td class="mdescRight">Creates a postprocessor that verifies if the GPU code is correct. <a href="#a7106b1742068c45966d6be5f4b8394aa">More...</a><br /></td></tr>
<tr class="separator:a7106b1742068c45966d6be5f4b8394aa"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a855ed7567cf6af092d19b59ceea52426"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">Postproc</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a855ed7567cf6af092d19b59ceea52426">RewriteLayout</a> ()</td></tr>
+<tr class="memdesc:a855ed7567cf6af092d19b59ceea52426"><td class="mdescLeft"> </td><td class="mdescRight">Creates a postprocessor that rewrites the layout of input tensor. <a href="#a855ed7567cf6af092d19b59ceea52426">More...</a><br /></td></tr>
+<tr class="separator:a855ed7567cf6af092d19b59ceea52426"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
@@ -293,6 +296,35 @@ Additional Inherited Members</h2></td></tr>
<p>Create a postprocessor that rewrites the cooperative fetch annotation to actual vectorized cooperative fetching in loop bindings. </p>
<dl class="section return"><dt>Returns</dt><dd>The postprocessor created. </dd></dl>
+</div>
+</div>
+<a id="a855ed7567cf6af092d19b59ceea52426"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a855ed7567cf6af092d19b59ceea52426">◆ </a></span>RewriteLayout()</h2>
+
+<div class="memitem">
+<div class="memproto">
+<table class="mlabels">
+ <tr>
+ <td class="mlabels-left">
+ <table class="memname">
+ <tr>
+ <td class="memname">static <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html">Postproc</a> tvm::meta_schedule::Postproc::RewriteLayout </td>
+ <td>(</td>
+ <td class="paramname"></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+ </td>
+ <td class="mlabels-right">
+<span class="mlabels"><span class="mlabel">static</span></span> </td>
+ </tr>
+</table>
+</div><div class="memdoc">
+
+<p>Creates a postprocessor that rewrites the layout of input tensor. </p>
+<dl class="section note"><dt>Note</dt><dd>Weight layout rewrite is supported so far, activation layout rewrite will be added. </dd></dl>
+<dl class="section return"><dt>Returns</dt><dd>The postprocessor created </dd></dl>
+
</div>
</div>
<a id="ad9ba0ccb7c8c2340ce64d8b0cb4d141c"></a>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc__coll__graph.svg b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc__coll__graph.svg
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+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc__coll__graph.svg
@@ -4,96 +4,97 @@
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+<polygon fill="#ffffff" stroke="#000000" points="11.5,-227.5 11.5,-449.5 145.5,-449.5 145.5,-227.5 11.5,-227.5"/>
+<text text-anchor="middle" x="78.5" y="-437.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectRef</text>
+<polyline fill="none" stroke="#000000" points="11.5,-430.5 145.5,-430.5 "/>
+<text text-anchor="start" x="19.5" y="-418.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<polyline fill="none" stroke="#000000" points="11.5,-411.5 145.5,-411.5 "/>
+<text text-anchor="start" x="19.5" y="-399.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
<text text-anchor="start" x="19.5" y="-388.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
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-<text text-anchor="start" x="19.5" y="-355.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator==()</text>
-<text text-anchor="start" x="19.5" y="-344.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator!=()</text>
-<text text-anchor="start" x="19.5" y="-333.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator<()</text>
-<text text-anchor="start" x="19.5" y="-322.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ defined()</text>
-<text text-anchor="start" x="19.5" y="-311.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
-<text text-anchor="start" x="19.5" y="-300.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
-<text text-anchor="start" x="19.5" y="-289.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
-<text text-anchor="start" x="19.5" y="-278.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ use_count()</text>
-<text text-anchor="start" x="19.5" y="-267.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ as()</text>
-<text text-anchor="start" x="19.5" y="-256.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># get_mutable()</text>
-<text text-anchor="start" x="19.5" y="-245.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DowncastNoCheck()</text>
-<text text-anchor="start" x="19.5" y="-234.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># FFIClearAfterMove()</text>
-<text text-anchor="start" x="19.5" y="-223.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetDataPtr()</text>
+<text text-anchor="start" x="19.5" y="-377.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ same_as()</text>
+<text text-anchor="start" x="19.5" y="-366.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator==()</text>
+<text text-anchor="start" x="19.5" y="-355.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator!=()</text>
+<text text-anchor="start" x="19.5" y="-344.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator<()</text>
+<text text-anchor="start" x="19.5" y="-333.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ defined()</text>
+<text text-anchor="start" x="19.5" y="-322.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
+<text text-anchor="start" x="19.5" y="-311.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
+<text text-anchor="start" x="19.5" y="-300.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="19.5" y="-289.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ use_count()</text>
+<text text-anchor="start" x="19.5" y="-278.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ as()</text>
+<text text-anchor="start" x="19.5" y="-267.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># get_mutable()</text>
+<text text-anchor="start" x="19.5" y="-256.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DowncastNoCheck()</text>
+<text text-anchor="start" x="19.5" y="-245.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># FFIClearAfterMove()</text>
+<text text-anchor="start" x="19.5" y="-234.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetDataPtr()</text>
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<title>Node3->Node2</title>
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-<polygon fill="none" stroke="#191970" points="75.0001,-206.1652 78.5,-216.1652 82.0001,-206.1652 75.0001,-206.1652"/>
+<path fill="none" stroke="#191970" d="M78.5,-217.3207C78.5,-207.9853 78.5,-198.6454 78.5,-189.5206"/>
+<polygon fill="none" stroke="#191970" points="75.0001,-217.4384 78.5,-227.4384 82.0001,-217.4385 75.0001,-217.4384"/>
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<g id="a_node3"><a xlink:href="classtvm_1_1runtime_1_1ObjectPtr.html" target="_top" xlink:title="{tvm::runtime::ObjectPtr\l\< tvm::runtime::Object \>\n||+ ObjectPtr()\l+ ObjectPtr()\l+ ObjectPtr()\l+ ObjectPtr()\l+ ObjectPtr()\l+ ObjectPtr()\l+ ~ObjectPtr()\l+ swap()\l+ get()\l+ operator-\>()\land 11 more...\l}">
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+<text text-anchor="start" x="16.5" y="-663.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectPtr</text>
+<text text-anchor="middle" x="78.5" y="-652.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::runtime::Object ></text>
+<polyline fill="none" stroke="#000000" points="8.5,-645.5 148.5,-645.5 "/>
+<text text-anchor="middle" x="78.5" y="-633.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polyline fill="none" stroke="#000000" points="8.5,-626.5 148.5,-626.5 "/>
+<text text-anchor="start" x="16.5" y="-614.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
<text text-anchor="start" x="16.5" y="-603.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
<text text-anchor="start" x="16.5" y="-592.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
<text text-anchor="start" x="16.5" y="-581.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
<text text-anchor="start" x="16.5" y="-570.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
<text text-anchor="start" x="16.5" y="-559.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
-<text text-anchor="start" x="16.5" y="-548.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectPtr()</text>
-<text text-anchor="start" x="16.5" y="-537.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~ObjectPtr()</text>
-<text text-anchor="start" x="16.5" y="-526.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ swap()</text>
-<text text-anchor="start" x="16.5" y="-515.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
-<text text-anchor="start" x="16.5" y="-504.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
-<text text-anchor="start" x="16.5" y="-493.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 11 more...</text>
+<text text-anchor="start" x="16.5" y="-548.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~ObjectPtr()</text>
+<text text-anchor="start" x="16.5" y="-537.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ swap()</text>
+<text text-anchor="start" x="16.5" y="-526.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
+<text text-anchor="start" x="16.5" y="-515.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
+<text text-anchor="start" x="16.5" y="-504.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 11 more...</text>
</a>
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<!-- Node4->Node3 -->
<g id="edge2" class="edge">
<title>Node4->Node3</title>
-<path fill="none" stroke="#404040" d="M78.5,-486.3167C78.5,-474.8765 78.5,-463.0062 78.5,-451.1402"/>
-<polygon fill="none" stroke="#404040" points="78.5001,-450.7944 74.5,-444.7944 78.5,-438.7944 82.5,-444.7943 78.5001,-450.7944"/>
-<text text-anchor="middle" x="98" y="-460" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #data_</text>
+<path fill="none" stroke="#404040" d="M78.5,-497.3167C78.5,-485.8765 78.5,-474.0062 78.5,-462.1402"/>
+<polygon fill="none" stroke="#404040" points="78.5001,-461.7944 74.5,-455.7944 78.5,-449.7944 82.5,-455.7943 78.5001,-461.7944"/>
+<text text-anchor="middle" x="98" y="-471" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #data_</text>
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index 940a6edd8..39eb59622 100644
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+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Postproc__inherit__graph.svg
@@ -4,66 +4,67 @@
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<title>tvm::meta_schedule::Postproc</title>
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+<polygon fill="#ffffff" stroke="transparent" points="-4,4 -4,-464 161,-464 161,4 -4,4"/>
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<g id="node1" class="node">
<title>Node0</title>
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-<text text-anchor="start" x="8" y="-166.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
-<text text-anchor="middle" x="78.5" y="-155.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::Postproc</text>
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-<text text-anchor="start" x="8" y="-117.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_MUTABLE</text>
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-<text text-anchor="start" x="8" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RewriteReductionBlock()</text>
-<text text-anchor="start" x="8" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RewriteUnboundBlock()</text>
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-<text text-anchor="start" x="8" y="-7.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ VerifyGPUCode()</text>
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+<text text-anchor="start" x="8" y="-177.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
+<text text-anchor="middle" x="78.5" y="-166.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::Postproc</text>
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+<text text-anchor="start" x="8" y="-128.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_MUTABLE</text>
+<text text-anchor="start" x="8" y="-117.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_OBJECT_REF_METHODS()</text>
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+<text text-anchor="start" x="8" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Unroll()</text>
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-<text text-anchor="middle" x="78.5" y="-436.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectRef</text>
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+<polygon fill="#ffffff" stroke="#000000" points="11.5,-226.5 11.5,-459.5 145.5,-459.5 145.5,-226.5 11.5,-226.5"/>
+<text text-anchor="middle" x="78.5" y="-447.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectRef</text>
+<polyline fill="none" stroke="#000000" points="11.5,-440.5 145.5,-440.5 "/>
+<text text-anchor="start" x="19.5" y="-428.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<text text-anchor="start" x="19.5" y="-417.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># data_</text>
+<polyline fill="none" stroke="#000000" points="11.5,-410.5 145.5,-410.5 "/>
+<text text-anchor="start" x="19.5" y="-398.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
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+<text text-anchor="start" x="19.5" y="-376.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ same_as()</text>
+<text text-anchor="start" x="19.5" y="-365.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator==()</text>
+<text text-anchor="start" x="19.5" y="-354.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator!=()</text>
+<text text-anchor="start" x="19.5" y="-343.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator<()</text>
+<text text-anchor="start" x="19.5" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ defined()</text>
+<text text-anchor="start" x="19.5" y="-321.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
+<text text-anchor="start" x="19.5" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
+<text text-anchor="start" x="19.5" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="19.5" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ use_count()</text>
+<text text-anchor="start" x="19.5" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ as()</text>
+<text text-anchor="start" x="19.5" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># get_mutable()</text>
+<text text-anchor="start" x="19.5" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DowncastNoCheck()</text>
+<text text-anchor="start" x="19.5" y="-244.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># FFIClearAfterMove()</text>
+<text text-anchor="start" x="19.5" y="-233.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetDataPtr()</text>
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diff --git a/docs/reference/api/doxygen/functions_func_r.html b/docs/reference/api/doxygen/functions_func_r.html
index 8d1689cb4..f67a3eb73 100644
--- a/docs/reference/api/doxygen/functions_func_r.html
+++ b/docs/reference/api/doxygen/functions_func_r.html
@@ -281,7 +281,7 @@ $(function() {
, <a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html#a4c93a9094db80cace013ef02e6bcd724">tvm::relay::MixedModeMutator</a>
</li>
<li>Rewrite_()
-: <a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html#ad6eed16eb7ac760434705411bbbde461">tvm::relay::ExprRewriter</a>
+: <a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html#a4a17923abf82534b9574ec74b893a907">tvm::relay::ExprRewriter</a>
, <a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html#a3b53908f4b8cc3708ca75892e47f0929">tvm::relay::MixedModeMutator</a>
</li>
<li>RewriteCooperativeFetch()
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</li>
<li>RewriteLayout()
: <a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeDAG.html#ae36f2943628beb48fbf9b473bb350253">tvm::auto_scheduler::ComputeDAG</a>
+, <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a855ed7567cf6af092d19b59ceea52426">tvm::meta_schedule::Postproc</a>
</li>
<li>RewriteParallelVectorizeUnroll()
: <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#ad9ba0ccb7c8c2340ce64d8b0cb4d141c">tvm::meta_schedule::Postproc</a>
diff --git a/docs/reference/api/doxygen/functions_r.html b/docs/reference/api/doxygen/functions_r.html
index 3830d83a8..59b5c0512 100644
--- a/docs/reference/api/doxygen/functions_r.html
+++ b/docs/reference/api/doxygen/functions_r.html
@@ -459,8 +459,8 @@ $(function() {
, <a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html#a4c93a9094db80cace013ef02e6bcd724">tvm::relay::MixedModeMutator</a>
</li>
<li>Rewrite_()
-: <a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html#a5d2966def9bd344cad258de9f338e1be">tvm::relay::ExprRewriter</a>
-, <a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html#a3b53908f4b8cc3708ca75892e47f0929">tvm::relay::MixedModeMutator</a>
+: <a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html#a682e33e435dd74c1ebfc521b9e33a106">tvm::relay::ExprRewriter</a>
+, <a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html#aedab19fa2803a80d4148f83c1c4b0814">tvm::relay::MixedModeMutator</a>
</li>
<li>rewrite_once
: <a class="el" href="classtvm_1_1relay_1_1DFPatternCallbackNode.html#a6e4c091ba92fee08251d29633da9b8b8">tvm::relay::DFPatternCallbackNode</a>
@@ -473,6 +473,7 @@ $(function() {
</li>
<li>RewriteLayout()
: <a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeDAG.html#ae36f2943628beb48fbf9b473bb350253">tvm::auto_scheduler::ComputeDAG</a>
+, <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#a855ed7567cf6af092d19b59ceea52426">tvm::meta_schedule::Postproc</a>
</li>
<li>RewriteParallelVectorizeUnroll()
: <a class="el" href="classtvm_1_1meta__schedule_1_1Postproc.html#ad9ba0ccb7c8c2340ce64d8b0cb4d141c">tvm::meta_schedule::Postproc</a>
@@ -494,7 +495,7 @@ $(function() {
: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#ab185c8eac1065290d84d58e7f4617232">tvm::tir::ScheduleNode</a>
</li>
<li>RfactorStep()
-: <a class="el" href="classtvm_1_1auto__scheduler_1_1RfactorStep.html#a95575c21441177634178245ab562cb4f">tvm::auto_scheduler::RfactorStep</a>
+: <a class="el" href="classtvm_1_1auto__scheduler_1_1RfactorStep.html#a26e6f85b55307f18fab4469e3bd4be0c">tvm::auto_scheduler::RfactorStep</a>
</li>
<li>rhs
: <a class="el" href="classtvm_1_1relay_1_1ClauseNode.html#a93217eeea15c1f7c1a659da3da86d3bd">tvm::relay::ClauseNode</a>
diff --git a/docs/reference/api/doxygen/namespacemembers.html b/docs/reference/api/doxygen/namespacemembers.html
index 4e40e164c..5371a516c 100644
--- a/docs/reference/api/doxygen/namespacemembers.html
+++ b/docs/reference/api/doxygen/namespacemembers.html
@@ -121,6 +121,9 @@ $(function() {
<li>AnnotateSpans()
: <a class="el" href="namespacetvm_1_1parser.html#aae21e0014c5fba6a9797a6a016979ec7">tvm::parser</a>
</li>
+<li>AnnotateUsedMemory()
+: <a class="el" href="namespacetvm_1_1relay_1_1transform.html#a6adb5ecf3c0fbe3c91d37e90795d91de">tvm::relay::transform</a>
+</li>
<li>any()
: <a class="el" href="namespacetvm.html#a5efd9942cdee5a56cfc438ba523c04f0">tvm</a>
</li>
diff --git a/docs/reference/api/doxygen/namespacemembers_func.html b/docs/reference/api/doxygen/namespacemembers_func.html
index d60096352..80305c8cb 100644
--- a/docs/reference/api/doxygen/namespacemembers_func.html
+++ b/docs/reference/api/doxygen/namespacemembers_func.html
@@ -118,6 +118,9 @@ $(function() {
<li>AnnotateSpans()
: <a class="el" href="namespacetvm_1_1parser.html#aae21e0014c5fba6a9797a6a016979ec7">tvm::parser</a>
</li>
+<li>AnnotateUsedMemory()
+: <a class="el" href="namespacetvm_1_1relay_1_1transform.html#a6adb5ecf3c0fbe3c91d37e90795d91de">tvm::relay::transform</a>
+</li>
<li>any()
: <a class="el" href="namespacetvm.html#a5efd9942cdee5a56cfc438ba523c04f0">tvm</a>
, <a class="el" href="namespacetvm_1_1topi.html#afb48d90f345698b1b3417bafa1911504">tvm::topi</a>
diff --git a/docs/reference/api/doxygen/namespacemembers_func_p.html b/docs/reference/api/doxygen/namespacemembers_func_p.html
index 7c33a5248..803915cb0 100644
--- a/docs/reference/api/doxygen/namespacemembers_func_p.html
+++ b/docs/reference/api/doxygen/namespacemembers_func_p.html
@@ -67,12 +67,12 @@ $(function() {
<li>PackImportsToLLVM()
: <a class="el" href="namespacetvm_1_1codegen.html#ab2cd2a65bac4b26427a8ca0abe4e0bd6">tvm::codegen</a>
</li>
-<li>pad()
-: <a class="el" href="namespacetvm_1_1topi.html#a3305d377f96cd20c23032eeada2756d5">tvm::topi</a>
-</li>
<li>Pad()
: <a class="el" href="namespacetvm_1_1topi.html#a97c798d0a0ec20a95d351618b83d5121">tvm::topi</a>
</li>
+<li>pad()
+: <a class="el" href="namespacetvm_1_1topi.html#a3305d377f96cd20c23032eeada2756d5">tvm::topi</a>
+</li>
<li>parallel_for()
: <a class="el" href="namespacetvm_1_1support.html#a8bf1225e8bb1db575578ca2d645fb23c">tvm::support</a>
</li>
diff --git a/docs/reference/api/doxygen/namespacemembers_p.html b/docs/reference/api/doxygen/namespacemembers_p.html
index eb3b32fd5..33cb466d5 100644
--- a/docs/reference/api/doxygen/namespacemembers_p.html
+++ b/docs/reference/api/doxygen/namespacemembers_p.html
@@ -67,12 +67,12 @@ $(function() {
<li>PackImportsToLLVM()
: <a class="el" href="namespacetvm_1_1codegen.html#ab2cd2a65bac4b26427a8ca0abe4e0bd6">tvm::codegen</a>
</li>
-<li>pad()
-: <a class="el" href="namespacetvm_1_1topi.html#a3305d377f96cd20c23032eeada2756d5">tvm::topi</a>
-</li>
<li>Pad()
: <a class="el" href="namespacetvm_1_1topi.html#a97c798d0a0ec20a95d351618b83d5121">tvm::topi</a>
</li>
+<li>pad()
+: <a class="el" href="namespacetvm_1_1topi.html#a3305d377f96cd20c23032eeada2756d5">tvm::topi</a>
+</li>
<li>parallel_for()
: <a class="el" href="namespacetvm_1_1support.html#a8bf1225e8bb1db575578ca2d645fb23c">tvm::support</a>
</li>
diff --git a/docs/reference/api/doxygen/namespacetvm_1_1relay_1_1transform.html b/docs/reference/api/doxygen/namespacetvm_1_1relay_1_1transform.html
index cc0e2f91e..1fdeb0aaa 100644
--- a/docs/reference/api/doxygen/namespacetvm_1_1relay_1_1transform.html
+++ b/docs/reference/api/doxygen/namespacetvm_1_1relay_1_1transform.html
@@ -217,6 +217,9 @@ Functions</h2></td></tr>
<tr class="memitem:af719f05ee653ea465589a38747b35e22"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#afa666ade112e9955059095d695238a9a">Pass</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#af719f05ee653ea465589a38747b35e22">FlattenAtrousConv</a> ()</td></tr>
<tr class="memdesc:af719f05ee653ea465589a38747b35e22"><td class="mdescLeft"> </td><td class="mdescRight">This transform flattens atrous convolution, which corresponds to the sequence of operations: "space_to_batch_nd"->"conv2d"->"batch_to_space_nd" and convert them into subgraphs with a convolution with the modified "dilation" and recalculated "padding" parameters. <a href="#af719f05ee653ea465589a38747b35e22">More...</a><br /></td></tr>
<tr class="separator:af719f05ee653ea465589a38747b35e22"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#afa666ade112e9955059095d695238a9a">Pass</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#a6adb5ecf3c0fbe3c91d37e90795d91de">AnnotateUsedMemory</a> ()</td></tr>
+<tr class="memdesc:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="mdescLeft"> </td><td class="mdescRight">Annotates the minimum required memory of each primitive function callsite by analyzing the liveness of the input/output tensors at each function callsite and calculating the total amount of memory these tensors require. This is added as a "used_memory" annotation to the function in question as a list of the number of bytes for each callsite. In addition, the containing function i [...]
