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Posted to commits@tvm.apache.org by tq...@apache.org on 2024/01/24 22:56:45 UTC
(tvm-site) branch asf-site updated: deploying docs (apache/tvm@0e8e4217668183b24a91789150856e1514202a35)
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 9120212e91 deploying docs (apache/tvm@0e8e4217668183b24a91789150856e1514202a35)
9120212e91 is described below
commit 9120212e919ab7593a38aacc94037def98fa6f1b
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Wed Jan 24 22:56:40 2024 +0000
deploying docs (apache/tvm@0e8e4217668183b24a91789150856e1514202a35)
---
.../how_to/compile_models/from_darknet.rst.txt | 2 +-
.../how_to/compile_models/from_mxnet.rst.txt | 2 +-
.../how_to/compile_models/from_oneflow.rst.txt | 2 +-
.../how_to/compile_models/from_paddle.rst.txt | 2 +-
.../how_to/compile_models/from_pytorch.rst.txt | 2 +-
.../how_to/compile_models/from_tensorflow.rst.txt | 2 +-
.../compile_models/sg_execution_times.rst.txt | 22 +-
.../deploy_models/deploy_model_on_adreno.rst.txt | 4 +-
.../deploy_model_on_adreno_tvmc.rst.txt | 2 +-
.../deploy_models/deploy_model_on_android.rst.txt | 2 +-
.../deploy_object_detection_pytorch.rst.txt | 4 +-
.../deploy_models/deploy_prequantized.rst.txt | 6 +-
.../deploy_prequantized_tflite.rst.txt | 2 +-
.../how_to/deploy_models/deploy_quantized.rst.txt | 2 +-
.../deploy_models/sg_execution_times.rst.txt | 20 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 2 +-
.../how_to/extend_tvm/sg_execution_times.rst.txt | 8 +-
.../how_to/extend_tvm/use_pass_instrument.rst.txt | 16 +-
.../optimize_operators/opt_conv_cuda.rst.txt | 2 +-
.../optimize_operators/opt_conv_tensorcore.rst.txt | 2 +-
.../how_to/optimize_operators/opt_gemm.rst.txt | 16 +-
.../optimize_operators/sg_execution_times.rst.txt | 8 +-
.../sg_execution_times.rst.txt | 14 +-
.../tune_conv2d_layer_cuda.rst.txt | 2 +-
.../tune_network_cuda.rst.txt | 4 +-
.../tune_network_x86.rst.txt | 4 +-
.../tune_with_autotvm/sg_execution_times.rst.txt | 8 +-
.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 2 +-
.../work_with_microtvm/micro_autotune.rst.txt | 18 +-
.../work_with_microtvm/micro_pytorch.rst.txt | 4 +-
.../how_to/work_with_microtvm/micro_train.rst.txt | 16 +-
.../work_with_microtvm/sg_execution_times.rst.txt | 14 +-
.../work_with_relay/sg_execution_times.rst.txt | 10 +-
.../how_to/work_with_schedules/intrin_math.rst.txt | 2 +-
.../work_with_schedules/sg_execution_times.rst.txt | 18 +-
.../tutorials/autotvm/sg_execution_times.rst.txt | 4 +-
.../frontend/deploy_classification.rst.txt | 7 +-
.../tutorials/frontend/deploy_detection.rst.txt | 7 +-
.../tutorials/frontend/sg_execution_times.rst.txt | 6 +-
.../tutorials/optimize/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/sg_execution_times.rst.txt | 4 +-
.../tutorial/auto_scheduler_matmul_x86.rst.txt | 6 +-
docs/_sources/tutorial/autotvm_matmul_x86.rst.txt | 20 +-
docs/_sources/tutorial/autotvm_relay_x86.rst.txt | 61 ++---
.../tutorial/cross_compilation_and_rpc.rst.txt | 2 +-
docs/_sources/tutorial/intro_topi.rst.txt | 2 +-
docs/_sources/tutorial/sg_execution_times.rst.txt | 56 ++---
.../tutorial/tensor_expr_get_started.rst.txt | 51 ++--
docs/commit_hash | 2 +-
docs/how_to/compile_models/from_darknet.html | 2 +-
docs/how_to/compile_models/from_mxnet.html | 2 +-
docs/how_to/compile_models/from_oneflow.html | 17 +-
docs/how_to/compile_models/from_paddle.html | 2 +-
docs/how_to/compile_models/from_pytorch.html | 14 +-
docs/how_to/compile_models/from_tensorflow.html | 2 +-
docs/how_to/compile_models/sg_execution_times.html | 22 +-
.../deploy_models/deploy_model_on_adreno.html | 4 +-
.../deploy_models/deploy_model_on_adreno_tvmc.html | 29 ++-
.../deploy_models/deploy_model_on_android.html | 2 +-
.../deploy_object_detection_pytorch.html | 61 ++---
docs/how_to/deploy_models/deploy_prequantized.html | 10 +-
.../deploy_models/deploy_prequantized_tflite.html | 2 +-
docs/how_to/deploy_models/deploy_quantized.html | 2 +-
docs/how_to/deploy_models/sg_execution_times.html | 20 +-
.../extend_tvm/bring_your_own_datatypes.html | 2 +-
docs/how_to/extend_tvm/sg_execution_times.html | 8 +-
docs/how_to/extend_tvm/use_pass_instrument.html | 16 +-
docs/how_to/optimize_operators/opt_conv_cuda.html | 2 +-
.../optimize_operators/opt_conv_tensorcore.html | 2 +-
docs/how_to/optimize_operators/opt_gemm.html | 16 +-
.../optimize_operators/sg_execution_times.html | 8 +-
.../sg_execution_times.html | 14 +-
.../tune_conv2d_layer_cuda.html | 2 +-
.../tune_with_autoscheduler/tune_network_cuda.html | 4 +-
.../tune_with_autoscheduler/tune_network_x86.html | 4 +-
.../tune_with_autotvm/sg_execution_times.html | 8 +-
.../how_to/tune_with_autotvm/tune_conv2d_cuda.html | 2 +-
docs/how_to/work_with_microtvm/micro_autotune.html | 18 +-
docs/how_to/work_with_microtvm/micro_pytorch.html | 6 +-
docs/how_to/work_with_microtvm/micro_train.html | 16 +-
.../work_with_microtvm/sg_execution_times.html | 14 +-
.../how_to/work_with_relay/sg_execution_times.html | 10 +-