+<tr class="separator:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<h2 class="groupheader">Typedef Documentation</h2>
<a id="afa666ade112e9955059095d695238a9a"></a>
@@ -336,6 +339,26 @@ Functions</h2></td></tr>
<p>Alternate the layouts of operators or replace primitive operators with other expressions. </p>
<dl class="section return"><dt>Returns</dt><dd>The pass. </dd></dl>
+</div>
+</div>
+<a id="a6adb5ecf3c0fbe3c91d37e90795d91de"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a6adb5ecf3c0fbe3c91d37e90795d91de">◆ </a></span>AnnotateUsedMemory()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#afa666ade112e9955059095d695238a9a">Pass</a> tvm::relay::transform::AnnotateUsedMemory </td>
+ <td>(</td>
+ <td class="paramname"></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+<p>Annotates the minimum required memory of each primitive function callsite by analyzing the liveness of the input/output tensors at each function callsite and calculating the total amount of memory these tensors require. This is added as a "used_memory" annotation to the function in question as a list of the number of bytes for each callsite. In addition, the containing function is annotated with an "io_used_memory" annotation which refers to the total memory required for the IO tensors. </p>
+<p>Note: This pass does not support dynamic shapes, it is the users responsibility to check this pass isn't applied where dynamic shapes may be input. </p>
+
</div>
</div>
<a id="a55b337ffaa1ad7a1e2e727329b2c9951"></a>
diff --git a/docs/reference/api/doxygen/postproc_8h_source.html b/docs/reference/api/doxygen/postproc_8h_source.html
index 35b61e17f..bb57dfee4 100644
--- a/docs/reference/api/doxygen/postproc_8h_source.html
+++ b/docs/reference/api/doxygen/postproc_8h_source.html
@@ -66,7 +66,7 @@ $(function() {
<div class="title">postproc.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="postproc_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 [...]
+<a href="postproc_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_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_1meta__schedule_1_1Postproc_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1Postproc.html">tvm::meta_schedule::Postproc</a></div><div class="ttdoc">Managed reference to PostprocNode. </div><div class="ttdef"><b>Definition:</b> postproc.h:105</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyPostprocNode_html_a745d8654ab1a9cde5d24d4a9c40a68f2"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyPostprocNode.html#a745d8654ab1a9cde5d24d4a9c40a68f2">tvm::meta_schedule::PyPostprocNode::f_initialize_with_tune_context</a></div><div class="ttdeci">FInitializeWithTuneContext f_initialize_with_tune_context</div><div class="ttdoc">The packed function to the InitializeWithTuneContext function. </div><div class="ttdef"><b>Def [...]
diff --git a/docs/reference/api/doxygen/relay_2transform_8h.html b/docs/reference/api/doxygen/relay_2transform_8h.html
index 0e1692616..7dae653ed 100644
--- a/docs/reference/api/doxygen/relay_2transform_8h.html
+++ b/docs/reference/api/doxygen/relay_2transform_8h.html
@@ -256,6 +256,9 @@ Functions</h2></td></tr>
<tr class="memitem:af719f05ee653ea465589a38747b35e22"><td class="memItemLeft" align="right" valign="top">Pass </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#af719f05ee653ea465589a38747b35e22">tvm::relay::transform::FlattenAtrousConv</a> ()</td></tr>
<tr class="memdesc:af719f05ee653ea465589a38747b35e22"><td class="mdescLeft"> </td><td class="mdescRight">This transform flattens atrous convolution, which corresponds to the sequence of operations: "space_to_batch_nd"->"conv2d"->"batch_to_space_nd" and convert them into subgraphs with a convolution with the modified "dilation" and recalculated "padding" parameters. <a href="namespacetvm_1_1relay_1_1transform.html#af719f05ee653ea465589a38747b35e22">More...</a><br /></td></tr>
<tr class="separator:af719f05ee653ea465589a38747b35e22"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="memItemLeft" align="right" valign="top">Pass </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1relay_1_1transform.html#a6adb5ecf3c0fbe3c91d37e90795d91de">tvm::relay::transform::AnnotateUsedMemory</a> ()</td></tr>
+<tr class="memdesc:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="mdescLeft"> </td><td class="mdescRight">Annotates the minimum required memory of each primitive function callsite by analyzing the liveness of the input/output tensors at each function callsite and calculating the total amount of memory these tensors require. This is added as a "used_memory" annotation to the function in question as a list of the number of bytes for each callsite. In addition, the containing function i [...]
+<tr class="separator:a6adb5ecf3c0fbe3c91d37e90795d91de"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad7cfa0b6a4537989b886d47767526726"><td class="memItemLeft" align="right" valign="top">Expr </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1relay.html#ad7cfa0b6a4537989b886d47767526726">tvm::relay::Bind</a> (const Expr &expr, const <a class="el" href="classtvm_1_1runtime_1_1Map.html">tvm::Map</a>< Var, Expr > &binds)</td></tr>
<tr class="memdesc:ad7cfa0b6a4537989b886d47767526726"><td class="mdescLeft"> </td><td class="mdescRight">Bind the free variables to a Relay expression. This is a helper function usually called by other pass functions to help optimizations. <a class="el" href="classtvm_1_1relay_1_1If.html">If</a> any free variables are introduced into a function, those are added to the functoin parameters. Additionally this may change the order of parameters if you map a variable to a variable. <a h [...]
<tr class="separator:ad7cfa0b6a4537989b886d47767526726"><td class="memSeparator" colspan="2"> </td></tr>
diff --git a/docs/reference/api/doxygen/relay_2transform_8h_source.html b/docs/reference/api/doxygen/relay_2transform_8h_source.html
index 2f693e75b..49b0a1518 100644
--- a/docs/reference/api/doxygen/relay_2transform_8h_source.html
+++ b/docs/reference/api/doxygen/relay_2transform_8h_source.html
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-<a href="relay_2transform_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 [...]
+<a href="relay_2transform_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="classtvm_1_1CompilationConfig_html"><div class="ttname"><a href="classtvm_1_1CompilationConfig.html">tvm::CompilationConfig</a></div><div class="ttdoc">Managed reference class to CompilationConfig. </div><div class="ttdef"><b>Definition:</b> compilation_config.h:183</div></div>
<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_ad90e4d6ac08b62ef553755e759d398fa"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#ad90e4d6ac08b62ef553755e759d398fa">tvm::relay::transform::ToCPS</a></div><div class="ttdeci">Pass ToCPS()</div><div class="ttdoc">Turn an expression into continuation passing style(CPS). </div></div>
<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_a93bbf7ab3f612d4f38a6832d6b53b4fd"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#a93bbf7ab3f612d4f38a6832d6b53b4fd">tvm::relay::transform::CanonicalizeCast</a></div><div class="ttdeci">Pass CanonicalizeCast()</div><div class="ttdoc">Canonicalize cast expressions to make operator fusion more efficient. </div></div>
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<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_1_1relay_1_1transform_html_aa97a0ec61929f58aefff5da83a73e1cd"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#aa97a0ec61929f58aefff5da83a73e1cd">tvm::relay::transform::CombineParallelBatchMatmul</a></div><div class="ttdeci">Pass CombineParallelBatchMatmul(uint64_t min_num_branches=3)</div><div class="ttdoc">Combine parallel batch_matmul ops into a single batch_matmul if the number of branches of this dense ...</div></div>
<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_af719f05ee653ea465589a38747b35e22"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#af719f05ee653ea465589a38747b35e22">tvm::relay::transform::FlattenAtrousConv</a></div><div class="ttdeci">Pass FlattenAtrousConv()</div><div class="ttdoc">This transform flattens atrous convolution, which corresponds to the sequence of operations: "space_t...</div></div>
+<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_a6adb5ecf3c0fbe3c91d37e90795d91de"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#a6adb5ecf3c0fbe3c91d37e90795d91de">tvm::relay::transform::AnnotateUsedMemory</a></div><div class="ttdeci">Pass AnnotateUsedMemory()</div><div class="ttdoc">Annotates the minimum required memory of each primitive function callsite by analyzing the liveness o...</div></div>
<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_adcddf150ca7da40e20408928421b0086"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#adcddf150ca7da40e20408928421b0086">tvm::relay::transform::CanonicalizeOps</a></div><div class="ttdeci">Pass CanonicalizeOps()</div><div class="ttdoc">Canonicalize some operators to the simplified operators. For example, bias_add can be canonicalized t...</div></div>
<div class="ttc" id="namespacetvm_1_1topi_html_aaa95d3ad68932ab206efbe0a326db6a2"><div class="ttname"><a href="namespacetvm_1_1topi.html#aaa95d3ad68932ab206efbe0a326db6a2">tvm::topi::mod</a></div><div class="ttdeci">tvm::PrimExpr mod(const tvm::PrimExpr &a, const tvm::PrimExpr &b)</div><div class="ttdef"><b>Definition:</b> broadcast.h:290</div></div>
<div class="ttc" id="namespacetvm_1_1relay_1_1transform_html_afbbf5f3e5ffb775fafb9c48473dbfa24"><div class="ttname"><a href="namespacetvm_1_1relay_1_1transform.html#afbbf5f3e5ffb775fafb9c48473dbfa24">tvm::relay::transform::RemoveUnusedFunctions</a></div><div class="ttdeci">Pass RemoveUnusedFunctions(Array< runtime::String > entry_functions)</div><div class="ttdoc">Remove the unused functions in the Relay IRModule. </div></div>
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diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index 653f92ed9..a98078337 100644
--- a/docs/reference/api/python/auto_scheduler.html
+++ b/docs/reference/api/python/auto_scheduler.html
@@ -380,59 +380,59 @@
<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.XGBModel" title="tvm.auto_scheduler.XGBModel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">XGBModel</span></code></a>([verbose_eval, num_warmup_sample, ...])</p></td>
<td><p>Train a XGBoost model to predict the normalized throughputs of programs.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext" title="tvm.auto_scheduler.DispatchContext"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DispatchContext</span></code></a>()</p></td>
-<td><p>Base class of dispatch context.</p></td>
-</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.ApplyHistoryBest" title="tvm.auto_scheduler.ApplyHistoryBest"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ApplyHistoryBest</span></code></a>(records[, n_lines, ...])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.ApplyHistoryBest" title="tvm.auto_scheduler.ApplyHistoryBest"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ApplyHistoryBest</span></code></a>(records[, n_lines, ...])</p></td>
<td><p>Apply the history best config</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.ApplyHistoryBestOrSample" title="tvm.auto_scheduler.ApplyHistoryBestOrSample"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ApplyHistoryBestOrSample</span></code></a>(records[, ...])</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.ApplyHistoryBestOrSample" title="tvm.auto_scheduler.ApplyHistoryBestOrSample"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ApplyHistoryBestOrSample</span></code></a>(records[, ...])</p></td>
<td><p>Apply the history best config, or sample a valid schedule if no config is found.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureInput" title="tvm.auto_scheduler.MeasureInput"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MeasureInput</span></code></a>(task, state)</p></td>
-<td><p>Store the input of a measurement.</p></td>
-</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureResult" title="tvm.auto_scheduler.MeasureResult"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MeasureResult</span></code></a>(costs, error_no, error_msg, ...)</p></td>
-<td><p>Store the results of a measurement.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext" title="tvm.auto_scheduler.DispatchContext"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DispatchContext</span></code></a>()</p></td>
+<td><p>Base class of dispatch context.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.LocalBuilder" title="tvm.auto_scheduler.LocalBuilder"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LocalBuilder</span></code></a>([timeout, n_parallel, build_func])</p></td>
<td><p>LocalBuilder use local CPU cores to build programs in parallel.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.LocalRunner" title="tvm.auto_scheduler.LocalRunner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LocalRunner</span></code></a>([timeout, number, repeat, ...])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.LocalRPCMeasureContext" title="tvm.auto_scheduler.LocalRPCMeasureContext"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LocalRPCMeasureContext</span></code></a>([priority, ...])</p></td>
+<td><p>A context wrapper for running RPCRunner locally.</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.LocalRunner" title="tvm.auto_scheduler.LocalRunner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LocalRunner</span></code></a>([timeout, number, repeat, ...])</p></td>
<td><p>LocalRunner that uses local CPU/GPU to measures the time cost of programs.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RPCRunner</span></code></a>(key, host, port[, priority, ...])</p></td>
-<td><p>RPCRunner that uses RPC call to measures the time cost of programs on remote devices.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureInput" title="tvm.auto_scheduler.MeasureInput"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MeasureInput</span></code></a>(task, state)</p></td>
+<td><p>Store the input of a measurement.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.LocalRPCMeasureContext" title="tvm.auto_scheduler.LocalRPCMeasureContext"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LocalRPCMeasureContext</span></code></a>([priority, ...])</p></td>
-<td><p>A context wrapper for running RPCRunner locally.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureResult" title="tvm.auto_scheduler.MeasureResult"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MeasureResult</span></code></a>(costs, error_no, error_msg, ...)</p></td>
+<td><p>Store the results of a measurement.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RecordToFile" title="tvm.auto_scheduler.RecordToFile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordToFile</span></code></a>(filename)</p></td>
-<td><p>A measurement callback that writes measurement records into a file.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RPCRunner</span></code></a>(key, host, port[, priority, ...])</p></td>
+<td><p>RPCRunner that uses RPC call to measures the time cost of programs on remote devices.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RecordReader" title="tvm.auto_scheduler.RecordReader"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordReader</span></code></a>(filename)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RecordReader" title="tvm.auto_scheduler.RecordReader"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordReader</span></code></a>(filename)</p></td>
<td><p>Reader of the json log file.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SearchTask</span></code></a>([func, args, compute_dag, ...])</p></td>
-<td><p>The computation information and hardware parameters for a schedule search task.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.RecordToFile" title="tvm.auto_scheduler.RecordToFile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordToFile</span></code></a>(filename)</p></td>
+<td><p>A measurement callback that writes measurement records into a file.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TuningOptions</span></code></a>([num_measure_trials, ...])</p></td>
-<td><p>This controls the options of performance tuning.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.EmptyPolicy" title="tvm.auto_scheduler.EmptyPolicy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">EmptyPolicy</span></code></a>(task[, init_search_callbacks])</p></td>
+<td><p>A simple example of the search policy which always returns the initial naive schedule (state).</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.HardwareParams" title="tvm.auto_scheduler.HardwareParams"><code class="xref py py-obj docutils literal notranslate"><span class="pre">HardwareParams</span></code></a>([num_cores, ...])</p></td>
-<td><p>The parameters of target hardware used to guide the search policy.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.PreloadCustomSketchRule" title="tvm.auto_scheduler.PreloadCustomSketchRule"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PreloadCustomSketchRule</span></code></a>(meet_condition_func, ...)</p></td>
+<td><p>A SearchCallback for SketchSearchPolicy that allows users to add custom sketch rule.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.EmptyPolicy" title="tvm.auto_scheduler.EmptyPolicy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">EmptyPolicy</span></code></a>(task[, init_search_callbacks])</p></td>
-<td><p>A simple example of the search policy which always returns the initial naive schedule (state).</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.PreloadMeasuredStates" title="tvm.auto_scheduler.PreloadMeasuredStates"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PreloadMeasuredStates</span></code></a>(filename)</p></td>
+<td><p>A SearchCallback to load measured states from the log file for a search policy.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy" title="tvm.auto_scheduler.SketchPolicy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SketchPolicy</span></code></a>(task[, program_cost_model, ...])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy" title="tvm.auto_scheduler.SketchPolicy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SketchPolicy</span></code></a>(task[, program_cost_model, ...])</p></td>
<td><p>The search policy that searches in a hierarchical search space defined by sketches.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.PreloadMeasuredStates" title="tvm.auto_scheduler.PreloadMeasuredStates"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PreloadMeasuredStates</span></code></a>(filename)</p></td>
-<td><p>A SearchCallback to load measured states from the log file for a search policy.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.HardwareParams" title="tvm.auto_scheduler.HardwareParams"><code class="xref py py-obj docutils literal notranslate"><span class="pre">HardwareParams</span></code></a>([num_cores, ...])</p></td>
+<td><p>The parameters of target hardware used to guide the search policy.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.PreloadCustomSketchRule" title="tvm.auto_scheduler.PreloadCustomSketchRule"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PreloadCustomSketchRule</span></code></a>(meet_condition_func, ...)</p></td>
-<td><p>A SearchCallback for SketchSearchPolicy that allows users to add custom sketch rule.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SearchTask</span></code></a>([func, args, compute_dag, ...])</p></td>
+<td><p>The computation information and hardware parameters for a schedule search task.</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TuningOptions</span></code></a>([num_measure_trials, ...])</p></td>
+<td><p>This controls the options of performance tuning.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.TaskScheduler" title="tvm.auto_scheduler.TaskScheduler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TaskScheduler</span></code></a>(tasks[, task_weights, ...])</p></td>
<td><p>Allocate the time resources when tuning multiple tasks together.</p></td>
@@ -464,27 +464,30 @@
<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.extract_tasks" title="tvm.auto_scheduler.extract_tasks"><code class="xref py py-obj docutils literal notranslate"><span class="pre">extract_tasks</span></code></a>(mod, params, target[, ...])</p></td>
<td><p>Extract tuning tasks from a relay program.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.remove_index_check" title="tvm.auto_scheduler.remove_index_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">remove_index_check</span></code></a>(tensor)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.is_auto_scheduler_enabled" title="tvm.auto_scheduler.is_auto_scheduler_enabled"><code class="xref py py-obj docutils literal notranslate"><span class="pre">is_auto_scheduler_enabled</span></code></a>()</p></td>
+<td><p>Return whether the auto-scheduler is enabled.</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.remove_index_check" title="tvm.auto_scheduler.remove_index_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">remove_index_check</span></code></a>(tensor)</p></td>
<td><p>Remove the safety check in the indexing function for a tensor.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.rewrite_compute_body" title="tvm.auto_scheduler.rewrite_compute_body"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rewrite_compute_body</span></code></a>(compute_tensor, new_layout)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.rewrite_compute_body" title="tvm.auto_scheduler.rewrite_compute_body"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rewrite_compute_body</span></code></a>(compute_tensor, new_layout)</p></td>
<td><p>Rewrite the body of a ComputeOp according to a new layout of a placeholder</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.is_auto_scheduler_enabled" title="tvm.auto_scheduler.is_auto_scheduler_enabled"><code class="xref py py-obj docutils literal notranslate"><span class="pre">is_auto_scheduler_enabled</span></code></a>()</p></td>
-<td><p>Return whether the auto-scheduler is enabled.</p></td>
-</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.create_task" title="tvm.auto_scheduler.create_task"><code class="xref py py-obj docutils literal notranslate"><span class="pre">create_task</span></code></a>(func, args, target[, ...])</p></td>
-<td><p>THIS API IS DEPRECATED.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.rewrite_tensor_shape" title="tvm.auto_scheduler.rewrite_tensor_shape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rewrite_tensor_shape</span></code></a>(tensor, shape)</p></td>
+<td><p>Rewrite the tensor shape</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.auto_schedule" title="tvm.auto_scheduler.auto_schedule"><code class="xref py py-obj docutils literal notranslate"><span class="pre">auto_schedule</span></code></a>(task[, search_policy, ...])</p></td>
<td><p>THIS API IS DEPRECATED.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.register_workload" title="tvm.auto_scheduler.register_workload"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_workload</span></code></a>(func_name[, f, override])</p></td>
-<td><p>Register a function that generates a certain workload.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.create_task" title="tvm.auto_scheduler.create_task"><code class="xref py py-obj docutils literal notranslate"><span class="pre">create_task</span></code></a>(func, args, target[, ...])</p></td>
+<td><p>THIS API IS DEPRECATED.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.make_workload_key" title="tvm.auto_scheduler.make_workload_key"><code class="xref py py-obj docutils literal notranslate"><span class="pre">make_workload_key</span></code></a>(func, args)</p></td>
<td><p>Make a workload key by function and arguments.</p></td>
</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.register_workload" title="tvm.auto_scheduler.register_workload"><code class="xref py py-obj docutils literal notranslate"><span class="pre">register_workload</span></code></a>(func_name[, f, override])</p></td>
+<td><p>Register a function that generates a certain workload.</p></td>
+</tr>
</tbody>
</table>
<dl class="py class">
@@ -915,67 +918,6 @@ This function can be used to pre-train the cost model with history log files.
</dd></dl>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext">
-<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">DispatchContext</span></span><a class="headerlink" href="#tvm.auto_scheduler.DispatchContext" title="Permalink to this definition">¶</a></dt>
-<dd><p>Base class of dispatch context.</p>
-<p><strong>Methods:</strong></p>
-<table class="longtable docutils align-default">
-<colgroup>
-<col style="width: 10%" />
-<col style="width: 90%" />
-</colgroup>
-<tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext.query" title="tvm.auto_scheduler.DispatchContext.query"><code class="xref py py-obj docutils literal notranslate"><span class="pre">query</span></code></a>(target, workload_key, has_complex_op, ...)</p></td>
-<td><p>Query the context to get the specific config for a workload.</p></td>
-</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext.update" title="tvm.auto_scheduler.DispatchContext.update"><code class="xref py py-obj docutils literal notranslate"><span class="pre">update</span></code></a>(target, workload_key, state)</p></td>
-<td><p>Update the config for a workload</p></td>
-</tr>
-</tbody>
-</table>
-<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext.query">
-<span class="sig-name descname"><span class="pre">query</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workload_key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">has_complex_op</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dag</span></span></em>, <em class="sig-param"><span class="n"><span clas [...]
-<dd><p>Query the context to get the specific config for a workload.
-If this function cannot find the result inside this context, it will query the result
-from the upper contexts.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>target</strong> (<a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>Target</em></a>) – The current target</p></li>
-<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The workload key</p></li>
-<li><p><strong>has_complex_op</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – Whether this workload has at least one complex op.</p></li>
-<li><p><strong>dag</strong> (<a class="reference internal" href="#tvm.auto_scheduler.ComputeDAG" title="tvm.auto_scheduler.ComputeDAG"><em>ComputeDAG</em></a>) – The ComputeDAG of the workload.</p></li>
-<li><p><strong>func_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The function name of this workload.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>state</strong> – The state that stores schedule configuration for the workload</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>StateObject</p>
-</dd>
-</dl>
-</dd></dl>
-
-<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext.update">
-<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workload_key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.DispatchContext.update" title="Permalink to this definitio [...]
-<dd><p>Update the config for a workload</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>target</strong> (<a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>Target</em></a>) – The current target</p></li>
-<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The current workload_key.</p></li>
-<li><p><strong>state</strong> (<em>StateObject</em>) – The state that stores schedule configuration for the workload</p></li>
-</ul>
-</dd>
-</dl>
-</dd></dl>
-
-</dd></dl>
-
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.ApplyHistoryBest">
<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">ApplyHistoryBest</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">records</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_lines</span></span><span class="o"><span class="pre">=</span></span><span class="default_v [...]
@@ -1125,17 +1067,9 @@ from the upper contexts.</p>
</dd></dl>
<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureInput">
-<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">MeasureInput</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">state</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_sched [...]
-<dd><p>Store the input of a measurement.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask of this measurement.</p></li>
-<li><p><strong>state</strong> (<em>Union</em><em>[</em><em>State</em><em>, </em><em>StateObject</em><em>]</em>) – The State to be measured.</p></li>
-</ul>
-</dd>
-</dl>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext">
+<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">DispatchContext</span></span><a class="headerlink" href="#tvm.auto_scheduler.DispatchContext" title="Permalink to this definition">¶</a></dt>
+<dd><p>Base class of dispatch context.</p>
<p><strong>Methods:</strong></p>
<table class="longtable docutils align-default">
<colgroup>
@@ -1143,40 +1077,56 @@ from the upper contexts.</p>
<col style="width: 90%" />
</colgroup>
<tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureInput.serialize" title="tvm.auto_scheduler.MeasureInput.serialize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">serialize</span></code></a>()</p></td>
-<td><p>Custom serialization to workaround MeasureInput not exposing all its members to the TVM ffi interface.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext.query" title="tvm.auto_scheduler.DispatchContext.query"><code class="xref py py-obj docutils literal notranslate"><span class="pre">query</span></code></a>(target, workload_key, has_complex_op, ...)</p></td>
+<td><p>Query the context to get the specific config for a workload.</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.DispatchContext.update" title="tvm.auto_scheduler.DispatchContext.update"><code class="xref py py-obj docutils literal notranslate"><span class="pre">update</span></code></a>(target, workload_key, state)</p></td>
+<td><p>Update the config for a workload</p></td>
</tr>
</tbody>
</table>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureInput.serialize">
-<span class="sig-name descname"><span class="pre">serialize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.MeasureInput.serialize" title="Permalink to this definition">¶</a></dt>
-<dd><p>Custom serialization to workaround MeasureInput not exposing all its
-members to the TVM ffi interface.</p>
-<p>Note that we do not implement __getstate__ as it does not seem to work
-with initialization of the workload registry (maybe because of
-initialization order?).</p>
-</dd></dl>
-
+<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext.query">
+<span class="sig-name descname"><span class="pre">query</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workload_key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">has_complex_op</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dag</span></span></em>, <em class="sig-param"><span class="n"><span clas [...]
+<dd><p>Query the context to get the specific config for a workload.
+If this function cannot find the result inside this context, it will query the result
+from the upper contexts.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>target</strong> (<a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>Target</em></a>) – The current target</p></li>
+<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The workload key</p></li>
+<li><p><strong>has_complex_op</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – Whether this workload has at least one complex op.</p></li>
+<li><p><strong>dag</strong> (<a class="reference internal" href="#tvm.auto_scheduler.ComputeDAG" title="tvm.auto_scheduler.ComputeDAG"><em>ComputeDAG</em></a>) – The ComputeDAG of the workload.</p></li>
+<li><p><strong>func_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The function name of this workload.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p><strong>state</strong> – The state that stores schedule configuration for the workload</p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p>StateObject</p>
+</dd>
+</dl>
</dd></dl>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureResult">
-<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">MeasureResult</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">costs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_no</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_msg</s [...]
-<dd><p>Store the results of a measurement.</p>
+<dl class="py method">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.DispatchContext.update">
+<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workload_key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">state</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.DispatchContext.update" title="Permalink to this definitio [...]
+<dd><p>Update the config for a workload</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>costs</strong> (<em>List</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a><em>]</em>) – The time costs of execution.</p></li>
-<li><p><strong>error_no</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The error code.</p></li>
-<li><p><strong>error_msg</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The error message if there is any error.</p></li>
-<li><p><strong>all_cost</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a>) – The time cost of build and run.</p></li>
-<li><p><strong>timestamp</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a>) – The time stamps of this measurement.</p></li>
+<li><p><strong>target</strong> (<a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>Target</em></a>) – The current target</p></li>
+<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The current workload_key.</p></li>
+<li><p><strong>state</strong> (<em>StateObject</em>) – The state that stores schedule configuration for the workload</p></li>
</ul>
</dd>
</dl>
</dd></dl>
+</dd></dl>
+
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.LocalBuilder">
<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">LocalBuilder</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">15</span></span></em>, <em class="sig-param"><span class="n"><sp [...]
@@ -1196,51 +1146,13 @@ If is callable, use it as custom build function, expect lib_format field.</p></l
</dd></dl>
<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.LocalRunner">
-<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">LocalRunner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><spa [...]
-<dd><p>LocalRunner that uses local CPU/GPU to measures the time cost of programs.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>timeout</strong> (<em>int = 10</em>) – The timeout limit (in second) for each run.
-This is used in a wrapper of the multiprocessing.Process.join().</p></li>
-<li><p><strong>number</strong> (<em>int = 3</em>) – The number of times to run the generated code for taking average.
-We call these runs as one <cite>repeat</cite> of measurement.</p></li>
-<li><p><strong>repeat</strong> (<em>int = 1</em>) – The number of times to repeat the measurement.
-In total, the generated code will be run (1 + number x repeat) times,
-where the first “1” is warm up and will be discarded.
-The returned result contains <cite>repeat</cite> costs,
-each of which is an average of <cite>number</cite> costs.</p></li>
-<li><p><strong>min_repeat_ms</strong> (<em>int = 100</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
-By default, one <cite>repeat</cite> contains <cite>number</cite> runs. If this parameter is set,
-the parameters <cite>number</cite> will be dynamically adjusted to meet the
-minimum duration requirement of one <cite>repeat</cite>.
-i.e., When the run time of one <cite>repeat</cite> falls below this time, the <cite>number</cite> parameter
-will be automatically increased.</p></li>
-<li><p><strong>cooldown_interval</strong> (<em>float = 0.0</em>) – The cool down interval between two measurements in seconds.</p></li>
-<li><p><strong>enable_cpu_cache_flush</strong> (<em>bool = False</em>) – Whether to flush cache on CPU between repeated measurements.
-Flushing cache can make the measured latency of one operator closer to
-its actual latency during end-to-end inference.
-To make this option effective, the argument <cite>number</cite> should also be set to 1.
-This is only has effect on CPU task.</p></li>
-<li><p><strong>device</strong> (<em>int = 0</em>) – Which device to run on if multiple are available.</p></li>
-</ul>
-</dd>
-</dl>
-</dd></dl>
-
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.RPCRunner">
-<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">RPCRunner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">host</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">port</span></span></em [...]
-<dd><p>RPCRunner that uses RPC call to measures the time cost of programs on remote devices.
-Or sometime we may need to use RPC even in local running to insulate the thread environment.
-(e.g. running CUDA programs)</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.LocalRPCMeasureContext">
+<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">LocalRPCMeasureContext</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">priority</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span cla [...]
+<dd><p>A context wrapper for running RPCRunner locally.
+This will launch a local RPC Tracker and local RPC Server.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The key of the device registered in the RPC tracker.</p></li>
-<li><p><strong>host</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The host address of the RPC Tracker.</p></li>
-<li><p><strong>port</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The port of RPC Tracker.</p></li>
<li><p><strong>priority</strong> (<em>int = 1</em>) – The priority of this run request, larger is more prior.</p></li>
<li><p><strong>n_parallel</strong> (<em>int = 1</em>) – The number of tasks run in parallel.</p></li>
<li><p><strong>timeout</strong> (<em>int = 10</em>) – The timeout limit (in second) for each run.
@@ -1252,7 +1164,7 @@ In total, the generated code will be run (1 + number x repeat) times,
where the first “1” is warm up and will be discarded.
The returned result contains <cite>repeat</cite> costs,
each of which is an average of <cite>number</cite> costs.</p></li>
-<li><p><strong>min_repeat_ms</strong> (<em>int = 100</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
+<li><p><strong>min_repeat_ms</strong> (<em>int = 0</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
By default, one <cite>repeat</cite> contains <cite>number</cite> runs. If this parameter is set,
the parameters <cite>number</cite> will be dynamically adjusted to meet the
minimum duration requirement of one <cite>repeat</cite>.
@@ -1271,15 +1183,12 @@ This is only has effect on CPU task.</p></li>
</dd></dl>
<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.LocalRPCMeasureContext">
-<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">LocalRPCMeasureContext</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">priority</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span cla [...]
-<dd><p>A context wrapper for running RPCRunner locally.
-This will launch a local RPC Tracker and local RPC Server.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.LocalRunner">
+<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">LocalRunner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">timeout</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><spa [...]
+<dd><p>LocalRunner that uses local CPU/GPU to measures the time cost of programs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>priority</strong> (<em>int = 1</em>) – The priority of this run request, larger is more prior.</p></li>
-<li><p><strong>n_parallel</strong> (<em>int = 1</em>) – The number of tasks run in parallel.</p></li>
<li><p><strong>timeout</strong> (<em>int = 10</em>) – The timeout limit (in second) for each run.
This is used in a wrapper of the multiprocessing.Process.join().</p></li>
<li><p><strong>number</strong> (<em>int = 3</em>) – The number of times to run the generated code for taking average.
@@ -1289,7 +1198,7 @@ In total, the generated code will be run (1 + number x repeat) times,
where the first “1” is warm up and will be discarded.
The returned result contains <cite>repeat</cite> costs,
each of which is an average of <cite>number</cite> costs.</p></li>
-<li><p><strong>min_repeat_ms</strong> (<em>int = 0</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
+<li><p><strong>min_repeat_ms</strong> (<em>int = 100</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
By default, one <cite>repeat</cite> contains <cite>number</cite> runs. If this parameter is set,
the parameters <cite>number</cite> will be dynamically adjusted to meet the
minimum duration requirement of one <cite>repeat</cite>.
@@ -1307,23 +1216,117 @@ This is only has effect on CPU task.</p></li>
</dl>
</dd></dl>
-<dl class="py function">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.register_task_input_check_func">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">register_task_input_check_func</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em> [...]
-<dd><p>Register a function that checks the input buffer map.</p>
-<p>The input function should take a list of Tensor wich indicate the Input/output Tensor of a TVM
-subgraph and return a Map from the input Tensor to its buffer name.</p>
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureInput">
+<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">MeasureInput</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">state</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_sched [...]
+<dd><p>Store the input of a measurement.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>func_name</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The check function that returns the compute declaration Tensors or its function name.</p></li>
-<li><p><strong>f</strong> (<em>Optional</em><em>[</em><em>Function</em><em>]</em>) – The check function to be registered.</p></li>
-<li><p><strong>override</strong> (<em>boolean = False</em>) – Whether to override existing entry.</p></li>
+<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask of this measurement.</p></li>
+<li><p><strong>state</strong> (<em>Union</em><em>[</em><em>State</em><em>, </em><em>StateObject</em><em>]</em>) – The State to be measured.</p></li>
</ul>
</dd>
</dl>
-<p class="rubric">Examples</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@auto_scheduler</span><span class="o">.</span><span class="n">register_task_input_check_func</span>
+<p><strong>Methods:</strong></p>
+<table class="longtable docutils align-default">
+<colgroup>
+<col style="width: 10%" />
+<col style="width: 90%" />
+</colgroup>
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.MeasureInput.serialize" title="tvm.auto_scheduler.MeasureInput.serialize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">serialize</span></code></a>()</p></td>
+<td><p>Custom serialization to workaround MeasureInput not exposing all its members to the TVM ffi interface.</p></td>
+</tr>
+</tbody>
+</table>
+<dl class="py method">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureInput.serialize">
+<span class="sig-name descname"><span class="pre">serialize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.MeasureInput.serialize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Custom serialization to workaround MeasureInput not exposing all its
+members to the TVM ffi interface.</p>
+<p>Note that we do not implement __getstate__ as it does not seem to work
+with initialization of the workload registry (maybe because of
+initialization order?).</p>
+</dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.MeasureResult">
+<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">MeasureResult</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">costs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_no</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">error_msg</s [...]
+<dd><p>Store the results of a measurement.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>costs</strong> (<em>List</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a><em>]</em>) – The time costs of execution.</p></li>
+<li><p><strong>error_no</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The error code.</p></li>
+<li><p><strong>error_msg</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The error message if there is any error.</p></li>
+<li><p><strong>all_cost</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a>) – The time cost of build and run.</p></li>
+<li><p><strong>timestamp</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><em>float</em></a>) – The time stamps of this measurement.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.RPCRunner">
+<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">RPCRunner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">host</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">port</span></span></em [...]
+<dd><p>RPCRunner that uses RPC call to measures the time cost of programs on remote devices.
+Or sometime we may need to use RPC even in local running to insulate the thread environment.
+(e.g. running CUDA programs)</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The key of the device registered in the RPC tracker.</p></li>
+<li><p><strong>host</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The host address of the RPC Tracker.</p></li>
+<li><p><strong>port</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The port of RPC Tracker.</p></li>
+<li><p><strong>priority</strong> (<em>int = 1</em>) – The priority of this run request, larger is more prior.</p></li>
+<li><p><strong>n_parallel</strong> (<em>int = 1</em>) – The number of tasks run in parallel.</p></li>
+<li><p><strong>timeout</strong> (<em>int = 10</em>) – The timeout limit (in second) for each run.
+This is used in a wrapper of the multiprocessing.Process.join().</p></li>
+<li><p><strong>number</strong> (<em>int = 3</em>) – The number of times to run the generated code for taking average.
+We call these runs as one <cite>repeat</cite> of measurement.</p></li>
+<li><p><strong>repeat</strong> (<em>int = 1</em>) – The number of times to repeat the measurement.
+In total, the generated code will be run (1 + number x repeat) times,
+where the first “1” is warm up and will be discarded.
+The returned result contains <cite>repeat</cite> costs,
+each of which is an average of <cite>number</cite> costs.</p></li>
+<li><p><strong>min_repeat_ms</strong> (<em>int = 100</em>) – The minimum duration of one <cite>repeat</cite> in milliseconds.
+By default, one <cite>repeat</cite> contains <cite>number</cite> runs. If this parameter is set,
+the parameters <cite>number</cite> will be dynamically adjusted to meet the
+minimum duration requirement of one <cite>repeat</cite>.
+i.e., When the run time of one <cite>repeat</cite> falls below this time, the <cite>number</cite> parameter
+will be automatically increased.</p></li>
+<li><p><strong>cooldown_interval</strong> (<em>float = 0.0</em>) – The cool down interval between two measurements in seconds.</p></li>
+<li><p><strong>enable_cpu_cache_flush</strong> (<em>bool = False</em>) – Whether to flush cache on CPU between repeated measurements.
+Flushing cache can make the measured latency of one operator closer to
+its actual latency during end-to-end inference.
+To make this option effective, the argument <cite>number</cite> should also be set to 1.
+This is only has effect on CPU task.</p></li>
+<li><p><strong>device</strong> (<em>int = 0</em>) – Which device to run on if multiple are available.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.register_task_input_check_func">
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">register_task_input_check_func</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em> [...]
+<dd><p>Register a function that checks the input buffer map.</p>
+<p>The input function should take a list of Tensor wich indicate the Input/output Tensor of a TVM
+subgraph and return a Map from the input Tensor to its buffer name.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>func_name</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The check function that returns the compute declaration Tensors or its function name.</p></li>
+<li><p><strong>f</strong> (<em>Optional</em><em>[</em><em>Function</em><em>]</em>) – The check function to be registered.</p></li>
+<li><p><strong>override</strong> (<em>boolean = False</em>) – Whether to override existing entry.</p></li>
+</ul>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@auto_scheduler</span><span class="o">.</span><span class="n">register_task_input_check_func</span>
<span class="k">def</span> <span class="nf">check_task_input_by_placeholder_name</span><span class="p">(</span><span class="n">args</span> <span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]):</span>
<span class="n">tensor_input_map</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">arg</span> <span class="ow">in</span> <span class="n">args</span><span class="p">:</span>
@@ -1335,17 +1338,6 @@ subgraph and return a Map from the input Tensor to its buffer name.</p>
</div>
</dd></dl>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.RecordToFile">
-<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">RecordToFile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.RecordToFile" title="Permalink to this definition">¶</a></dt>
-<dd><p>A measurement callback that writes measurement records into a file.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – File name for this callback to write log to.</p>
-</dd>
-</dl>
-</dd></dl>
-
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.RecordReader">
<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">RecordReader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.RecordReader" title="Permalink to this definition">¶</a></dt>
@@ -1411,6 +1403,17 @@ to rebuild these fields.</p>
</dd></dl>
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.RecordToFile">
+<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">RecordToFile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.RecordToFile" title="Permalink to this definition">¶</a></dt>
+<dd><p>A measurement callback that writes measurement records into a file.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – File name for this callback to write log to.</p>
+</dd>
+</dl>
+</dd></dl>
+
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.load_best_record">
<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">load_best_record</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workload_key</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <e [...]
@@ -1501,6 +1504,17 @@ to rebuild these fields.</p>
</dl>
</dd></dl>
+<dl class="py function">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.is_auto_scheduler_enabled">
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">is_auto_scheduler_enabled</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.is_auto_scheduler_enabled" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return whether the auto-scheduler is enabled.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><p><strong>enabled</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – Whether the auto-scheduler is enabled</p>
+</dd>
+</dl>
+</dd></dl>
+
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.remove_index_check">
<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">remove_index_check</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tensor</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.remove_index_check" title="Permalink to this definition">¶</a></dt>
@@ -1522,61 +1536,94 @@ temporary wrong IR and fix it later in other places.</p>
</dd></dl>
<dl class="py function">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.is_auto_scheduler_enabled">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">is_auto_scheduler_enabled</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.is_auto_scheduler_enabled" title="Permalink to this definition">¶</a></dt>
-<dd><p>Return whether the auto-scheduler is enabled.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.rewrite_tensor_shape">
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">rewrite_tensor_shape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.rewrite_tensor_shape" title="Permalink to [...]
+<dd><p>Rewrite the tensor shape</p>
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.EmptyPolicy">
+<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">EmptyPolicy</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">init_search_callbacks</span></span><span class="o"><span class="pre">=</span></span><span class="def [...]
+<dd><p>A simple example of the search policy which always returns
+the initial naive schedule (state).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>enabled</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – Whether the auto-scheduler is enabled</p>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
+<li><p><strong>init_search_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>SearchCallback</em><em>]</em><em>]</em>) – Callback functions called before the search process.</p></li>
+</ul>
</dd>
</dl>
</dd></dl>
<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask">
-<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">SearchTask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span [...]
-<dd><p>The computation information and hardware parameters for a schedule search task.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.PreloadCustomSketchRule">
+<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">PreloadCustomSketchRule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">meet_condition_func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">apply_func</span></span></em>, <em class="sig-param"><span class="n"><spa [...]
+<dd><p>A SearchCallback for SketchSearchPolicy that allows users to add
+custom sketch rule.</p>
+<p class="rubric">Notes</p>
+<p>This is an advanced feature. Make sure you’re clear how it works and this should only be used
+in SketchSearchPolicy.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>func</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The function that returns the compute declaration Tensors.
-Can be the a function or the function name.</p></li>
-<li><p><strong>args</strong> (<em>Union</em><em>[</em><em>Tuple</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>, </em><em>...</em><em>]</em><em>, </em><em>List</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>]</em><em>]</em>) – The args of the function.</p></li>
-<li><p><strong>compute_dag</strong> (<a class="reference internal" href="#tvm.auto_scheduler.ComputeDAG" title="tvm.auto_scheduler.ComputeDAG"><em>ComputeDAG</em></a>) – The ComputeDAG for the corresponding compute declaration.</p></li>
-<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The workload key for the corresponding compute declaration.</p></li>
-<li><p><strong>target</strong> (<em>any target-like object</em><em>, </em><em>see Target.canon_target</em>) – The target device of this search task.</p></li>
-<li><p><strong>target_host</strong> (<a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.10)"><em>None</em></a><em> or </em><em>any target-like object</em><em>, </em><em>see Target.canon_target</em>) – The target host device of this search task.</p></li>
-<li><p><strong>hardware_params</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.HardwareParams" title="tvm.auto_scheduler.HardwareParams"><em>HardwareParams</em></a><em>]</em>) – Hardware parameters used in this search task.</p></li>
-<li><p><strong>layout_rewrite_option</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.LayoutRewriteOption" title="tvm.auto_scheduler.LayoutRewriteOption"><em>LayoutRewriteOption</em></a><em>]</em>) – The layout rewrite option used for measuring programs. If None, the default value will be
-set depending on the specified target.