docs/how_to/work_with_schedules/intrin_math.html | 2 +-
.../work_with_schedules/sg_execution_times.html | 18 +-
docs/install/nnpack.html | 12 +-
docs/reference/api/python/auto_scheduler.html | 4 +-
.../api/typedoc/classes/ArtifactCache.html | 8 +-
docs/reference/api/typedoc/classes/DLDataType.html | 14 +-
docs/reference/api/typedoc/classes/DLDevice.html | 12 +-
docs/reference/api/typedoc/classes/Instance.html | 102 ++++----
docs/reference/api/typedoc/classes/Module.html | 12 +-
docs/reference/api/typedoc/classes/NDArray.html | 30 +--
docs/reference/api/typedoc/classes/RPCServer.html | 16 +-
docs/reference/api/typedoc/classes/Scalar.html | 8 +-
docs/reference/api/typedoc/classes/TVMArray.html | 16 +-
docs/reference/api/typedoc/classes/TVMObject.html | 12 +-
.../api/typedoc/classes/VirtualMachine.html | 10 +-
.../classes/_internal_.CachedCallStack.html | 36 +--
.../classes/_internal_.CanvasRenderManager.html | 10 +-
.../typedoc/classes/_internal_.Environment.html | 14 +-
.../api/typedoc/classes/_internal_.FFILibrary.html | 22 +-
.../api/typedoc/classes/_internal_.Memory.html | 36 +--
.../typedoc/classes/_internal_.PackedFuncCell.html | 8 +-
.../typedoc/classes/_internal_.RuntimeContext.html | 52 ++--
.../api/typedoc/classes/_internal_.TVMString.html | 14 +-
.../typedoc/classes/_internal_.WebGPUContext.html | 28 +--
.../typedoc/enums/_internal_.RPCServerState.html | 14 +-
docs/reference/api/typedoc/functions/assert.html | 2 +-
.../api/typedoc/functions/createPolyfillWASI.html | 2 +-
.../api/typedoc/functions/detectGPUDevice.html | 2 +-
.../api/typedoc/functions/hasNDArrayInCache.html | 2 +-
.../api/typedoc/functions/instantiate.html | 2 +-
docs/reference/api/typedoc/functions/wasmPath.html | 2 +-
.../api/typedoc/interfaces/Disposable.html | 4 +-
.../typedoc/interfaces/GPUDeviceDetectOutput.html | 8 +-
.../api/typedoc/interfaces/InitProgressReport.html | 10 +-
.../api/typedoc/interfaces/LibraryProvider.html | 6 +-
.../interfaces/_internal_.FunctionInfo.html | 8 +-
.../interfaces/_internal_.NDArrayCacheEntry.html | 14 +-
.../interfaces/_internal_.NDArrayShardEntry.html | 10 +-
.../api/typedoc/types/InitProgressCallback.html | 2 +-
docs/reference/api/typedoc/types/PackedFunc.html | 2 +-
.../types/_internal_.FObjectConstructor.html | 2 +-
.../types/_internal_.FTVMWasmAllocSpace.html | 2 +-
.../types/_internal_.FTVMWasmFreeSpace.html | 2 +-
.../types/_internal_.FTVMWasmPackedCFunc.html | 2 +-
.../api/typedoc/types/_internal_.Pointer.html | 2 +-
.../typedoc/types/_internal_.TVMObjectBase.html | 2 +-
docs/searchindex.js | 2 +-
.../vta/tutorials/autotvm/sg_execution_times.html | 4 +-
.../tutorials/frontend/deploy_classification.html | 3 +-
.../vta/tutorials/frontend/deploy_detection.html | 3 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 4 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 4 +-
docs/tutorial/autotvm_matmul_x86.html | 20 +-
docs/tutorial/autotvm_relay_x86.html | 268 ++++++++++-----------
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/sg_execution_times.html | 22 +-
docs/tutorial/tensor_expr_get_started.html | 47 ++--
142 files changed, 924 insertions(+), 890 deletions(-)
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 42dbaec685..3cfb5a0a7f 100644
--- a/docs/_sources/how_to/compile_models/from_darknet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
@@ -318,7 +318,7 @@ The process is no different from other examples.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 37.452 seconds)
+ **Total running time of the script:** ( 1 minutes 39.440 seconds)
.. _sphx_glr_download_how_to_compile_models_from_darknet.py:
diff --git a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
index 5999f708da..9ff1f4bd5b 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -116,7 +116,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipe673319f-f6c5-4687-9fb1-6095d9f9c68c from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip081dde5a-3ce8-4839-afb3-f0527d11d7df from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
diff --git a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
index 7a51cb5f57..165cacafa2 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -121,7 +121,7 @@ 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
-
0%| | 0.00/41.5M [00:00<?, ?B/s]
15%|#5 | 6.33M/41.5M [00:00<00:00, 52.9MB/s]
27%|##7 | 11.4M/41.5M [00:00<00:00, 41.5MB/s]
37%|###7 | 15.4M/41.5M [00:00<00:00, 27.7MB/s]
54%|#####3 | 22.3M/41.5M [00:00<00:00, 38.7MB/s]
64%|######4 | 26.7M/41.5M [00:00<00:00, 35.4MB/s]
77%|#######7 | 32.0M/41.5M [00:00<00:00, 39.4MB/s]
96%|#########6| 40.0M/41.5M [00:01<00:00, 49.1MB/s]
100%|##########| 41.5M/41.5M [00:01<00:00, 43.0MB/s]
+
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35%|###4 | 14.3M/41.5M [00:00<00:00, 28.6MB/s]
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58%|#####7 | 24.0M/41.5M [00:00<00:00, 29.4MB/s]
77%|#######7 | 32.0M/41.5M [00:01<00:00, 34.5MB/s]
85%|########4 | 35.2M/41.5M [00:01<00:00, 34.1MB/s]