-Auto_scheduler will find a better schedule for the specified layout rewrite option.
-The NO_REWRITE and INSERT_TRANSFORM_STAGE are expected to be used when tuning a standalone
-op, and the REWRITE_FOR_PRE_TRANSFORMED is expected to be used when tuning ops inside a
-network.</p></li>
-<li><p><strong>task_inputs</strong> (<em>Union</em><em>[</em><em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>, </em><a class="reference internal" href="ndarray.html#tvm.nd.NDArray" title="tvm.nd.NDArray"><em>tvm.nd.NDArray</em></a><em>]</em><em>, </em><em>List</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python [...]
-Some special Tensor used as inputs in program measuring. Usually we do not need to care
-about it, but for special workloads like Sparse computation the Sparse Tensor input are
-meaningful that we cannot use random input directly.</p></li>
-<li><p><strong>task_inputs_overwrite</strong> (<em>bool = False</em>) – Whether to overwrite the data if a name has already in the global table.</p></li>
-<li><p><strong>task_inputs_save_to_file</strong> (<em>bool = False</em>) – Whether to save the data to a local file as well. This can be reused to resume the last
-tuning process.</p></li>
-<li><p><strong>desc</strong> (<em>str = ""</em>) – The description string of this task.</p></li>
+<li><p><strong>meet_condition_func</strong> (<em>Callable</em>) – A function with <cite>(policy, state, stage_id) -> int</cite>. Should return one of the result
+enumeration.</p></li>
+<li><p><strong>apply_func</strong> (<em>Callable</em>) – A function with <cite>(policy, state, stage_id) -> [[State, int], …]</cite>.</p></li>
+<li><p><strong>rule_name</strong> (<em>str = "CustomSketchRule"</em>) – The name of this custom sketch rule.</p></li>
</ul>
</dd>
</dl>
-<p class="rubric">Examples</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># We support two ways to create a search task</span>
+</dd></dl>
-<span class="c1"># Way 1: create a task by a workload generation function.</span>
-<span class="c1"># The `workload_func` is a function decorated by @auto_scheduler.register_workload</span>
-<span class="n">task</span> <span class="o">=</span> <span class="n">SearchTask</span><span class="p">(</span><span class="n">func</span><span class="o">=</span><span class="n">workload_func</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="n">target</span><span class="p">)</span>
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.PreloadMeasuredStates">
+<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">PreloadMeasuredStates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.PreloadMeasuredStates" title="Permalink to this definition">¶</a></dt>
+<dd><p>A SearchCallback to load measured states from the log file for a search policy.</p>
+<dl class="simple">
+<dt>This can resume the state of the search policy:</dt><dd><ul class="simple">
+<li><p>Making sure an already measured state in former searches will never be measured again.</p></li>
+<li><p>The history states can be used to speed up the search process(e.g. SketchPolicy uses
+history states as starting point to perform Evolutionary Search).</p></li>
+</ul>
+</dd>
+</dl>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the record file.</p>
+</dd>
+</dl>
+</dd></dl>
-<span class="c1"># Way 2: create a task by a workload_key.</span>
-<span class="c1"># The `workload_key` is a string, which can be either a hash key or a json-serialized</span>
-<span class="c1"># tuple(func, args).</span>
-<span class="n">task</span> <span class="o">=</span> <span class="n">SearchTask</span><span class="p">(</span><span class="n">workload_key</span><span class="o">=</span><span class="n">workload_key</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="n">target</span><span class="p">)</span>
-</pre></div>
-</div>
+<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 [...]
+<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>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
+<li><p><strong>program_cost_model</strong> (<em>CostModel = RandomModel</em><em>(</em><em>)</em>) – The cost model to estimate the complete schedules.</p></li>
+<li><p><strong>params</strong> (<em>Optional</em><em>[</em><em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>, </em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>]</em><em>]</em>) – Parameters of the search policy.
+See <cite>src/auto_scheduler/search_policy/sketch_search_policy.h</cite> for the definitions.
+See <cite>DEFAULT_PARAMS</cite> below to find the default values.</p></li>
+<li><p><strong>seed</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) – Random seed.</p></li>
+<li><p><strong>verbose</strong> (<em>int = 1</em>) – Verbosity level. 0 for silent, 1 to output information during schedule search.</p></li>
+<li><p><strong>init_search_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>SearchCallback</em><em>]</em><em>]</em>) – <p>Callback functions called before the search process, usually used to do extra
+initializations.
+Possible callbacks:</p>
+<blockquote>
+<div><ul>
+<li><p>auto_scheduler.PreloadMeasuredStates</p></li>
+<li><p>auto_scheduler.PreloadCustomSketchRule</p></li>
+</ul>
+</div></blockquote>
+</p></li>
+</ul>
+</dd>
+</dl>
<p><strong>Methods:</strong></p>
<table class="longtable docutils align-default">
<colgroup>
@@ -1584,102 +1631,76 @@ tuning process.</p></li>
<col style="width: 90%" />
</colgroup>
<tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.tune" title="tvm.auto_scheduler.SearchTask.tune"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tune</span></code></a>(tuning_options[, search_policy])</p></td>
-<td><p>Run auto scheduling search for a task</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.generate_sketches" title="tvm.auto_scheduler.SketchPolicy.generate_sketches"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_sketches</span></code></a>([print_for_debug])</p></td>
+<td><p>Generate the sketches.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.apply_best" title="tvm.auto_scheduler.SearchTask.apply_best"><code class="xref py py-obj docutils literal notranslate"><span class="pre">apply_best</span></code></a>(log_file[, include_compatible, ...])</p></td>
-<td><p>Apply the history best from a log file and return the schedule.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.sample_initial_population" title="tvm.auto_scheduler.SketchPolicy.sample_initial_population"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sample_initial_population</span></code></a>()</p></td>
+<td><p>Sample initial population.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.print_best" title="tvm.auto_scheduler.SearchTask.print_best"><code class="xref py py-obj docutils literal notranslate"><span class="pre">print_best</span></code></a>(log_file[, print_mode])</p></td>
-<td><p>Print the best schedule as python schedule API code or CUDA source code.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.evolutionary_search" title="tvm.auto_scheduler.SketchPolicy.evolutionary_search"><code class="xref py py-obj docutils literal notranslate"><span class="pre">evolutionary_search</span></code></a>(init_populations, out_size)</p></td>
+<td><p>Perform evolutionary search.</p></td>
</tr>
</tbody>
</table>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.tune">
-<span class="sig-name descname"><span class="pre">tune</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tuning_options</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><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SearchTask.tune" tit [...]
-<dd><p>Run auto scheduling search for a task</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.generate_sketches">
+<span class="sig-name descname"><span class="pre">generate_sketches</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">print_for_debug</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.generate_sketches" title="Permalink to this definition">¶</a></dt>
+<dd><p>Generate the sketches.
+This python interface is mainly used for debugging and testing.
+The actual search is all done in c++.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>tuning_options</strong> (<a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><em>TuningOptions</em></a>) – Tuning and measurement options.</p></li>
-<li><p><strong>search_policy</strong> (<em>Optional</em><em>[</em><em>SearchPolicy</em><em>]</em>) – The search policy to be used for schedule search.</p></li>
-</ul>
+<dd class="field-odd"><p><strong>print_for_debug</strong> (<em>bool = False</em>) – Whether print out the sketches for debug.</p>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p><strong>sketches</strong> – The generated sketches of this search task.</p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p>List[State]</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.apply_best">
-<span class="sig-name descname"><span class="pre">apply_best</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log_file</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_compatible</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layout_rewrite_option</span></span>< [...]
-<dd><p>Apply the history best from a log file and return the schedule.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.sample_initial_population">
+<span class="sig-name descname"><span class="pre">sample_initial_population</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.sample_initial_population" title="Permalink to this definition">¶</a></dt>
+<dd><p>Sample initial population.
+This python interface is mainly used for debugging and testing.
+The actual search is all done in c++.</p>
<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>log_file</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the log file.</p></li>
-<li><p><strong>include_compatible</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – When set to True, all compatible records in the log file will be considered.</p></li>
-<li><p><strong>layout_rewrite_option</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.LayoutRewriteOption" title="tvm.auto_scheduler.LayoutRewriteOption"><em>LayoutRewriteOption</em></a><em>]</em>) – The layout rewrite option.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p></p>
+<dt class="field-odd">Returns</dt>
+<dd class="field-odd"><p><strong>states</strong> – The sampled states</p>
</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>A <cite>te.Schedule</cite> and the a list of <cite>te.Tensor</cite> to be used in <cite>tvm.lower</cite> or <cite>tvm.build</cite>.</p>
+<dt class="field-even">Return type</dt>
+<dd class="field-even"><p>List[State]</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.print_best">
-<span class="sig-name descname"><span class="pre">print_best</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log_file</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">print_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'schedule'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SearchTask.print_ [...]
-<dd><p>Print the best schedule as python schedule API code or CUDA source code.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.evolutionary_search">
+<span class="sig-name descname"><span class="pre">evolutionary_search</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_populations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_size</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.evolutionary_search" title="Permalink to this definition">¶</a></dt>
+<dd><p>Perform evolutionary search.
+This python interface is mainly used for debugging and testing.
+The actual search is all done in c++.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>log_file</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the log file</p></li>
-<li><p><strong>print_mode</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – if “schedule”, print the best schedule as python schedule API code.
-if “cuda”, print the best schedule as CUDA source code.</p></li>
+<li><p><strong>init_populations</strong> (<em>List</em><em>[</em><em>State</em><em>]</em>) – The initial population states</p></li>
+<li><p><strong>out_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The size of generated states</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>code</strong> – The best schedule code in python API or CUDA source code</p>
+<dd class="field-even"><p><strong>states</strong> – The generated states</p>
</dd>
<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)">str</a></p>
+<dd class="field-odd"><p>List[State]</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.TuningOptions">
-<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">TuningOptions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_measure_trials</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span cl [...]
-<dd><p>This controls the options of performance tuning.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>num_measure_trials</strong> (<em>int = 0</em>) – The number of measurement trials.
-The search policy measures <cite>num_measure_trials</cite> schedules in total and returns the best one
-among them.
-With <cite>num_measure_trials</cite> == 0, the policy will do the schedule search but won’t involve
-measurement. This can be used to get a runnable schedule quickly without auto-tuning.</p></li>
-<li><p><strong>early_stopping</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) – Stop the tuning early if getting no improvement after n measurements.</p></li>
-<li><p><strong>num_measures_per_round</strong> (<em>int = 64</em>) – The number of schedules to be measured at each search round.
-The whole schedule search process will try a total number of <cite>num_measure_trials</cite> in several
-rounds.</p></li>
-<li><p><strong>verbose</strong> (<em>int = 1</em>) – Verbosity level. 0 for silent, 1 to output information during schedule search.</p></li>
-<li><p><strong>builder</strong> (<em>Union</em><em>[</em><em>ProgramBuilder</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>] </em><em>= 'local'</em>) – ProgramBuilder which builds the program.</p></li>
-<li><p><strong>runner</strong> (<em>Union</em><em>[</em><em>ProgramRunner</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>] </em><em>= 'local'</em>) – ProgramRunner which runs the program and measures time costs.</p></li>
-<li><p><strong>measure_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>MeasureCallback</em><em>]</em><em>]</em>) – Callback functions called after each measurement.
-Candidates:
-- auto_scheduler.RecordToFile</p></li>
-</ul>
-</dd>
-</dl>
-</dd></dl>
-
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.HardwareParams">
<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">HardwareParams</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_cores</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class=" [...]
@@ -1710,97 +1731,51 @@ TODO(jcf94): This is considered to be merged with the new Target specification:
:type target_host: str or Target, optional</p>
</dd></dl>
-<dl class="py function">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.create_task">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">create_task</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class [...]
-<dd><p>THIS API IS DEPRECATED.</p>
-<p>Create a search task.</p>
+<dl class="py class">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask">
+<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">SearchTask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span [...]
+<dd><p>The computation information and hardware parameters for a schedule search task.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>func</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The function that returns the compute declaration Tensors.
Can be the a function or the function name.</p></li>
<li><p><strong>args</strong> (<em>Union</em><em>[</em><em>Tuple</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>, </em><em>...</em><em>]</em><em>, </em><em>List</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>]</em><em>]</em>) – The args of the function.</p></li>
-<li><p><strong>target</strong> (<em>Union</em><em>[</em><a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>tvm.target.Target</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The target device of this search task.</p></li>
-<li><p><strong>target_host</strong> (<em>Optional</em><em>[</em><em>Union</em><em>[</em><a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>tvm.target.Target</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em><em>]</em>) – The target host device of this search task.</p></li>
+<li><p><strong>compute_dag</strong> (<a class="reference internal" href="#tvm.auto_scheduler.ComputeDAG" title="tvm.auto_scheduler.ComputeDAG"><em>ComputeDAG</em></a>) – The ComputeDAG for the corresponding compute declaration.</p></li>
+<li><p><strong>workload_key</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The workload key for the corresponding compute declaration.</p></li>
+<li><p><strong>target</strong> (<em>any target-like object</em><em>, </em><em>see Target.canon_target</em>) – The target device of this search task.</p></li>
+<li><p><strong>target_host</strong> (<a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.10)"><em>None</em></a><em> or </em><em>any target-like object</em><em>, </em><em>see Target.canon_target</em>) – The target host device of this search task.</p></li>
<li><p><strong>hardware_params</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.HardwareParams" title="tvm.auto_scheduler.HardwareParams"><em>HardwareParams</em></a><em>]</em>) – Hardware parameters used in this search task.</p></li>
+<li><p><strong>layout_rewrite_option</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.LayoutRewriteOption" title="tvm.auto_scheduler.LayoutRewriteOption"><em>LayoutRewriteOption</em></a><em>]</em>) – The layout rewrite option used for measuring programs. If None, the default value will be
+set depending on the specified target.
+Auto_scheduler will find a better schedule for the specified layout rewrite option.
+The NO_REWRITE and INSERT_TRANSFORM_STAGE are expected to be used when tuning a standalone
+op, and the REWRITE_FOR_PRE_TRANSFORMED is expected to be used when tuning ops inside a
+network.</p></li>
+<li><p><strong>task_inputs</strong> (<em>Union</em><em>[</em><em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>, </em><a class="reference internal" href="ndarray.html#tvm.nd.NDArray" title="tvm.nd.NDArray"><em>tvm.nd.NDArray</em></a><em>]</em><em>, </em><em>List</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python [...]
+Some special Tensor used as inputs in program measuring. Usually we do not need to care
+about it, but for special workloads like Sparse computation the Sparse Tensor input are
+meaningful that we cannot use random input directly.</p></li>
+<li><p><strong>task_inputs_overwrite</strong> (<em>bool = False</em>) – Whether to overwrite the data if a name has already in the global table.</p></li>
+<li><p><strong>task_inputs_save_to_file</strong> (<em>bool = False</em>) – Whether to save the data to a local file as well. This can be reused to resume the last
+tuning process.</p></li>
+<li><p><strong>desc</strong> (<em>str = ""</em>) – The description string of this task.</p></li>
</ul>
</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>SearchTask</strong></p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>the created task</p>
-</dd>
-</dl>
-</dd></dl>
-
-<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 [...]
-<dd><p>THIS API IS DEPRECATED.</p>
-<p>Run auto scheduling search for a task.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
-<li><p><strong>search_policy</strong> (<em>Optional</em><em>[</em><em>SearchPolicy</em><em>]</em>) – The search policy to be used for schedule search.</p></li>
-<li><p><strong>tuning_options</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><em>TuningOptions</em></a><em>]</em>) – Tuning and measurement options.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p></p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>A <cite>te.Schedule</cite> and the a list of <cite>te.Tensor</cite> to be used in <cite>tvm.lower</cite> or <cite>tvm.build</cite>.</p>
-</dd>
</dl>
-</dd></dl>
+<p class="rubric">Examples</p>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># We support two ways to create a search task</span>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.EmptyPolicy">
-<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">EmptyPolicy</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">init_search_callbacks</span></span><span class="o"><span class="pre">=</span></span><span class="def [...]
-<dd><p>A simple example of the search policy which always returns
-the initial naive schedule (state).</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
-<li><p><strong>init_search_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>SearchCallback</em><em>]</em><em>]</em>) – Callback functions called before the search process.</p></li>
-</ul>
-</dd>
-</dl>
-</dd></dl>
+<span class="c1"># Way 1: create a task by a workload generation function.</span>
+<span class="c1"># The `workload_func` is a function decorated by @auto_scheduler.register_workload</span>
+<span class="n">task</span> <span class="o">=</span> <span class="n">SearchTask</span><span class="p">(</span><span class="n">func</span><span class="o">=</span><span class="n">workload_func</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="n">target</span><span class="p">)</span>
-<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 [...]
-<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>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
-<li><p><strong>program_cost_model</strong> (<em>CostModel = RandomModel</em><em>(</em><em>)</em>) – The cost model to estimate the complete schedules.</p></li>
-<li><p><strong>params</strong> (<em>Optional</em><em>[</em><em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>, </em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>]</em><em>]</em>) – Parameters of the search policy.
-See <cite>src/auto_scheduler/search_policy/sketch_search_policy.h</cite> for the definitions.
-See <cite>DEFAULT_PARAMS</cite> below to find the default values.</p></li>
-<li><p><strong>seed</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) – Random seed.</p></li>
-<li><p><strong>verbose</strong> (<em>int = 1</em>) – Verbosity level. 0 for silent, 1 to output information during schedule search.</p></li>
-<li><p><strong>init_search_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>SearchCallback</em><em>]</em><em>]</em>) – <p>Callback functions called before the search process, usually used to do extra
-initializations.
-Possible callbacks:</p>
-<blockquote>
-<div><ul>
-<li><p>auto_scheduler.PreloadMeasuredStates</p></li>
-<li><p>auto_scheduler.PreloadCustomSketchRule</p></li>
-</ul>
-</div></blockquote>
-</p></li>
-</ul>
-</dd>
-</dl>
+<span class="c1"># Way 2: create a task by a workload_key.</span>
+<span class="c1"># The `workload_key` is a string, which can be either a hash key or a json-serialized</span>
+<span class="c1"># tuple(func, args).</span>
+<span class="n">task</span> <span class="o">=</span> <span class="n">SearchTask</span><span class="p">(</span><span class="n">workload_key</span><span class="o">=</span><span class="n">workload_key</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="n">target</span><span class="p">)</span>
+</pre></div>
+</div>
<p><strong>Methods:</strong></p>
<table class="longtable docutils align-default">
<colgroup>
@@ -1808,70 +1783,69 @@ Possible callbacks:</p>
<col style="width: 90%" />
</colgroup>
<tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.generate_sketches" title="tvm.auto_scheduler.SketchPolicy.generate_sketches"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_sketches</span></code></a>([print_for_debug])</p></td>
-<td><p>Generate the sketches.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.tune" title="tvm.auto_scheduler.SearchTask.tune"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tune</span></code></a>(tuning_options[, search_policy])</p></td>
+<td><p>Run auto scheduling search for a task</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.sample_initial_population" title="tvm.auto_scheduler.SketchPolicy.sample_initial_population"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sample_initial_population</span></code></a>()</p></td>
-<td><p>Sample initial population.</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.apply_best" title="tvm.auto_scheduler.SearchTask.apply_best"><code class="xref py py-obj docutils literal notranslate"><span class="pre">apply_best</span></code></a>(log_file[, include_compatible, ...])</p></td>
+<td><p>Apply the history best from a log file and return the schedule.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SketchPolicy.evolutionary_search" title="tvm.auto_scheduler.SketchPolicy.evolutionary_search"><code class="xref py py-obj docutils literal notranslate"><span class="pre">evolutionary_search</span></code></a>(init_populations, out_size)</p></td>
-<td><p>Perform evolutionary search.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#tvm.auto_scheduler.SearchTask.print_best" title="tvm.auto_scheduler.SearchTask.print_best"><code class="xref py py-obj docutils literal notranslate"><span class="pre">print_best</span></code></a>(log_file[, print_mode])</p></td>
+<td><p>Print the best schedule as python schedule API code or CUDA source code.</p></td>
</tr>
</tbody>
</table>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.generate_sketches">
-<span class="sig-name descname"><span class="pre">generate_sketches</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">print_for_debug</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.generate_sketches" title="Permalink to this definition">¶</a></dt>
-<dd><p>Generate the sketches.
-This python interface is mainly used for debugging and testing.
-The actual search is all done in c++.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.tune">
+<span class="sig-name descname"><span class="pre">tune</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">tuning_options</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><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SearchTask.tune" tit [...]
+<dd><p>Run auto scheduling search for a task</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>print_for_debug</strong> (<em>bool = False</em>) – Whether print out the sketches for debug.</p>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>sketches</strong> – The generated sketches of this search task.</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>List[State]</p>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>tuning_options</strong> (<a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><em>TuningOptions</em></a>) – Tuning and measurement options.</p></li>
+<li><p><strong>search_policy</strong> (<em>Optional</em><em>[</em><em>SearchPolicy</em><em>]</em>) – The search policy to be used for schedule search.</p></li>
+</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.sample_initial_population">
-<span class="sig-name descname"><span class="pre">sample_initial_population</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.sample_initial_population" title="Permalink to this definition">¶</a></dt>
-<dd><p>Sample initial population.
-This python interface is mainly used for debugging and testing.
-The actual search is all done in c++.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.apply_best">
+<span class="sig-name descname"><span class="pre">apply_best</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log_file</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_compatible</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layout_rewrite_option</span></span>< [...]
+<dd><p>Apply the history best from a log file and return the schedule.</p>
<dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
-<dd class="field-odd"><p><strong>states</strong> – The sampled states</p>
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>log_file</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the log file.</p></li>
+<li><p><strong>include_compatible</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) – When set to True, all compatible records in the log file will be considered.</p></li>
+<li><p><strong>layout_rewrite_option</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.LayoutRewriteOption" title="tvm.auto_scheduler.LayoutRewriteOption"><em>LayoutRewriteOption</em></a><em>]</em>) – The layout rewrite option.</p></li>
+</ul>
</dd>
-<dt class="field-even">Return type</dt>
-<dd class="field-even"><p>List[State]</p>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p></p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p>A <cite>te.Schedule</cite> and the a list of <cite>te.Tensor</cite> to be used in <cite>tvm.lower</cite> or <cite>tvm.build</cite>.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy.evolutionary_search">
-<span class="sig-name descname"><span class="pre">evolutionary_search</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_populations</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_size</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SketchPolicy.evolutionary_search" title="Permalink to this definition">¶</a></dt>
-<dd><p>Perform evolutionary search.
-This python interface is mainly used for debugging and testing.
-The actual search is all done in c++.</p>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.SearchTask.print_best">
+<span class="sig-name descname"><span class="pre">print_best</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">log_file</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">print_mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'schedule'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.SearchTask.print_ [...]
+<dd><p>Print the best schedule as python schedule API code or CUDA source code.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>init_populations</strong> (<em>List</em><em>[</em><em>State</em><em>]</em>) – The initial population states</p></li>
-<li><p><strong>out_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) – The size of generated states</p></li>
+<li><p><strong>log_file</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the log file</p></li>
+<li><p><strong>print_mode</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – if “schedule”, print the best schedule as python schedule API code.
+if “cuda”, print the best schedule as CUDA source code.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>states</strong> – The generated states</p>
+<dd class="field-even"><p><strong>code</strong> – The best schedule code in python API or CUDA source code</p>
</dd>
<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>List[State]</p>
+<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)">str</a></p>
</dd>
</dl>
</dd></dl>
@@ -1879,41 +1853,76 @@ The actual search is all done in c++.</p>
</dd></dl>
<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.PreloadMeasuredStates">
-<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">PreloadMeasuredStates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.PreloadMeasuredStates" title="Permalink to this definition">¶</a></dt>
-<dd><p>A SearchCallback to load measured states from the log file for a search policy.</p>
-<dl class="simple">
-<dt>This can resume the state of the search policy:</dt><dd><ul class="simple">
-<li><p>Making sure an already measured state in former searches will never be measured again.</p></li>
-<li><p>The history states can be used to speed up the search process(e.g. SketchPolicy uses
-history states as starting point to perform Evolutionary Search).</p></li>
+<dt class="sig sig-object py" id="tvm.auto_scheduler.TuningOptions">
+<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">TuningOptions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_measure_trials</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span cl [...]
+<dd><p>This controls the options of performance tuning.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>num_measure_trials</strong> (<em>int = 0</em>) – The number of measurement trials.
+The search policy measures <cite>num_measure_trials</cite> schedules in total and returns the best one
+among them.
+With <cite>num_measure_trials</cite> == 0, the policy will do the schedule search but won’t involve
+measurement. This can be used to get a runnable schedule quickly without auto-tuning.</p></li>
+<li><p><strong>early_stopping</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) – Stop the tuning early if getting no improvement after n measurements.</p></li>
+<li><p><strong>num_measures_per_round</strong> (<em>int = 64</em>) – The number of schedules to be measured at each search round.
+The whole schedule search process will try a total number of <cite>num_measure_trials</cite> in several
+rounds.</p></li>
+<li><p><strong>verbose</strong> (<em>int = 1</em>) – Verbosity level. 0 for silent, 1 to output information during schedule search.</p></li>
+<li><p><strong>builder</strong> (<em>Union</em><em>[</em><em>ProgramBuilder</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>] </em><em>= 'local'</em>) – ProgramBuilder which builds the program.</p></li>
+<li><p><strong>runner</strong> (<em>Union</em><em>[</em><em>ProgramRunner</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>] </em><em>= 'local'</em>) – ProgramRunner which runs the program and measures time costs.</p></li>
+<li><p><strong>measure_callbacks</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>MeasureCallback</em><em>]</em><em>]</em>) – Callback functions called after each measurement.
+Candidates:
+- auto_scheduler.RecordToFile</p></li>
</ul>
</dd>
</dl>
+</dd></dl>
+
+<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 [...]
+<dd><p>THIS API IS DEPRECATED.</p>
+<p>Run auto scheduling search for a task.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) – The name of the record file.</p>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>task</strong> (<a class="reference internal" href="#tvm.auto_scheduler.SearchTask" title="tvm.auto_scheduler.SearchTask"><em>SearchTask</em></a>) – The SearchTask for the computation declaration.</p></li>
+<li><p><strong>search_policy</strong> (<em>Optional</em><em>[</em><em>SearchPolicy</em><em>]</em>) – The search policy to be used for schedule search.</p></li>
+<li><p><strong>tuning_options</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.TuningOptions" title="tvm.auto_scheduler.TuningOptions"><em>TuningOptions</em></a><em>]</em>) – Tuning and measurement options.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p></p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p>A <cite>te.Schedule</cite> and the a list of <cite>te.Tensor</cite> to be used in <cite>tvm.lower</cite> or <cite>tvm.build</cite>.</p>
</dd>
</dl>
</dd></dl>
-<dl class="py class">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.PreloadCustomSketchRule">
-<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">PreloadCustomSketchRule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">meet_condition_func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">apply_func</span></span></em>, <em class="sig-param"><span class="n"><spa [...]
-<dd><p>A SearchCallback for SketchSearchPolicy that allows users to add
-custom sketch rule.</p>
-<p class="rubric">Notes</p>
-<p>This is an advanced feature. Make sure you’re clear how it works and this should only be used
-in SketchSearchPolicy.</p>
+<dl class="py function">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.create_task">
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">create_task</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class [...]
+<dd><p>THIS API IS DEPRECATED.</p>
+<p>Create a search task.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
-<li><p><strong>meet_condition_func</strong> (<em>Callable</em>) – A function with <cite>(policy, state, stage_id) -> int</cite>. Should return one of the result
-enumeration.</p></li>
-<li><p><strong>apply_func</strong> (<em>Callable</em>) – A function with <cite>(policy, state, stage_id) -> [[State, int], …]</cite>.</p></li>
-<li><p><strong>rule_name</strong> (<em>str = "CustomSketchRule"</em>) – The name of this custom sketch rule.</p></li>
+<li><p><strong>func</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The function that returns the compute declaration Tensors.
+Can be the a function or the function name.</p></li>
+<li><p><strong>args</strong> (<em>Union</em><em>[</em><em>Tuple</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>, </em><em>...</em><em>]</em><em>, </em><em>List</em><em>[</em><a class="reference internal" href="tir.html#tvm.tir.Any" title="tvm.tir.Any"><em>Any</em></a><em>]</em><em>]</em>) – The args of the function.</p></li>
+<li><p><strong>target</strong> (<em>Union</em><em>[</em><a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>tvm.target.Target</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The target device of this search task.</p></li>
+<li><p><strong>target_host</strong> (<em>Optional</em><em>[</em><em>Union</em><em>[</em><a class="reference internal" href="target.html#tvm.target.Target" title="tvm.target.Target"><em>tvm.target.Target</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em><em>]</em>) – The target host device of this search task.</p></li>
+<li><p><strong>hardware_params</strong> (<em>Optional</em><em>[</em><a class="reference internal" href="#tvm.auto_scheduler.HardwareParams" title="tvm.auto_scheduler.HardwareParams"><em>HardwareParams</em></a><em>]</em>) – Hardware parameters used in this search task.</p></li>
</ul>
</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p><strong>SearchTask</strong></p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p>the created task</p>
+</dd>
</dl>
</dd></dl>
@@ -1988,6 +1997,27 @@ too many logs.</p></li>
</dd></dl>
+<dl class="py function">
+<dt class="sig sig-object py" id="tvm.auto_scheduler.make_workload_key">
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">make_workload_key</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.make_workload_key" title="Permalink to this defi [...]
+<dd><p>Make a workload key by function and arguments.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters</dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>func</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The function that returns the compute declaration Tensors.
+Can be the a function or the function name.</p></li>
+<li><p><strong>args</strong> (<em>Args</em>) – The args of the function.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns</dt>
+<dd class="field-even"><p><strong>workload_key</strong> – The workload key of the function.</p>
+</dd>
+<dt class="field-odd">Return type</dt>
+<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)">str</a></p>
+</dd>
+</dl>
+</dd></dl>
+
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.register_workload">
<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">register_workload</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class=" [...]
@@ -2015,27 +2045,6 @@ too many logs.</p></li>
</div>
</dd></dl>
-<dl class="py function">
-<dt class="sig sig-object py" id="tvm.auto_scheduler.make_workload_key">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">make_workload_key</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#tvm.auto_scheduler.make_workload_key" title="Permalink to this defi [...]
-<dd><p>Make a workload key by function and arguments.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>func</strong> (<em>Union</em><em>[</em><em>Function</em><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a><em>]</em>) – The function that returns the compute declaration Tensors.
-Can be the a function or the function name.</p></li>
-<li><p><strong>args</strong> (<em>Args</em>) – The args of the function.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p><strong>workload_key</strong> – The workload key of the function.</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)">str</a></p>
-</dd>
-</dl>
-</dd></dl>
-
</div>
diff --git a/docs/reference/api/typedoc/classes/bytestreamreader.html b/docs/reference/api/typedoc/classes/bytestreamreader.html
index 21e1962b2..243b2bf27 100644
--- a/docs/reference/api/typedoc/classes/bytestreamreader.html
+++ b/docs/reference/api/typedoc/classes/bytestreamreader.html
@@ -119,7 +119,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -141,7 +141,7 @@
<div class="tsd-signature tsd-kind-icon">bytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Uint8Array</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
</ul>
</aside>
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@@ -151,7 +151,7 @@
<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>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L42">rpc_server.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L42">rpc_server.ts:42</a></li>
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@@ -168,7 +168,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L63">rpc_server.ts:63</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L63">rpc_server.ts:63</a></li>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Uint8Array</span></h4>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L49">rpc_server.ts:49</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L49">rpc_server.ts:49</a></li>
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@@ -202,7 +202,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/rpc_server.ts#L57">rpc_server.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L57">rpc_server.ts:57</a></li>
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<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4>
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index abc19aae5..cc108195e 100644
--- a/docs/reference/api/typedoc/classes/cachedcallstack.html
+++ b/docs/reference/api/typedoc/classes/cachedcallstack.html
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<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L223">memory.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L223">memory.ts:223</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L208">memory.ts:208</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L208">memory.ts:208</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L312">memory.ts:312</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L312">memory.ts:312</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L284">memory.ts:284</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L284">memory.ts:284</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L388">memory.ts:388</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L388">memory.ts:388</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L376">memory.ts:376</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L376">memory.ts:376</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L267">memory.ts:267</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L267">memory.ts:267</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -373,7 +373,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L243">memory.ts:243</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L243">memory.ts:243</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L321">memory.ts:321</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L321">memory.ts:321</a></li>
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@@ -422,7 +422,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L252">memory.ts:252</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L252">memory.ts:252</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L359">memory.ts:359</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L359">memory.ts:359</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L342">memory.ts:342</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L342">memory.ts:342</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L350">memory.ts:350</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L350">memory.ts:350</a></li>
</ul>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L326">memory.ts:326</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L326">memory.ts:326</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L363">memory.ts:363</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L363">memory.ts:363</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L346">memory.ts:346</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L346">memory.ts:346</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L334">memory.ts:334</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L334">memory.ts:334</a></li>
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index dcf6bcef2..2cb41c07f 100644
--- a/docs/reference/api/typedoc/classes/dldatatype.html
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L262">runtime.ts:262</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L262">runtime.ts:262</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L260">runtime.ts:260</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L260">runtime.ts:260</a></li>
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L258">runtime.ts:258</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L262">runtime.ts:262</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/45568c996/web/src/runtime.ts#L279">runtime.ts:279</a></li>
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- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L270">runtime.ts:270</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L270">runtime.ts:270</a></li>
</ul>
</aside>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4>
diff --git a/docs/reference/api/typedoc/classes/dldevice.html b/docs/reference/api/typedoc/classes/dldevice.html
index 2cb93aa55..7658df7b3 100644
--- a/docs/reference/api/typedoc/classes/dldevice.html
+++ b/docs/reference/api/typedoc/classes/dldevice.html
@@ -118,7 +118,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L202">runtime.ts:202</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L202">runtime.ts:202</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L200">runtime.ts:200</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L198">runtime.ts:198</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L198">runtime.ts:198</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -183,7 +183,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L223">runtime.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L223">runtime.ts:223</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L230">runtime.ts:230</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L230">runtime.ts:230</a></li>
</ul>
</aside>
<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 10348adac..f6312f951 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/12dad9a4a/web/src/environment.ts#L86">environment.ts:86</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/environment.ts#L70">environment.ts:70</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/environment.ts#L70">environment.ts:70</a></li>
</ul>
</aside>
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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/12dad9a4a/web/src/environment.ts#L69">environment.ts:69</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/environment.ts#L78">environment.ts:78</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/environment.ts#L78">environment.ts:78</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/environment.ts#L84">environment.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/environment.ts#L84">environment.ts:84</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/environment.ts#L105">environment.ts:105</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 de3ea98cb..cced46b7e 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/12dad9a4a/web/src/runtime.ts#L49">runtime.ts:49</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L49">runtime.ts:49</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L46">runtime.ts:46</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L46">runtime.ts:46</a></li>
</ul>
</aside>
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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/12dad9a4a/web/src/runtime.ts#L45">runtime.ts:45</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L45">runtime.ts:45</a></li>
</ul>
</aside>
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@@ -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/12dad9a4a/web/src/runtime.ts#L44">runtime.ts:44</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L47">runtime.ts:47</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L47">runtime.ts:47</a></li>
</ul>
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@@ -203,7 +203,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L76">runtime.ts:76</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L76">runtime.ts:76</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L66">runtime.ts:66</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L66">runtime.ts:66</a></li>
</ul>
</aside>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
@@ -243,7 +243,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L84">runtime.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L84">runtime.ts:84</a></li>
</ul>
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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">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L95">runtime.ts:95</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L95">runtime.ts:95</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -283,7 +283,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L72">runtime.ts:72</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 a95057a0c..0bbc5de1c 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/12dad9a4a/web/src/runtime.ts#L583">runtime.ts:583</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L583">runtime.ts:583</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L579">runtime.ts:579</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L579">runtime.ts:579</a></li>
</ul>
</aside>
</section>
@@ -179,7 +179,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L654">runtime.ts:654</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L597">runtime.ts:597</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L631">runtime.ts:631</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L631">runtime.ts:631</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -279,7 +279,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L644">runtime.ts:644</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L644">runtime.ts:644</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -310,7 +310,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L621">runtime.ts:621</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L621">runtime.ts:621</a></li>
</ul>
</aside>
<div class="tsd-comment tsd-typography">
@@ -332,7 +332,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L609">runtime.ts:609</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 bce05747e..8f8f878d7 100644
--- a/docs/reference/api/typedoc/classes/instance.html
+++ b/docs/reference/api/typedoc/classes/instance.html
@@ -139,7 +139,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L692">runtime.ts:692</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L692">runtime.ts:692</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L684">runtime.ts:684</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L683">runtime.ts:683</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L683">runtime.ts:683</a></li>
</ul>
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@@ -229,7 +229,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L932">runtime.ts:932</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L932">runtime.ts:932</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -260,7 +260,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L994">runtime.ts:994</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L994">runtime.ts:994</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -303,7 +303,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L924">runtime.ts:924</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L732">runtime.ts:732</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L952">runtime.ts:952</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L816">runtime.ts:816</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L1033">runtime.ts:1033</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L846">runtime.ts:846</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L846">runtime.ts:846</a></li>
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@@ -497,7 +497,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L750">runtime.ts:750</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L750">runtime.ts:750</a></li>
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@@ -520,7 +520,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L1013">runtime.ts:1013</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L1013">runtime.ts:1013</a></li>
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<div class="tsd-comment tsd-typography">
@@ -568,7 +568,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L789">runtime.ts:789</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L914">runtime.ts:914</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L1134">runtime.ts:1134</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L1134">runtime.ts:1134</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/12dad9a4a/web/src/runtime.ts#L740">runtime.ts:740</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L740">runtime.ts:740</a></li>
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<div class="tsd-comment tsd-typography">
@@ -722,7 +722,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L868">runtime.ts:868</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L868">runtime.ts:868</a></li>
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<div class="tsd-comment tsd-typography">
@@ -754,7 +754,7 @@
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<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L857">runtime.ts:857</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L940">runtime.ts:940</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L940">runtime.ts:940</a></li>
</ul>
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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 929169a0e..18b46cfec 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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L40">memory.ts:40</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L32">memory.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L32">memory.ts:32</a></li>
</ul>
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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>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L33">memory.ts:33</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L33">memory.ts:33</a></li>
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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/12dad9a4a/web/src/memory.ts#L154">memory.ts:154</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L90">memory.ts:90</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L90">memory.ts:90</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -233,7 +233,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L97">memory.ts:97</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L97">memory.ts:97</a></li>
</ul>
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<h4 class="tsd-parameters-title">Parameters</h4>
@@ -256,7 +256,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L74">memory.ts:74</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L74">memory.ts:74</a></li>
</ul>
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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/12dad9a4a/web/src/memory.ts#L81">memory.ts:81</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L81">memory.ts:81</a></li>
</ul>
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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/12dad9a4a/web/src/memory.ts#L104">memory.ts:104</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/memory.ts#L132">memory.ts:132</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L132">memory.ts:132</a></li>
</ul>
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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/12dad9a4a/web/src/memory.ts#L145">memory.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L145">memory.ts:145</a></li>
</ul>
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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/12dad9a4a/web/src/memory.ts#L60">memory.ts:60</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L60">memory.ts:60</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/memory.ts#L67">memory.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L67">memory.ts:67</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -439,7 +439,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L53">memory.ts:53</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/memory.ts#L53">memory.ts:53</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -462,7 +462,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/memory.ts#L114">memory.ts:114</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/memory.ts#L124">memory.ts:124</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/memory.ts#L175">memory.ts:175</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 c8aa99118..92236b68a 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/12dad9a4a/web/src/runtime.ts#L504">runtime.ts:504</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L504">runtime.ts:504</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L502">runtime.ts:502</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L502">runtime.ts:502</a></li>
</ul>
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@@ -187,7 +187,7 @@
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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L516">runtime.ts:516</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L516">runtime.ts:516</a></li>
</ul>
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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/12dad9a4a/web/src/runtime.ts#L530">runtime.ts:530</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L530">runtime.ts:530</a></li>
</ul>
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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/12dad9a4a/web/src/runtime.ts#L561">runtime.ts:561</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L561">runtime.ts:561</a></li>
</ul>
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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 7f97e5246..15542a0bb 100644
--- a/docs/reference/api/typedoc/classes/ndarray.html
+++ b/docs/reference/api/typedoc/classes/ndarray.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/12dad9a4a/web/src/runtime.ts#L304">runtime.ts:304</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L297">runtime.ts:297</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L293">runtime.ts:293</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L289">runtime.ts:289</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L289">runtime.ts:289</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L291">runtime.ts:291</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L291">runtime.ts:291</a></li>
</ul>
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<div class="tsd-comment tsd-typography">
@@ -218,7 +218,7 @@
<div class="tsd-signature tsd-kind-icon">shape<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></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L295">runtime.ts:295</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L295">runtime.ts:295</a></li>
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<div class="tsd-comment tsd-typography">
@@ -240,7 +240,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L370">runtime.ts:370</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L414">runtime.ts:414</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L355">runtime.ts:355</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L474">runtime.ts:474</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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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<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L443">runtime.ts:443</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 3fa789e22..035e2a7ea 100644
--- a/docs/reference/api/typedoc/classes/packedfunccell.html
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@@ -122,7 +122,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/runtime.ts#L158">runtime.ts:158</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L158">runtime.ts:158</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/runtime.ts#L157">runtime.ts:157</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L165">runtime.ts:165</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 728272493..47242330e 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/12dad9a4a/web/src/rpc_server.ts#L92">rpc_server.ts:92</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li>
</ul>
</aside>
</section>
@@ -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/12dad9a4a/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 edb025f6f..ebc070d32 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/12dad9a4a/web/src/runtime.ts#L145">runtime.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L145">runtime.ts:145</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L143">runtime.ts:143</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 ed2c9e9da..2c7837d60 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/12dad9a4a/web/src/webgpu.ts#L57">webgpu.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L50">webgpu.ts:50</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/webgpu.ts#L50">webgpu.ts:50</a></li>
</ul>
</aside>
</section>
@@ -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/12dad9a4a/web/src/webgpu.ts#L51">webgpu.ts:51</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/webgpu.ts#L51">webgpu.ts:51</a></li>
</ul>
</aside>
</section>
@@ -172,7 +172,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/webgpu.ts#L84">webgpu.ts:84</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L170">webgpu.ts:170</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L67">webgpu.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 4edd9cefe..265882ba0 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/12dad9a4a/web/src/ctypes.ts#L220">ctypes.ts:220</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L216">ctypes.ts:216</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L214">ctypes.ts:214</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L218">ctypes.ts:218</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L226">ctypes.ts:226</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L221">ctypes.ts:221</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L219">ctypes.ts:219</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L223">ctypes.ts:223</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L227">ctypes.ts:227</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L222">ctypes.ts:222</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L228">ctypes.ts:228</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L217">ctypes.ts:217</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L224">ctypes.ts:224</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L225">ctypes.ts:225</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L215">ctypes.ts:215</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/ctypes.ts#L215">ctypes.ts:215</a></li>
</ul>
</aside>
</section>
diff --git a/docs/reference/api/typedoc/enums/aynccallbackcode.html b/docs/reference/api/typedoc/enums/aynccallbackcode.html
index 970b08daf..175262579 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/12dad9a4a/web/src/runtime.ts#L676">runtime.ts:676</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L675">runtime.ts:675</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 9ab9d78df..f85e356fe 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/12dad9a4a/web/src/runtime.ts#L242">runtime.ts:242</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L240">runtime.ts:240</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L243">runtime.ts:243</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L241">runtime.ts:241</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 ccc253ad0..4c18032b7 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/12dad9a4a/web/src/rpc_server.ts#L27">rpc_server.ts:27</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L28">rpc_server.ts:28</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L32">rpc_server.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L31">rpc_server.ts:31</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L30">rpc_server.ts:30</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 55cc8c25f..c55e3d961 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/12dad9a4a/web/src/ctypes.ts#L206">ctypes.ts:206</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L207">ctypes.ts:207</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L203">ctypes.ts:203</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L204">ctypes.ts:204</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L201">ctypes.ts:201</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L202">ctypes.ts:202</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L205">ctypes.ts:205</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L200">ctypes.ts:200</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L199">ctypes.ts:199</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 a6638ee99..8aa7a0b0c 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/12dad9a4a/web/src/ctypes.ts#L112">ctypes.ts:112</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L128">ctypes.ts:128</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L144">ctypes.ts:144</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L136">ctypes.ts:136</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L121">ctypes.ts:121</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L160">ctypes.ts:160</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L77">ctypes.ts:77</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L83">ctypes.ts:83</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L67">ctypes.ts:67</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L57">ctypes.ts:57</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/ctypes.ts#L100">ctypes.ts:100</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L88">ctypes.ts:88</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 [...]