93%|#########2| 38.4M/41.5M [00:01<00:00, 33.9MB/s]
100%|##########| 41.5M/41.5M [00:01<00:00, 28.7MB/s]
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 181d80078a..75f97b9f0c 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -209,7 +209,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 4.281 seconds)
+ **Total running time of the script:** ( 1 minutes 6.773 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 40727dd93a..8540507544 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -101,7 +101,7 @@ Load a pretrained PyTorch model
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
-
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47%|####6 | 20.8M/44.7M [00:00<00:00, 53.5MB/s]
59%|#####8 | 26.2M/44.7M [00:00<00:00, 45.8MB/s]
69%|######8 | 30.8M/44.7M [00:00<00:00, 35.2MB/s]
77%|#######7 | 34.5M/44.7M [00:00<00:00, 31.8MB/s]
90%|########9 | 40.0M/44.7M [00:01<00:00, 34.2MB/s]
97%|#########7| 43.4M/44.7M [00:01<00:00, 32.7MB/s]
100%|##########| 44.7M/44.7M [00:01<00:00, 38.2MB/s]
+
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100%|##########| 44.7M/44.7M [00:00<00:00, 59.2MB/s]
diff --git a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
index 48e7766c05..6624e55d24 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -430,7 +430,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 35.034 seconds)
+ **Total running time of the script:** ( 1 minutes 36.250 seconds)
.. _sphx_glr_download_how_to_compile_models_from_tensorflow.py:
diff --git a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
index 3bf9e974de..20ed0cb0f2 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
=================
-**07:26.549** total execution time for **how_to_compile_models** files:
+**07:38.638** total execution time for **how_to_compile_models** files:
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:37.452 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:39.440 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:35.034 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:36.250 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:04.281 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:06.773 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:43.461 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:45.184 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:39.331 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:40.569 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:35.292 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:36.089 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:29.295 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:29.966 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:27.227 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:29.091 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:12.201 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:12.296 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.975 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.982 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
index 2f0f161a5b..d3782d2e47 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
@@ -673,7 +673,7 @@ well as provides information about the model's performance
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 4120.8783 4119.6472 4130.9018 4118.2180 3.4969
+ 4128.3883 4125.5310 4150.8472 4124.1747 7.6155
@@ -681,7 +681,7 @@ well as provides information about the model's performance
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 19.693 seconds)
+ **Total running time of the script:** ( 1 minutes 21.545 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_model_on_adreno.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt
index 155c4d35ae..a700077f0b 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt
@@ -127,7 +127,7 @@ Make a Keras Resnet50 Model
.. code-block:: none
Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels.h5
-
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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 5167eed765..6654e32d49 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
@@ -437,7 +437,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.7448 16.9271 17.2100 15.9493 0.3913
+ 17.0997 17.2100 17.5490 16.2214 0.3977
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 d6aac48b55..eeeba581a0 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
@@ -130,7 +130,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=MaskRCNN_ResNet50_FPN_Weights.COCO_V1`. You can also use `weights=MaskRCNN_ResNet50_FPN_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
-
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]
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+
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s]
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/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/nn/functional.py:3912: 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).