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/12dad9a4a/web/src/ctypes.ts#L94">ctypes.ts:94</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/ctypes.ts#L94">ctypes.ts:94</a></li>
</ul>
</aside>
<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/12dad9a4a/web/src/ctypes.ts#L34">ctypes.ts:34</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L52">ctypes.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L42">ctypes.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L48">ctypes.ts:48</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L150">ctypes.ts:150</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L167">ctypes.ts:167</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L170">ctypes.ts:170</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L187">ctypes.ts:187</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L179">ctypes.ts:179</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L193">ctypes.ts:193</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L25">webgpu.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L36">runtime.ts:36</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L25">ctypes.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/ctypes.ts#L28">ctypes.ts:28</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/rpc_server.ts#L36">rpc_server.ts:36</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/support.ts#L25">support.ts:25</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/support.ts#L39">support.ts:39</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/support.ts#L52">support.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/compact.ts#L38">compact.ts:38</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L30">webgpu.ts:30</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/environment.ts#L32">environment.ts:32</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/compact.ts#L24">compact.ts:24</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L1356">runtime.ts:1356</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/web/src/runtime.ts#L1356">runtime.ts:1356</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/12dad9a4a/web/src/support.ts#L62">support.ts:62</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L246">runtime.ts:246</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L247">runtime.ts:247</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L248">runtime.ts:248</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L249">runtime.ts:249</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L250">runtime.ts:250</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L175">runtime.ts:175</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L176">runtime.ts:176</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L180">runtime.ts:180</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L177">runtime.ts:177</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L178">runtime.ts:178</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L179">runtime.ts:179</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L183">runtime.ts:183</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L186">runtime.ts:186</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L184">runtime.ts:184</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L185">runtime.ts:185</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L189">runtime.ts:189</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L187">runtime.ts:187</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L188">runtime.ts:188</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/runtime.ts#L190">runtime.ts:190</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 5f6bb9c60..adada667a 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/12dad9a4a/web/src/types.ts#L52">types.ts:52</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 7ef008bd8..51c45928f 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/12dad9a4a/web/src/webgpu.ts#L41">webgpu.ts:41</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L42">webgpu.ts:42</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/webgpu.ts#L40">webgpu.ts:40</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 f1206b2d0..ffe90b74c 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/12dad9a4a/web/src/types.ts#L34">types.ts:34</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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/12dad9a4a/web/src/types.ts#L39">types.ts:39</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/45568c996/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 91365b7a7..13871b958 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["arch/benchmark","arch/convert_layout","arch/debugger","arch/device_target_interactions","arch/frontend/tensorflow","arch/hybrid_script","arch/index","arch/inferbound","arch/introduction_to_module_serialization","arch/microtvm_design","arch/microtvm_project_api","arch/model_library_format","arch/pass_infra","arch/relay_intro","arch/relay_op_strategy","arch/runtime","arch/runtimes/vulkan","arch/security","arch/virtual_machine","contribute/ci","contribute/code_gu [...]
\ No newline at end of file
+Search.setIndex({docnames:["arch/benchmark","arch/convert_layout","arch/debugger","arch/device_target_interactions","arch/frontend/tensorflow","arch/hybrid_script","arch/index","arch/inferbound","arch/introduction_to_module_serialization","arch/microtvm_design","arch/microtvm_project_api","arch/model_library_format","arch/pass_infra","arch/relay_intro","arch/relay_op_strategy","arch/runtime","arch/runtimes/vulkan","arch/security","arch/virtual_machine","contribute/ci","contribute/code_gu [...]
\ No newline at end of file
diff --git a/docs/topic/vta/tutorials/autotvm/sg_execution_times.html b/docs/topic/vta/tutorials/autotvm/sg_execution_times.html
index fd80d0d37..f0764aa64 100644
--- a/docs/topic/vta/tutorials/autotvm/sg_execution_times.html
+++ b/docs/topic/vta/tutorials/autotvm/sg_execution_times.html
@@ -322,7 +322,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-topic-vta-tutorials-autotvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:19.812</strong> total execution time for <strong>topic_vta_tutorials_autotvm</strong> files:</p>
+<p><strong>00:20.279</strong> total execution time for <strong>topic_vta_tutorials_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 82%" />
@@ -331,7 +331,7 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_vta.html#sphx-glr-topic-vta-tutorials-autotvm-tune-relay-vta-py"><span class="std std-ref">Auto-tuning a convolutional network on VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_vta.py</span></code>)</p></td>
-<td><p>00:19.806</p></td>
+<td><p>00:20.273</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_alu_vta.html#sphx-glr-topic-vta-tutorials-autotvm-tune-alu-vta-py"><span class="std std-ref">Auto-tuning a ALU fused op on VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_alu_vta.py</span></code>)</p></td>
diff --git a/docs/topic/vta/tutorials/autotvm/tune_relay_vta.html b/docs/topic/vta/tutorials/autotvm/tune_relay_vta.html
index 799a0b196..250657f54 100644
--- a/docs/topic/vta/tutorials/autotvm/tune_relay_vta.html
+++ b/docs/topic/vta/tutorials/autotvm/tune_relay_vta.html
@@ -753,7 +753,7 @@ the <code class="docutils literal notranslate"><span class="pre">`TARGET</span><
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Extract tasks...
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/target/target.py:261: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
diff --git a/docs/topic/vta/tutorials/frontend/deploy_classification.html b/docs/topic/vta/tutorials/frontend/deploy_classification.html
index 523baccd9..0a5d64b3a 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_classification.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_classification.html
@@ -560,13 +560,13 @@ and dense layer which will both be executed in fp32 on the CPU.</p></li>
<a href="../../../../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-contrib-graph_executor sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">m</span></a> <span class="o">=</span> <a href="../../../../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.create" title="tvm.contrib.graph_executor.create" class="sphx-glr-backref-mo [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
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 21.22s!
+resnet18_v1 inference graph built in 22.00s!
</pre></div>
</div>
</div>
diff --git a/docs/topic/vta/tutorials/frontend/deploy_detection.html b/docs/topic/vta/tutorials/frontend/deploy_detection.html
index 66ab478ae..46fe494ed 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_detection.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_detection.html
@@ -580,11 +580,11 @@ and dense layer which will both be executed in fp32 on the CPU.</p></li>
<a href="../../../../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-contrib-graph_executor sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">m</span></a> <span class="o">=</span> <a href="../../../../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-back [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:411: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
-yolov3-tiny inference graph built in 14.96s!
+yolov3-tiny inference graph built in 15.45s!
</pre></div>
</div>
</div>
diff --git a/docs/topic/vta/tutorials/frontend/sg_execution_times.html b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
index 43874b03c..040e1e0c5 100644
--- a/docs/topic/vta/tutorials/frontend/sg_execution_times.html
+++ b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
@@ -322,7 +322,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-topic-vta-tutorials-frontend-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>01:27.642</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
+<p><strong>01:29.164</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -331,11 +331,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_detection.html#sphx-glr-topic-vta-tutorials-frontend-deploy-detection-py"><span class="std std-ref">Deploy Pretrained Vision Detection Model from Darknet on VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_detection.py</span></code>)</p></td>
-<td><p>00:46.521</p></td>
+<td><p>00:47.344</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_classification.html#sphx-glr-topic-vta-tutorials-frontend-deploy-classification-py"><span class="std std-ref">Deploy Pretrained Vision Model from MxNet on VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_classification.py</span></code>)</p></td>
-<td><p>00:41.121</p></td>
+<td><p>00:41.820</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/topic/vta/tutorials/matrix_multiply.html b/docs/topic/vta/tutorials/matrix_multiply.html
index 39ac35aa9..adbe37d79 100644
--- a/docs/topic/vta/tutorials/matrix_multiply.html
+++ b/docs/topic/vta/tutorials/matrix_multiply.html
@@ -833,7 +833,7 @@ into a TVM function.</p>
<a href="../../../reference/api/python/runtime.html#tvm.runtime.Module" title="tvm.runtime.Module" class="sphx-glr-backref-module-tvm-runtime sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">f</span></a> <span class="o">=</span> <a href="../../../reference/api/python/rpc.html#tvm.rpc.RPCSession.load_module" title="tvm.rpc.RPCSession.load_module" class="sphx-glr-backref-module-tvm-rpc sphx-glr-backref-type-py-method"><span class="n">remote</span><span class="o">.< [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/topic/vta/tutorials/optimize/convolution_opt.html b/docs/topic/vta/tutorials/optimize/convolution_opt.html
index f62970dc6..316649a5a 100644
--- a/docs/topic/vta/tutorials/optimize/convolution_opt.html
+++ b/docs/topic/vta/tutorials/optimize/convolution_opt.html
@@ -1108,7 +1108,7 @@ ensure correctness.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Successful 2D convolution test!"</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Execution statistics:
inp_load_nbytes : 114688
diff --git a/docs/topic/vta/tutorials/optimize/matrix_multiply_opt.html b/docs/topic/vta/tutorials/optimize/matrix_multiply_opt.html
index 7cb555515..0f07e2332 100644
--- a/docs/topic/vta/tutorials/optimize/matrix_multiply_opt.html
+++ b/docs/topic/vta/tutorials/optimize/matrix_multiply_opt.html
@@ -894,7 +894,7 @@ ensure correctness.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Successful blocked matrix multiply test!"</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
Execution statistics:
inp_load_nbytes : 4096
diff --git a/docs/topic/vta/tutorials/optimize/sg_execution_times.html b/docs/topic/vta/tutorials/optimize/sg_execution_times.html
index 6fae39c27..783206c85 100644
--- a/docs/topic/vta/tutorials/optimize/sg_execution_times.html
+++ b/docs/topic/vta/tutorials/optimize/sg_execution_times.html
@@ -322,7 +322,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-topic-vta-tutorials-optimize-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:03.185</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
+<p><strong>00:03.278</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -331,11 +331,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="convolution_opt.html#sphx-glr-topic-vta-tutorials-optimize-convolution-opt-py"><span class="std std-ref">2D Convolution Optimization</span></a> (<code class="docutils literal notranslate"><span class="pre">convolution_opt.py</span></code>)</p></td>
-<td><p>00:02.808</p></td>
+<td><p>00:02.883</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="matrix_multiply_opt.html#sphx-glr-topic-vta-tutorials-optimize-matrix-multiply-opt-py"><span class="std std-ref">Matrix Multiply Blocking</span></a> (<code class="docutils literal notranslate"><span class="pre">matrix_multiply_opt.py</span></code>)</p></td>
-<td><p>00:00.377</p></td>
+<td><p>00:00.395</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/topic/vta/tutorials/sg_execution_times.html b/docs/topic/vta/tutorials/sg_execution_times.html
index 72218b5b1..6e3dc7375 100644
--- a/docs/topic/vta/tutorials/sg_execution_times.html
+++ b/docs/topic/vta/tutorials/sg_execution_times.html
@@ -322,7 +322,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-topic-vta-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:00.701</strong> total execution time for <strong>topic_vta_tutorials</strong> files:</p>
+<p><strong>00:00.721</strong> total execution time for <strong>topic_vta_tutorials</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -331,11 +331,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="matrix_multiply.html#sphx-glr-topic-vta-tutorials-matrix-multiply-py"><span class="std std-ref">Simple Matrix Multiply</span></a> (<code class="docutils literal notranslate"><span class="pre">matrix_multiply.py</span></code>)</p></td>
-<td><p>00:00.375</p></td>
+<td><p>00:00.386</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="vta_get_started.html#sphx-glr-topic-vta-tutorials-vta-get-started-py"><span class="std std-ref">Get Started with VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">vta_get_started.py</span></code>)</p></td>
-<td><p>00:00.326</p></td>
+<td><p>00:00.335</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/topic/vta/tutorials/vta_get_started.html b/docs/topic/vta/tutorials/vta_get_started.html
index 947217b9a..a1dc7d545 100644
--- a/docs/topic/vta/tutorials/vta_get_started.html
+++ b/docs/topic/vta/tutorials/vta_get_started.html
@@ -695,7 +695,7 @@ we want to compile to.</p>
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/tutorial/auto_scheduler_matmul_x86.html b/docs/tutorial/auto_scheduler_matmul_x86.html
index 3d61ba05d..f82997874 100644
--- a/docs/tutorial/auto_scheduler_matmul_x86.html
+++ b/docs/tutorial/auto_scheduler_matmul_x86.html
@@ -561,7 +561,7 @@ 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: 93.728 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 92.446 ms
</pre></div>
</div>
</div>
@@ -625,7 +625,6 @@ resume the status and do more 5 trials.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Resume search:
/usr/local/lib/python3.7/dist-packages/xgboost/training.py:17: UserWarning: Old style callback is deprecated. See: https://xgboost.readthedocs.io/en/latest/python/callbacks.html
warnings.warn(f'Old style callback is deprecated. See: {link}', UserWarning)
-*E
</pre></div>
</div>
</div>
diff --git a/docs/tutorial/autotvm_matmul_x86.html b/docs/tutorial/autotvm_matmul_x86.html
index f80233fad..75db9c770 100644
--- a/docs/tutorial/autotvm_matmul_x86.html
+++ b/docs/tutorial/autotvm_matmul_x86.html
@@ -660,16 +660,16 @@ reduce variance, we take 5 measurements and average them.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>waiting for device...
device available
Get devices for measurement successfully!
-No: 1 GFLOPS: 10.34/10.34 result: MeasureResult(costs=(0.0259562372,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5491230487823486, timestamp=1656117296.9030733) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
-No: 2 GFLOPS: 2.77/10.34 result: MeasureResult(costs=(0.0969674538,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6972053050994873, timestamp=1656117299.1309118) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
-No: 3 GFLOPS: 11.82/11.82 result: MeasureResult(costs=(0.022706498999999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5993161201477051, timestamp=1656117299.6973338) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
-No: 4 GFLOPS: 1.85/11.82 result: MeasureResult(costs=(0.1452927854,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4411725997924805, timestamp=1656117302.6916847) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
-No: 5 GFLOPS: 3.67/11.82 result: MeasureResult(costs=(0.073103693,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.301805019378662, timestamp=1656117304.1234105) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
-No: 6 GFLOPS: 1.71/11.82 result: MeasureResult(costs=(0.15696236,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.664360284805298, timestamp=1656117306.8340483) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
-No: 7 GFLOPS: 0.87/11.82 result: MeasureResult(costs=(0.3078180376,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.051161050796509, timestamp=1656117312.44912) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
-No: 8 GFLOPS: 10.71/11.82 result: MeasureResult(costs=(0.025068074200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5381650924682617, timestamp=1656117313.0124152) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
-No: 9 GFLOPS: 1.90/11.82 result: MeasureResult(costs=(0.1416254626,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.361100196838379, timestamp=1656117315.4919925) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
-No: 10 GFLOPS: 2.71/11.82 result: MeasureResult(costs=(0.09921746960000001,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6903772354125977, timestamp=1656117317.2416878) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
+No: 1 GFLOPS: 9.02/9.02 result: MeasureResult(costs=(0.029773967800000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6079602241516113, timestamp=1656357607.0578802) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
+No: 2 GFLOPS: 2.40/9.02 result: MeasureResult(costs=(0.1116488642,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.9338338375091553, timestamp=1656357609.009395) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
+No: 3 GFLOPS: 11.86/11.86 result: MeasureResult(costs=(0.022629014,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5676710605621338, timestamp=1656357610.0525854) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
+No: 4 GFLOPS: 1.62/11.86 result: MeasureResult(costs=(0.16590396820000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.772679090499878, timestamp=1656357613.3981004) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
+No: 5 GFLOPS: 3.69/11.86 result: MeasureResult(costs=(0.0728351586,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.300386905670166, timestamp=1656357614.8272932) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
+No: 6 GFLOPS: 1.89/11.86 result: MeasureResult(costs=(0.1418611314,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.430314540863037, timestamp=1656357617.3039713) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
+No: 7 GFLOPS: 0.77/11.86 result: MeasureResult(costs=(0.3487647382,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.7042810916900635, timestamp=1656357623.5580387) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
+No: 8 GFLOPS: 10.62/11.86 result: MeasureResult(costs=(0.025265008,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5482184886932373, timestamp=1656357624.12589) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
+No: 9 GFLOPS: 1.78/11.86 result: MeasureResult(costs=(0.1507286632,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.5086991786956787, timestamp=1656357626.7537687) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
+No: 10 GFLOPS: 2.69/11.86 result: MeasureResult(costs=(0.09990336139999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.701523780822754, timestamp=1656357628.5155542) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
</pre></div>
</div>
<p>With tuning completed, we can choose the configuration from the log file that
diff --git a/docs/tutorial/autotvm_relay_x86.html b/docs/tutorial/autotvm_relay_x86.html
index 8005766a1..425008feb 100644
--- a/docs/tutorial/autotvm_relay_x86.html
+++ b/docs/tutorial/autotvm_relay_x86.html
@@ -495,7 +495,7 @@ set.</p>
<a href="../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-contrib-graph_executor sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">module</span></a> <span class="o">=</span> <a href="../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-co [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -542,7 +542,7 @@ standard deviation.</p>
<span class="nb">print</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">unoptimized</span></a><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{'mean': 494.34375246999025, 'median': 494.3581909499926, 'std': 0.9444984363007716}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{'mean': 493.2739005100075, 'median': 493.0039684500116, 'std': 0.8300160632685638}
</pre></div>
</div>
</div>
@@ -693,183 +693,183 @@ depending on the specifics of the model and the target platform.</p>
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 1/25] Current/Best: 17.41/ 17.41 GFLOPS | Progress: (4/20) | 6.25 s
-[Task 1/25] Current/Best: 6.15/ 17.41 GFLOPS | Progress: (8/20) | 9.23 s
-[Task 1/25] Current/Best: 11.53/ 22.73 GFLOPS | Progress: (12/20) | 11.68 s
-[Task 1/25] Current/Best: 16.87/ 22.73 GFLOPS | Progress: (16/20) | 13.35 s
-[Task 1/25] Current/Best: 11.62/ 23.97 GFLOPS | Progress: (20/20) | 15.09 s Done.
+[Task 1/25] Current/Best: 17.53/ 17.53 GFLOPS | Progress: (4/20) | 6.20 s
+[Task 1/25] Current/Best: 6.17/ 17.53 GFLOPS | Progress: (8/20) | 9.11 s
+[Task 1/25] Current/Best: 11.54/ 22.89 GFLOPS | Progress: (12/20) | 11.51 s
+[Task 1/25] Current/Best: 16.80/ 22.89 GFLOPS | Progress: (16/20) | 13.18 s
+[Task 1/25] Current/Best: 11.59/ 23.91 GFLOPS | Progress: (20/20) | 14.93 s Done.
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 2/25] Current/Best: 12.30/ 12.91 GFLOPS | Progress: (4/20) | 3.76 s
-[Task 2/25] Current/Best: 13.84/ 18.26 GFLOPS | Progress: (8/20) | 5.08 s
-[Task 2/25] Current/Best: 21.38/ 21.38 GFLOPS | Progress: (12/20) | 6.39 s
-[Task 2/25] Current/Best: 12.20/ 21.38 GFLOPS | Progress: (16/20) | 7.64 s
-[Task 2/25] Current/Best: 20.21/ 21.38 GFLOPS | Progress: (20/20) | 9.23 s Done.
+[Task 2/25] Current/Best: 12.19/ 13.14 GFLOPS | Progress: (4/20) | 3.62 s
+[Task 2/25] Current/Best: 14.15/ 18.75 GFLOPS | Progress: (8/20) | 4.91 s
+[Task 2/25] Current/Best: 21.00/ 21.00 GFLOPS | Progress: (12/20) | 6.21 s
+[Task 2/25] Current/Best: 12.88/ 21.00 GFLOPS | Progress: (16/20) | 7.49 s
+[Task 2/25] Current/Best: 18.90/ 21.00 GFLOPS | Progress: (20/20) | 9.03 s Done.
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 3/25] Current/Best: 1.63/ 10.58 GFLOPS | Progress: (4/20) | 5.85 s
-[Task 3/25] Current/Best: 15.59/ 16.86 GFLOPS | Progress: (8/20) | 7.75 s
-[Task 3/25] Current/Best: 14.91/ 16.86 GFLOPS | Progress: (12/20) | 9.48 s
-[Task 3/25] Current/Best: 7.22/ 23.82 GFLOPS | Progress: (16/20) | 11.39 s
-[Task 3/25] Current/Best: 12.66/ 23.82 GFLOPS | Progress: (20/20) | 15.88 s Done.
+[Task 3/25] Current/Best: 1.63/ 10.58 GFLOPS | Progress: (4/20) | 5.83 s
+[Task 3/25] Current/Best: 15.54/ 16.87 GFLOPS | Progress: (8/20) | 7.75 s
+[Task 3/25] Current/Best: 14.94/ 16.87 GFLOPS | Progress: (12/20) | 9.48 s
+[Task 3/25] Current/Best: 7.16/ 23.76 GFLOPS | Progress: (16/20) | 11.41 s
+[Task 3/25] Current/Best: 12.68/ 23.76 GFLOPS | Progress: (20/20) | 15.88 s Done.
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 4/25] Current/Best: 9.56/ 19.75 GFLOPS | Progress: (4/20) | 2.37 s
-[Task 4/25] Current/Best: 6.86/ 19.75 GFLOPS | Progress: (8/20) | 6.71 s
-[Task 4/25] Current/Best: 22.02/ 22.02 GFLOPS | Progress: (12/20) | 11.13 s
-[Task 4/25] Current/Best: 17.37/ 22.02 GFLOPS | Progress: (16/20) | 13.39 s
-[Task 4/25] Current/Best: 13.51/ 22.02 GFLOPS | Progress: (20/20) | 15.27 s Done.
+[Task 4/25] Current/Best: 9.58/ 20.41 GFLOPS | Progress: (4/20) | 2.35 s
+[Task 4/25] Current/Best: 6.80/ 20.41 GFLOPS | Progress: (8/20) | 6.71 s
+[Task 4/25] Current/Best: 22.31/ 22.31 GFLOPS | Progress: (12/20) | 11.11 s
+[Task 4/25] Current/Best: 16.60/ 22.31 GFLOPS | Progress: (16/20) | 13.30 s
+[Task 4/25] Current/Best: 13.38/ 22.31 GFLOPS | Progress: (20/20) | 15.19 s Done.
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 5/25] Current/Best: 9.49/ 10.35 GFLOPS | Progress: (4/20) | 2.58 s
-[Task 5/25] Current/Best: 11.60/ 12.49 GFLOPS | Progress: (8/20) | 4.65 s
-[Task 5/25] Current/Best: 11.43/ 18.04 GFLOPS | Progress: (12/20) | 7.72 s
-[Task 5/25] Current/Best: 11.68/ 22.72 GFLOPS | Progress: (16/20) | 9.13 s
-[Task 5/25] Current/Best: 12.04/ 22.72 GFLOPS | Progress: (20/20) | 11.00 s Done.
+[Task 5/25] Current/Best: 9.72/ 10.43 GFLOPS | Progress: (4/20) | 2.58 s
+[Task 5/25] Current/Best: 11.80/ 12.08 GFLOPS | Progress: (8/20) | 4.68 s
+[Task 5/25] Current/Best: 11.57/ 18.07 GFLOPS | Progress: (12/20) | 7.77 s
+[Task 5/25] Current/Best: 11.87/ 22.63 GFLOPS | Progress: (16/20) | 9.21 s
+[Task 5/25] Current/Best: 12.05/ 22.63 GFLOPS | Progress: (20/20) | 11.05 s Done.
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 6/25] Current/Best: 12.19/ 20.77 GFLOPS | Progress: (4/20) | 3.93 s
-[Task 6/25] Current/Best: 18.66/ 20.77 GFLOPS | Progress: (8/20) | 5.68 s
-[Task 6/25] Current/Best: 13.20/ 20.77 GFLOPS | Progress: (12/20) | 7.60 s
-[Task 6/25] Current/Best: 19.98/ 20.77 GFLOPS | Progress: (16/20) | 9.87 s
-[Task 6/25] Current/Best: 3.73/ 20.77 GFLOPS | Progress: (20/20) | 12.41 s Done.
+[Task 6/25] Current/Best: 12.22/ 20.81 GFLOPS | Progress: (4/20) | 3.94 s
+[Task 6/25] Current/Best: 18.99/ 20.81 GFLOPS | Progress: (8/20) | 5.68 s
+[Task 6/25] Current/Best: 13.34/ 20.81 GFLOPS | Progress: (12/20) | 7.60 s
+[Task 6/25] Current/Best: 20.08/ 20.81 GFLOPS | Progress: (16/20) | 9.83 s
+[Task 6/25] Current/Best: 3.73/ 20.81 GFLOPS | Progress: (20/20) | 12.34 s Done.
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 7/25] Current/Best: 11.22/ 12.13 GFLOPS | Progress: (4/20) | 3.61 s
-[Task 7/25] Current/Best: 20.19/ 21.10 GFLOPS | Progress: (8/20) | 5.13 s
-[Task 7/25] Current/Best: 14.89/ 21.10 GFLOPS | Progress: (12/20) | 7.04 s
-[Task 7/25] Current/Best: 12.26/ 21.10 GFLOPS | Progress: (16/20) | 9.09 s
-[Task 7/25] Current/Best: 6.37/ 21.71 GFLOPS | Progress: (20/20) | 11.56 s Done.
+[Task 7/25] Current/Best: 11.30/ 12.83 GFLOPS | Progress: (4/20) | 3.58 s
+[Task 7/25] Current/Best: 20.29/ 21.16 GFLOPS | Progress: (8/20) | 5.07 s
+[Task 7/25] Current/Best: 14.05/ 21.16 GFLOPS | Progress: (12/20) | 7.03 s
+[Task 7/25] Current/Best: 12.28/ 21.16 GFLOPS | Progress: (16/20) | 9.07 s
+[Task 7/25] Current/Best: 5.82/ 21.79 GFLOPS | Progress: (20/20) | 11.54 s Done.
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 8/25] Current/Best: 10.30/ 13.89 GFLOPS | Progress: (4/20) | 2.90 s
-[Task 8/25] Current/Best: 9.60/ 13.89 GFLOPS | Progress: (8/20) | 7.67 s
-[Task 8/25] Current/Best: 12.30/ 13.89 GFLOPS | Progress: (12/20) | 13.85 s
-[Task 8/25] Current/Best: 18.73/ 18.73 GFLOPS | Progress: (16/20) | 15.94 s
-[Task 8/25] Current/Best: 20.20/ 20.20 GFLOPS | Progress: (20/20) | 22.46 s Done.
+[Task 8/25] Current/Best: 9.98/ 14.30 GFLOPS | Progress: (4/20) | 2.87 s
+[Task 8/25] Current/Best: 9.75/ 14.30 GFLOPS | Progress: (8/20) | 7.62 s
+[Task 8/25] Current/Best: 12.82/ 14.30 GFLOPS | Progress: (12/20) | 13.68 s
+[Task 8/25] Current/Best: 18.74/ 18.74 GFLOPS | Progress: (16/20) | 15.75 s
+[Task 8/25] Current/Best: 18.14/ 18.74 GFLOPS | Progress: (20/20) | 22.22 s Done.
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 9/25] Current/Best: 14.28/ 15.77 GFLOPS | Progress: (4/20) | 11.93 s
-[Task 9/25] Current/Best: 23.49/ 23.49 GFLOPS | Progress: (8/20) | 13.65 s
-[Task 9/25] Current/Best: 8.29/ 23.49 GFLOPS | Progress: (12/20) | 15.99 s
-[Task 9/25] Current/Best: 17.87/ 23.49 GFLOPS | Progress: (16/20) | 18.61 s
-[Task 9/25] Current/Best: 9.03/ 23.49 GFLOPS | Progress: (20/20) | 26.14 s
+[Task 9/25] Current/Best: 14.37/ 15.92 GFLOPS | Progress: (4/20) | 11.94 s
+[Task 9/25] Current/Best: 22.76/ 22.76 GFLOPS | Progress: (8/20) | 13.67 s
+[Task 9/25] Current/Best: 8.29/ 22.76 GFLOPS | Progress: (12/20) | 15.98 s
+[Task 9/25] Current/Best: 18.03/ 22.76 GFLOPS | Progress: (16/20) | 18.61 s
+[Task 9/25] Current/Best: 9.07/ 22.76 GFLOPS | Progress: (20/20) | 26.22 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 10/25] Current/Best: 18.25/ 18.25 GFLOPS | Progress: (4/20) | 2.55 s
-[Task 10/25] Current/Best: 15.54/ 18.25 GFLOPS | Progress: (8/20) | 4.14 s
-[Task 10/25] Current/Best: 11.90/ 18.93 GFLOPS | Progress: (12/20) | 5.66 s
-[Task 10/25] Current/Best: 19.11/ 20.17 GFLOPS | Progress: (16/20) | 6.76 s
-[Task 10/25] Current/Best: 8.77/ 20.17 GFLOPS | Progress: (20/20) | 8.29 s Done.
+[Task 10/25] Current/Best: 18.18/ 18.18 GFLOPS | Progress: (4/20) | 2.53 s
+[Task 10/25] Current/Best: 15.54/ 18.18 GFLOPS | Progress: (8/20) | 4.13 s
+[Task 10/25] Current/Best: 11.75/ 19.00 GFLOPS | Progress: (12/20) | 5.65 s
+[Task 10/25] Current/Best: 19.16/ 20.38 GFLOPS | Progress: (16/20) | 6.75 s
+[Task 10/25] Current/Best: 8.91/ 20.38 GFLOPS | Progress: (20/20) | 8.29 s Done.
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 11/25] Current/Best: 12.28/ 18.12 GFLOPS | Progress: (4/20) | 3.28 s
-[Task 11/25] Current/Best: 16.97/ 18.12 GFLOPS | Progress: (8/20) | 5.98 s
-[Task 11/25] Current/Best: 18.22/ 18.22 GFLOPS | Progress: (12/20) | 8.04 s
-[Task 11/25] Current/Best: 11.90/ 21.18 GFLOPS | Progress: (16/20) | 10.82 s
-[Task 11/25] Current/Best: 19.44/ 21.50 GFLOPS | Progress: (20/20) | 12.82 s Done.
+[Task 11/25] Current/Best: 12.18/ 18.02 GFLOPS | Progress: (4/20) | 3.24 s
+[Task 11/25] Current/Best: 16.99/ 18.02 GFLOPS | Progress: (8/20) | 5.96 s
+[Task 11/25] Current/Best: 18.12/ 18.12 GFLOPS | Progress: (12/20) | 7.99 s
+[Task 11/25] Current/Best: 13.51/ 21.24 GFLOPS | Progress: (16/20) | 10.75 s
+[Task 11/25] Current/Best: 19.48/ 21.59 GFLOPS | Progress: (20/20) | 12.77 s Done.
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 12/25] Current/Best: 7.83/ 17.96 GFLOPS | Progress: (4/20) | 5.26 s
-[Task 12/25] Current/Best: 5.26/ 17.96 GFLOPS | Progress: (8/20) | 8.98 s
-[Task 12/25] Current/Best: 18.78/ 19.00 GFLOPS | Progress: (12/20) | 10.96 s
-[Task 12/25] Current/Best: 15.51/ 19.00 GFLOPS | Progress: (16/20) | 13.69 s
-[Task 12/25] Current/Best: 15.17/ 19.00 GFLOPS | Progress: (20/20) | 15.61 s Done.
+[Task 12/25] Current/Best: 7.84/ 18.02 GFLOPS | Progress: (4/20) | 5.29 s
+[Task 12/25] Current/Best: 5.32/ 18.02 GFLOPS | Progress: (8/20) | 8.92 s
+[Task 12/25] Current/Best: 18.92/ 18.94 GFLOPS | Progress: (12/20) | 10.92 s
+[Task 12/25] Current/Best: 15.43/ 18.94 GFLOPS | Progress: (16/20) | 13.65 s
+[Task 12/25] Current/Best: 15.13/ 18.94 GFLOPS | Progress: (20/20) | 15.61 s Done.
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 13/25] Current/Best: 8.62/ 17.14 GFLOPS | Progress: (4/20) | 3.62 s
-[Task 13/25] Current/Best: 15.68/ 21.13 GFLOPS | Progress: (8/20) | 6.05 s
-[Task 13/25] Current/Best: 19.67/ 21.91 GFLOPS | Progress: (12/20) | 8.92 s
-[Task 13/25] Current/Best: 12.31/ 21.91 GFLOPS | Progress: (16/20) | 12.34 s
-[Task 13/25] Current/Best: 18.18/ 21.91 GFLOPS | Progress: (20/20) | 14.61 s Done.
+[Task 13/25] Current/Best: 8.80/ 17.31 GFLOPS | Progress: (4/20) | 3.61 s
+[Task 13/25] Current/Best: 15.88/ 21.02 GFLOPS | Progress: (8/20) | 6.02 s
+[Task 13/25] Current/Best: 19.76/ 21.61 GFLOPS | Progress: (12/20) | 8.91 s
+[Task 13/25] Current/Best: 12.27/ 21.61 GFLOPS | Progress: (16/20) | 12.32 s
+[Task 13/25] Current/Best: 18.66/ 21.61 GFLOPS | Progress: (20/20) | 14.59 s Done.
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 14/25] Current/Best: 12.70/ 13.23 GFLOPS | Progress: (4/20) | 3.34 s
-[Task 14/25] Current/Best: 6.12/ 13.39 GFLOPS | Progress: (8/20) | 5.55 s
-[Task 14/25] Current/Best: 19.68/ 19.68 GFLOPS | Progress: (12/20) | 8.07 s
-[Task 14/25] Current/Best: 16.95/ 19.68 GFLOPS | Progress: (16/20) | 9.70 s Done.
+[Task 14/25] Current/Best: 13.61/ 13.61 GFLOPS | Progress: (4/20) | 3.23 s
+[Task 14/25] Current/Best: 6.07/ 13.61 GFLOPS | Progress: (8/20) | 5.44 s
+[Task 14/25] Current/Best: 20.85/ 20.85 GFLOPS | Progress: (12/20) | 7.96 s
+[Task 14/25] Current/Best: 16.92/ 20.85 GFLOPS | Progress: (16/20) | 9.62 s Done.
-[Task 14/25] Current/Best: 17.20/ 19.68 GFLOPS | Progress: (20/20) | 11.40 s
+[Task 14/25] Current/Best: 15.77/ 20.85 GFLOPS | Progress: (20/20) | 11.37 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 15/25] Current/Best: 16.10/ 17.69 GFLOPS | Progress: (4/20) | 2.65 s
-[Task 15/25] Current/Best: 14.23/ 18.03 GFLOPS | Progress: (8/20) | 3.94 s
-[Task 15/25] Current/Best: 10.38/ 22.31 GFLOPS | Progress: (12/20) | 6.02 s
-[Task 15/25] Current/Best: 20.43/ 22.31 GFLOPS | Progress: (16/20) | 9.20 s
-[Task 15/25] Current/Best: 9.71/ 22.31 GFLOPS | Progress: (20/20) | 10.20 s
+[Task 15/25] Current/Best: 16.13/ 17.64 GFLOPS | Progress: (4/20) | 2.69 s
+[Task 15/25] Current/Best: 12.99/ 18.10 GFLOPS | Progress: (8/20) | 4.02 s
+[Task 15/25] Current/Best: 10.39/ 22.30 GFLOPS | Progress: (12/20) | 6.06 s
+[Task 15/25] Current/Best: 20.41/ 22.30 GFLOPS | Progress: (16/20) | 9.49 s
+[Task 15/25] Current/Best: 9.71/ 22.30 GFLOPS | Progress: (20/20) | 10.50 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 16/25] Current/Best: 20.64/ 20.64 GFLOPS | Progress: (4/20) | 2.91 s
-[Task 16/25] Current/Best: 3.04/ 20.64 GFLOPS | Progress: (8/20) | 4.52 s
-[Task 16/25] Current/Best: 19.28/ 20.64 GFLOPS | Progress: (12/20) | 5.73 s
-[Task 16/25] Current/Best: 17.08/ 20.64 GFLOPS | Progress: (16/20) | 7.05 s
-[Task 16/25] Current/Best: 10.04/ 22.12 GFLOPS | Progress: (20/20) | 9.08 s Done.
+[Task 16/25] Current/Best: 20.36/ 20.36 GFLOPS | Progress: (4/20) | 2.99 s
+[Task 16/25] Current/Best: 3.04/ 20.36 GFLOPS | Progress: (8/20) | 4.60 s
+[Task 16/25] Current/Best: 19.63/ 20.36 GFLOPS | Progress: (12/20) | 5.81 s
+[Task 16/25] Current/Best: 17.75/ 20.36 GFLOPS | Progress: (16/20) | 7.14 s
+[Task 16/25] Current/Best: 10.06/ 22.03 GFLOPS | Progress: (20/20) | 9.16 s Done.
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 17/25] Current/Best: 13.11/ 18.88 GFLOPS | Progress: (4/20) | 4.67 s
-[Task 17/25] Current/Best: 14.38/ 23.31 GFLOPS | Progress: (8/20) | 7.51 s
-[Task 17/25] Current/Best: 16.85/ 23.31 GFLOPS | Progress: (12/20) | 9.57 s
-[Task 17/25] Current/Best: 16.53/ 23.31 GFLOPS | Progress: (16/20) | 11.71 s
-[Task 17/25] Current/Best: 10.00/ 23.31 GFLOPS | Progress: (20/20) | 13.81 s Done.
+[Task 17/25] Current/Best: 13.15/ 18.88 GFLOPS | Progress: (4/20) | 4.68 s
+[Task 17/25] Current/Best: 14.46/ 23.39 GFLOPS | Progress: (8/20) | 7.41 s
+[Task 17/25] Current/Best: 16.81/ 23.39 GFLOPS | Progress: (12/20) | 9.43 s
+[Task 17/25] Current/Best: 16.55/ 23.39 GFLOPS | Progress: (16/20) | 11.54 s
+[Task 17/25] Current/Best: 10.06/ 23.39 GFLOPS | Progress: (20/20) | 13.65 s Done.
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 18/25] Current/Best: 11.37/ 18.09 GFLOPS | Progress: (4/20) | 3.64 s
-[Task 18/25] Current/Best: 10.55/ 19.51 GFLOPS | Progress: (8/20) | 7.04 s
-[Task 18/25] Current/Best: 18.93/ 19.51 GFLOPS | Progress: (12/20) | 8.97 s
-[Task 18/25] Current/Best: 10.06/ 19.51 GFLOPS | Progress: (16/20) | 12.47 s
-[Task 18/25] Current/Best: 20.63/ 20.63 GFLOPS | Progress: (20/20) | 13.96 s Done.
+[Task 18/25] Current/Best: 11.46/ 17.93 GFLOPS | Progress: (4/20) | 3.64 s
+[Task 18/25] Current/Best: 10.59/ 18.89 GFLOPS | Progress: (8/20) | 7.01 s
+[Task 18/25] Current/Best: 19.23/ 19.23 GFLOPS | Progress: (12/20) | 8.93 s
+[Task 18/25] Current/Best: 10.02/ 19.23 GFLOPS | Progress: (16/20) | 12.42 s
+[Task 18/25] Current/Best: 20.83/ 20.83 GFLOPS | Progress: (20/20) | 13.91 s Done.
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 19/25] Current/Best: 7.18/ 20.51 GFLOPS | Progress: (4/20) | 5.98 s
-[Task 19/25] Current/Best: 2.61/ 20.51 GFLOPS | Progress: (8/20) | 9.24 s
-[Task 19/25] Current/Best: 20.22/ 21.32 GFLOPS | Progress: (12/20) | 11.99 s
-[Task 19/25] Current/Best: 14.27/ 21.32 GFLOPS | Progress: (16/20) | 14.86 s
-[Task 19/25] Current/Best: 2.70/ 23.86 GFLOPS | Progress: (20/20) | 17.68 s Done.