(torch.floor((input.size(i + 2).float() * torch.tensor(scale_factors[i], dtype=torch.float32)).float()))
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/ops/boxes.py:157: 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).
@@ -292,7 +292,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 3 minutes 38.383 seconds)
+ **Total running time of the script:** ( 3 minutes 57.738 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 ed851ded07..094500f930 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -227,7 +227,7 @@ training. Other models require a full post training calibration.
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=MobileNet_V2_Weights.IMAGENET1K_V1`. You can also use `weights=MobileNet_V2_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
-
0%| | 0.00/13.6M [00:00<?, ?B/s]
47%|####6 | 6.30M/13.6M [00:00<00:00, 26.5MB/s]
65%|######5 | 8.84M/13.6M [00:00<00:00, 23.5MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 29.7MB/s]
+
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47%|####6 | 6.30M/13.6M [00:00<00:00, 63.5MB/s]
91%|#########1| 12.4M/13.6M [00:00<00:00, 40.2MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 46.0MB/s]
@@ -409,7 +409,7 @@ 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)
- 89.1363 89.0420 93.0028 88.8081 0.4420
+ 89.2267 89.1254 90.4185 88.9010 0.2800
@@ -457,7 +457,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 29.620 seconds)
+ **Total running time of the script:** ( 1 minutes 35.040 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 588ae136ee..661fc953d7 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
@@ -423,7 +423,7 @@ 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)
- 110.4182 110.4049 113.8229 109.6947 0.4790
+ 112.1531 112.0897 113.3706 111.4586 0.3977
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 68c20be833..2eb6a441c1 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -257,7 +257,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 58.022 seconds)
+ **Total running time of the script:** ( 2 minutes 27.236 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_quantized.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 df794bf48a..b95caf5341 100644
--- a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
@@ -5,26 +5,26 @@
Computation times
=================
-**11:58.297** total execution time for **how_to_deploy_models** files:
+**13:06.713** total execution time for **how_to_deploy_models** files:
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:38.383 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:57.738 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:58.022 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 02:27.236 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:29.620 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:35.040 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 01:19.693 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 01:21.545 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 00:52.932 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 00:54.908 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:51.538 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:54.647 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``) | 00:47.314 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``) | 00:51.210 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:30.568 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:32.455 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:30.221 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:31.928 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.007 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
index 3ea0f84af0..a865279dd6 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
@@ -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.zip5eea2627-759f-4fc8-89d8-d131d45bbf3e from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zipc9b40a5d-fd36-4694-b3e7-3757ecac6510 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
diff --git a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
index a6b6ac4ecd..2e0bd80a12 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
=================
-**00:59.595** total execution time for **how_to_extend_tvm** files:
+**01:03.038** 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``) | 00:55.503 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:58.708 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.865 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:03.042 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.218 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.281 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``) | 00:00.008 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt b/docs/_sources/how_to/extend_tvm/use_pass_instrument.rst.txt
index 2e45b4e2b6..7aeb5618a5 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
@@ -220,10 +220,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 25286us [25286us] (48.62%; 48.62%)