+[Task 19/25] Current/Best: 7.23/ 20.49 GFLOPS | Progress: (4/20) | 5.94 s
+[Task 19/25] Current/Best: 2.60/ 20.49 GFLOPS | Progress: (8/20) | 9.24 s
+[Task 19/25] Current/Best: 20.04/ 21.79 GFLOPS | Progress: (12/20) | 12.05 s
+[Task 19/25] Current/Best: 13.04/ 21.79 GFLOPS | Progress: (16/20) | 14.91 s
+[Task 19/25] Current/Best: 2.70/ 23.79 GFLOPS | Progress: (20/20) | 17.74 s Done.
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 20/25] Current/Best: 8.55/ 14.90 GFLOPS | Progress: (4/20) | 3.29 s Done.
+[Task 20/25] Current/Best: 9.01/ 15.27 GFLOPS | Progress: (4/20) | 3.30 s Done.
Done.
-[Task 20/25] Current/Best: 9.57/ 14.90 GFLOPS | Progress: (8/20) | 6.72 s
-[Task 20/25] Current/Best: 2.32/ 16.26 GFLOPS | Progress: (12/20) | 10.55 s
-[Task 20/25] Current/Best: 12.46/ 16.26 GFLOPS | Progress: (16/20) | 14.09 s
-[Task 20/25] Current/Best: 12.38/ 22.33 GFLOPS | Progress: (20/20) | 16.14 s
+[Task 20/25] Current/Best: 9.65/ 15.27 GFLOPS | Progress: (8/20) | 6.73 s
+[Task 20/25] Current/Best: 2.32/ 16.64 GFLOPS | Progress: (12/20) | 10.66 s
+[Task 20/25] Current/Best: 12.39/ 16.64 GFLOPS | Progress: (16/20) | 14.33 s
+[Task 20/25] Current/Best: 12.62/ 22.13 GFLOPS | Progress: (20/20) | 16.40 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 21/25] Current/Best: 6.43/ 17.76 GFLOPS | Progress: (4/20) | 3.17 s
-[Task 21/25] Current/Best: 14.60/ 17.76 GFLOPS | Progress: (8/20) | 4.71 s
-[Task 21/25] Current/Best: 1.61/ 17.76 GFLOPS | Progress: (12/20) | 6.85 s
-[Task 21/25] Current/Best: 17.98/ 17.98 GFLOPS | Progress: (16/20) | 10.27 s
-[Task 21/25] Current/Best: 4.46/ 17.98 GFLOPS | Progress: (20/20) | 17.31 s
+[Task 21/25] Current/Best: 6.41/ 17.71 GFLOPS | Progress: (4/20) | 3.21 s
+[Task 21/25] Current/Best: 14.66/ 17.71 GFLOPS | Progress: (8/20) | 4.75 s
+[Task 21/25] Current/Best: 1.61/ 17.71 GFLOPS | Progress: (12/20) | 6.89 s
+[Task 21/25] Current/Best: 17.80/ 17.80 GFLOPS | Progress: (16/20) | 10.31 s
+[Task 21/25] Current/Best: 4.47/ 17.80 GFLOPS | Progress: (20/20) | 17.33 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 22/25] Current/Best: 2.71/ 17.00 GFLOPS | Progress: (4/20) | 2.63 s
-[Task 22/25] Current/Best: 8.71/ 22.09 GFLOPS | Progress: (8/20) | 4.62 s
-[Task 22/25] Current/Best: 20.12/ 22.09 GFLOPS | Progress: (12/20) | 6.89 s
-[Task 22/25] Current/Best: 15.38/ 22.09 GFLOPS | Progress: (16/20) | 9.00 s
-[Task 22/25] Current/Best: 14.05/ 22.09 GFLOPS | Progress: (20/20) | 10.64 s Done.
+[Task 22/25] Current/Best: 2.70/ 17.02 GFLOPS | Progress: (4/20) | 2.67 s
+[Task 22/25] Current/Best: 8.76/ 21.96 GFLOPS | Progress: (8/20) | 4.56 s
+[Task 22/25] Current/Best: 20.01/ 21.96 GFLOPS | Progress: (12/20) | 6.88 s
+[Task 22/25] Current/Best: 15.49/ 21.96 GFLOPS | Progress: (16/20) | 8.91 s
+[Task 22/25] Current/Best: 14.27/ 21.96 GFLOPS | Progress: (20/20) | 10.62 s Done.
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 23/25] Current/Best: 17.63/ 20.63 GFLOPS | Progress: (4/20) | 3.20 s
-[Task 23/25] Current/Best: 14.35/ 20.63 GFLOPS | Progress: (8/20) | 6.45 s
-[Task 23/25] Current/Best: 21.07/ 21.83 GFLOPS | Progress: (12/20) | 8.21 s
-[Task 23/25] Current/Best: 6.41/ 21.83 GFLOPS | Progress: (16/20) | 15.21 s
-[Task 23/25] Current/Best: 7.77/ 21.83 GFLOPS | Progress: (20/20) | 19.41 s Done.
+[Task 23/25] Current/Best: 17.70/ 20.93 GFLOPS | Progress: (4/20) | 3.23 s
+[Task 23/25] Current/Best: 14.22/ 20.93 GFLOPS | Progress: (8/20) | 6.59 s
+[Task 23/25] Current/Best: 20.90/ 21.75 GFLOPS | Progress: (12/20) | 8.38 s
+[Task 23/25] Current/Best: 6.41/ 21.75 GFLOPS | Progress: (16/20) | 15.28 s
+[Task 23/25] Current/Best: 7.94/ 21.75 GFLOPS | Progress: (20/20) | 19.46 s Done.
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 24/25] Current/Best: 8.43/ 8.43 GFLOPS | Progress: (4/20) | 11.77 s
-[Task 24/25] Current/Best: 3.66/ 8.43 GFLOPS | Progress: (8/20) | 22.99 s
-[Task 24/25] Current/Best: 4.15/ 8.43 GFLOPS | Progress: (12/20) | 33.69 s Done.
+[Task 24/25] Current/Best: 8.55/ 8.55 GFLOPS | Progress: (4/20) | 11.78 s
+[Task 24/25] Current/Best: 2.11/ 8.55 GFLOPS | Progress: (8/20) | 22.82 s
+[Task 24/25] Current/Best: 4.53/ 8.55 GFLOPS | Progress: (12/20) | 34.33 s Done.
Done.
-[Task 24/25] Current/Best: 6.09/ 9.00 GFLOPS | Progress: (16/20) | 39.05 s
-[Task 24/25] Current/Best: 3.21/ 9.00 GFLOPS | Progress: (20/20) | 44.91 s Done.
+[Task 24/25] Current/Best: 5.91/ 8.70 GFLOPS | Progress: (16/20) | 39.72 s
+[Task 24/25] Current/Best: 3.41/ 8.78 GFLOPS | Progress: (20/20) | 45.52 s Done.
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 25/25] Current/Best: 1.55/ 2.78 GFLOPS | Progress: (4/20) | 11.56 s
-[Task 25/25] Current/Best: 6.32/ 8.53 GFLOPS | Progress: (8/20) | 22.79 s
-[Task 25/25] Current/Best: 6.12/ 8.53 GFLOPS | Progress: (12/20) | 34.21 s
-[Task 25/25] Current/Best: 5.93/ 8.84 GFLOPS | Progress: (16/20) | 36.02 s
-[Task 25/25] Current/Best: 2.96/ 9.34 GFLOPS | Progress: (20/20) | 46.74 s
+[Task 25/25] Current/Best: 1.55/ 2.76 GFLOPS | Progress: (4/20) | 11.57 s
+[Task 25/25] Current/Best: 6.14/ 8.29 GFLOPS | Progress: (8/20) | 22.86 s
+[Task 25/25] Current/Best: 5.98/ 8.29 GFLOPS | Progress: (12/20) | 34.15 s
+[Task 25/25] Current/Best: 5.82/ 8.90 GFLOPS | Progress: (16/20) | 36.05 s
+[Task 25/25] Current/Best: 2.83/ 9.26 GFLOPS | Progress: (20/20) | 46.73 s
</pre></div>
</div>
<p>The output from this tuning process will look something like this:</p>
@@ -916,7 +916,7 @@ model using optimized operators to speed up our computations.</p>
<a href="../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-contrib-graph_executor sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">module</span></a> <span class="o">=</span> <a href="../reference/api/python/graph_executor.html#tvm.contrib.graph_executor.GraphModule" title="tvm.contrib.graph_executor.GraphModule" class="sphx-glr-backref-module-tvm-co [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -972,8 +972,8 @@ improvement in comparing the optimized model to the unoptimized model.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"unoptimized: </span><span class="si">%s</span><span class="s2">"</span> <span class="o">%</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">unoptimized</span></a><span class="p">))</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {'mean': 412.64101150999977, 'median': 412.11191500001405, 'std': 1.6191610398155065}
-unoptimized: {'mean': 494.34375246999025, 'median': 494.3581909499926, 'std': 0.9444984363007716}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {'mean': 408.12680654999895, 'median': 407.4677640000118, 'std': 1.5531821657855862}
+unoptimized: {'mean': 493.2739005100075, 'median': 493.0039684500116, 'std': 0.8300160632685638}
</pre></div>
</div>
</div>
@@ -987,7 +987,7 @@ models.</p>
<p>Here we presented a simple example using ResNet-50 v2 locally. However, TVM
supports many more features including cross-compilation, remote execution and
profiling/benchmarking.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 10 minutes 10.157 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 10 minutes 8.987 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-autotvm-relay-x86-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../_downloads/57a45d9bef1af358191e7d50043e652c/autotvm_relay_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">autotvm_relay_x86.py</span></code></a></p>
diff --git a/docs/tutorial/cross_compilation_and_rpc.html b/docs/tutorial/cross_compilation_and_rpc.html
index d5e54af2b..05a9fe1dd 100644
--- a/docs/tutorial/cross_compilation_and_rpc.html
+++ b/docs/tutorial/cross_compilation_and_rpc.html
@@ -518,7 +518,7 @@ device and returns the measured cost. Network overhead is excluded.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="si">%g</span><span class="s2"> secs/op"</span> <span class="o">%</span> <span class="n">cost</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.678e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.346e-07 secs/op
</pre></div>
</div>
</div>
diff --git a/docs/tutorial/intro_topi.html b/docs/tutorial/intro_topi.html
index 00d57f819..6eace6fbc 100644
--- a/docs/tutorial/intro_topi.html
+++ b/docs/tutorial/intro_topi.html
@@ -478,7 +478,7 @@ we can schedule the following series of operations ending with <code class="code
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/ir.html#tvm.ir.Array" title="tvm.ir.Array" class="sphx-glr-backref-module-tvm-ir sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">sg</span><span class="o">.</span><span class="n">stages</span></a><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[stage(a, placeholder(a, 0x20ccb3c0)), stage(b, placeholder(b, 0xff7adc0)), 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=[i [...]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[stage(a, placeholder(a, 0xf940b30)), stage(b, placeholder(b, 0x26eb8db0)), 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=[i [...]
</pre></div>
</div>
<p>We can test the correctness by comparing with <code class="code docutils literal notranslate"><span class="pre">numpy</span></code> result as follows</p>
diff --git a/docs/tutorial/relay_quick_start.html b/docs/tutorial/relay_quick_start.html
index ddade92df..7eda2ca0a 100644
--- a/docs/tutorial/relay_quick_start.html
+++ b/docs/tutorial/relay_quick_start.html
@@ -524,7 +524,7 @@ in this example. Then the machine code will be generated as the module library.<
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/target/target.py:377: UserWarning: Try specifying cuda arch by adding 'arch=sm_xx' to your target.
warnings.warn("Try specifying cuda arch by adding 'arch=sm_xx' to your target.")
-/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
diff --git a/docs/tutorial/sg_execution_times.html b/docs/tutorial/sg_execution_times.html
index ceba92cda..9200a7e97 100644
--- a/docs/tutorial/sg_execution_times.html
+++ b/docs/tutorial/sg_execution_times.html
@@ -322,7 +322,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-tutorial-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>13:02.719</strong> total execution time for <strong>tutorial</strong> files:</p>
+<p><strong>12:54.775</strong> total execution time for <strong>tutorial</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -331,42 +331,42 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="autotvm_relay_x86.html#sphx-glr-tutorial-autotvm-relay-x86-py"><span class="std std-ref">Compiling and Optimizing a Model with the Python Interface (AutoTVM)</span></a> (<code class="docutils literal notranslate"><span class="pre">autotvm_relay_x86.py</span></code>)</p></td>
-<td><p>10:10.157</p></td>
+<td><p>10:08.987</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensor_expr_get_started.html#sphx-glr-tutorial-tensor-expr-get-started-py"><span class="std std-ref">Working with Operators Using Tensor Expression</span></a> (<code class="docutils literal notranslate"><span class="pre">tensor_expr_get_started.py</span></code>)</p></td>
-<td><p>01:00.901</p></td>
+<td><p>00:58.673</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_scheduler_matmul_x86.html#sphx-glr-tutorial-auto-scheduler-matmul-x86-py"><span class="std std-ref">Optimizing Operators with Auto-scheduling</span></a> (<code class="docutils literal notranslate"><span class="pre">auto_scheduler_matmul_x86.py</span></code>)</p></td>
-<td><p>00:58.655</p></td>
+<td><p>00:52.935</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="relay_quick_start.html#sphx-glr-tutorial-relay-quick-start-py"><span class="std std-ref">Quick Start Tutorial for Compiling Deep Learning Models</span></a> (<code class="docutils literal notranslate"><span class="pre">relay_quick_start.py</span></code>)</p></td>
-<td><p>00:27.941</p></td>
+<td><p>00:27.664</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="autotvm_matmul_x86.html#sphx-glr-tutorial-autotvm-matmul-x86-py"><span class="std std-ref">Optimizing Operators with Schedule Templates and AutoTVM</span></a> (<code class="docutils literal notranslate"><span class="pre">autotvm_matmul_x86.py</span></code>)</p></td>
-<td><p>00:23.742</p></td>
+<td><p>00:24.907</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="intro_topi.html#sphx-glr-tutorial-intro-topi-py"><span class="std std-ref">Introduction to TOPI</span></a> (<code class="docutils literal notranslate"><span class="pre">intro_topi.py</span></code>)</p></td>
-<td><p>00:00.682</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tensor_ir_blitz_course.html#sphx-glr-tutorial-tensor-ir-blitz-course-py"><span class="std std-ref">Blitz Course to TensorIR</span></a> (<code class="docutils literal notranslate"><span class="pre">tensor_ir_blitz_course.py</span></code>)</p></td>
+<td><p>00:00.774</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tensor_ir_blitz_course.html#sphx-glr-tutorial-tensor-ir-blitz-course-py"><span class="std std-ref">Blitz Course to TensorIR</span></a> (<code class="docutils literal notranslate"><span class="pre">tensor_ir_blitz_course.py</span></code>)</p></td>
-<td><p>00:00.508</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="intro_topi.html#sphx-glr-tutorial-intro-topi-py"><span class="std std-ref">Introduction to TOPI</span></a> (<code class="docutils literal notranslate"><span class="pre">intro_topi.py</span></code>)</p></td>
+<td><p>00:00.682</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="cross_compilation_and_rpc.html#sphx-glr-tutorial-cross-compilation-and-rpc-py"><span class="std std-ref">Cross Compilation and RPC</span></a> (<code class="docutils literal notranslate"><span class="pre">cross_compilation_and_rpc.py</span></code>)</p></td>
-<td><p>00:00.133</p></td>
+<td><p>00:00.152</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tvmc_command_line_driver.html#sphx-glr-tutorial-tvmc-command-line-driver-py"><span class="std std-ref">Compiling and Optimizing a Model with TVMC</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_command_line_driver.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="introduction.html#sphx-glr-tutorial-introduction-py"><span class="std std-ref">Introduction</span></a> (<code class="docutils literal notranslate"><span class="pre">introduction.py</span></code>)</p></td>
<td><p>00:00.000</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="introduction.html#sphx-glr-tutorial-introduction-py"><span class="std std-ref">Introduction</span></a> (<code class="docutils literal notranslate"><span class="pre">introduction.py</span></code>)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tvmc_command_line_driver.html#sphx-glr-tutorial-tvmc-command-line-driver-py"><span class="std std-ref">Compiling and Optimizing a Model with TVMC</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_command_line_driver.py</span></code>)</p></td>
<td><p>00:00.000</p></td>
<td><p>0.0 MB</p></td>
</tr>
diff --git a/docs/tutorial/tensor_expr_get_started.html b/docs/tutorial/tensor_expr_get_started.html
index 7bec0d862..7115ffb71 100644
--- a/docs/tutorial/tensor_expr_get_started.html
+++ b/docs/tutorial/tensor_expr_get_started.html
@@ -476,7 +476,7 @@ the inputs and outputs) as well as target language we want to compile to.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">fadd</span> <span class="o">=</span> <a href="../reference/api/python/driver.html#tvm.build" title="tvm.build" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">build</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
</pre></div>
</div>
@@ -534,7 +534,7 @@ helper function to run a profile of the TVM generated code.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000007
-naive: 0.000007
+naive: 0.000006
</pre></div>
</div>
</div>
@@ -583,7 +583,7 @@ compile and run this new schedule with the parallel operation applied:</p>
<span class="n">evaluate_addition</span><span class="p">(</span><span class="n">fadd_parallel</span><span class="p">,</span> <a href="../reference/api/python/target.html#tvm.target.Target" title="tvm.target.Target" class="sphx-glr-backref-module-tvm-target sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">tgt</span></a><span class="p">,</span> <span class="s2">"parallel"</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.h [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
parallel: 0.000006
</pre></div>
@@ -624,7 +624,7 @@ factor to be the number of threads on your CPU.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
vector: 0.000025
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
@@ -659,10 +659,10 @@ vector: 0.000025
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Operator Timing Performance
- numpy 7.052989999465353e-06 1.0
- naive 6.7129e-06 0.9517807342005116
-parallel 6.0362e-06 0.8558356102103604
- vector 2.46616e-05 3.4966163289426833
+ numpy 6.7325199961487665e-06 1.0
+ naive 5.8615e-06 0.870624967078149
+parallel 6.052e-06 0.8989204641741803
+ vector 2.45162e-05 3.6414596635470984
</pre></div>
</div>
<div class="admonition-code-specialization admonition">
@@ -978,7 +978,7 @@ matrix multiplication.</p>
<span class="n">answer</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">a</span><span class="o">.</span><span class="n">numpy</span><span class="p">(),</span> <span class="n">b</span><span class="o">.</span><span class="n">numpy</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: 0.019149
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.017890
</pre></div>
</div>
<p>Now we write a basic matrix multiplication using TVM TE and verify that it
@@ -1019,9 +1019,9 @@ optimizations.</p>
<span class="n">evaluate_operation</span><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">s</span></a><span class="p">,</span> <span class="p">[</span><a href="../reference/api/python/te.html#tvm.te.Tensor" title="tvm.te.Tensor" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-none: 3.410052
+none: 3.255034
</pre></div>
</div>
<p>Let’s take a look at the intermediate representation of the operator and
@@ -1086,9 +1086,9 @@ schedule.</p>
<span class="n">evaluate_operation</span><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">s</span></a><span class="p">,</span> <span class="p">[</span><a href="../reference/api/python/te.html#tvm.te.Tensor" title="tvm.te.Tensor" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-blocking: 0.300462
+blocking: 0.297283
</pre></div>
</div>
<p>By reordering the computation to take advantage of caching, you should see a
@@ -1147,9 +1147,9 @@ already cache friendly from our previous optimizations.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-vectorization: 0.336541
+vectorization: 0.333843
@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, [1048576], []),
@@ -1204,9 +1204,9 @@ more cache friendly.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-loop permutation: 0.117097
+loop permutation: 0.116820
@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, [1048576], []),
@@ -1282,9 +1282,9 @@ optimized schedule.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-array packing: 0.111708
+array packing: 0.110421
@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, [1048576], []),
@@ -1358,9 +1358,9 @@ to `C</cite> when all the block results are ready.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-block caching: 0.111311
+block caching: 0.111059
@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, [1048576], []),
@@ -1427,9 +1427,9 @@ of thread-level parallelization.</p>
<span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-parallelization: 0.143680
+parallelization: 0.143716
@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, [1048576], []),
@@ -1491,13 +1491,13 @@ working, we can compare the results.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span> Operator Timing Performance
- none 3.4100518081000004 1.0
- blocking 0.3004623758 0.08811079499915589
- vectorization 0.3365409461 0.09869086015074727
-loop permutation 0.11709737199999999 0.03433888356823642
- array packing 0.11170753340000002 0.03275830975196849
- block caching 0.111310507 0.032641881491536504
- parallelization 0.1436801223 0.04213429307986236
+ none 3.2550339356 1.0
+ blocking 0.29728293250000004 0.09133020987850374
+ vectorization 0.3338428512 0.1025620186471152
+loop permutation 0.11681979180000002 0.03588896279155585
+ array packing 0.1104211219 0.033923186081820704
+ block caching 0.11105910379999999 0.0341191846221193
+ parallelization 0.1437163352 0.04415202361738473
</pre></div>
</div>
<p>Note that the outputs on the web page reflect the running times on a
@@ -1529,7 +1529,6 @@ is</p>
you can build generic templates of the matrix multiplication and other
operations with tunable parameters that allows you to automatically optimize
the computation for specific platforms.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 0.901 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-tensor-expr-get-started-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../_downloads/40a01cffb015a67aaec0fad7e27cf80d/tensor_expr_get_started.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">tensor_expr_get_started.py</span></code></a></p>