- FoldScaleAxis: 26722us [8us] (51.38%; 51.38%)
- FoldConstant: 26714us [1818us] (51.37%; 99.97%)
- InferType: 24897us [24897us] (47.87%; 93.20%)
+ InferType: 26080us [26080us] (48.43%; 48.43%)
+ FoldScaleAxis: 27772us [10us] (51.57%; 51.57%)
+ FoldConstant: 27762us [1914us] (51.55%; 99.96%)
+ InferType: 25848us [25848us] (48.00%; 93.10%)
@@ -262,10 +262,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 25148us [25148us] (48.26%; 48.26%)
- FoldScaleAxis: 26960us [8us] (51.74%; 51.74%)
- FoldConstant: 26952us [1925us] (51.72%; 99.97%)
- InferType: 25027us [25027us] (48.03%; 92.86%)
+ InferType: 26044us [26044us] (48.37%; 48.37%)
+ FoldScaleAxis: 27798us [10us] (51.63%; 51.63%)
+ FoldConstant: 27788us [1955us] (51.61%; 99.96%)
+ InferType: 25832us [25832us] (47.98%; 92.96%)
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 82310b0af2..7dc191dad0 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
@@ -331,7 +331,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 53.581600 ms
+ Convolution: 52.110080 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 12abf6ed1e..5249757922 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
@@ -598,7 +598,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 12.266588 ms
+ conv2d with tensor core: 11.292902 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 313bcd6c7d..15dabcb676 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -134,8 +134,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.018203
- Baseline: 3.394873
+ Numpy running time: 0.019308
+ Baseline: 3.694823
@@ -227,7 +227,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.297073
+ Opt1: 0.328926
@@ -318,7 +318,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.282980
+ Opt2: 0.329192
@@ -406,7 +406,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.114630
+ Opt3: 0.141160
@@ -523,7 +523,7 @@ flattening.
.. code-block:: none
- Opt4: 0.107914
+ Opt4: 0.111365
@@ -635,7 +635,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.112693
+ Opt5: 0.115196
@@ -748,7 +748,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
.. code-block:: none
- Opt6: 0.132949
+ Opt6: 0.136598
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 cfcdb80e87..9c7cdcc9fa 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
=================
-**00:34.050** total execution time for **how_to_optimize_operators** files:
+**00:36.717** total execution time for **how_to_optimize_operators** files:
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:30.890 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:33.425 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.933 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:02.066 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.227 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.226 | 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 ad74356216..b32ac3d6e0 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
=================
-**03:39.512** total execution time for **how_to_tune_with_autoscheduler** files:
+**03:49.952** total execution time for **how_to_tune_with_autoscheduler** files:
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:35.153 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:39.358 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:13.282 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:16.809 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:18.135 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:19.314 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:16.706 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:17.570 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:16.135 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:16.796 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:00.102 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:00.104 | 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 e4320ab4cc..a9a2691449 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
@@ -766,7 +766,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.337 ms
+ Execution time of this operator: 0.331 ms
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 5c1e2e2c27..620dcbac38 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
@@ -647,7 +647,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 3.1987 3.1983 3.1996 3.1981 0.0007
+ 3.2059 3.2060 3.2065 3.2053 0.0005
@@ -674,7 +674,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 13.282 seconds)
+ **Total running time of the script:** ( 1 minutes 16.809 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_cuda.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_network_x86.rst.txt
index bbf3441d66..4eb24dbd12 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
@@ -666,7 +666,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 767.3287 767.4479 768.3663 766.1720 0.8998
+ 764.8503 764.1512 768.0400 762.3597 2.3711
@@ -693,7 +693,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 35.153 seconds)
+ **Total running time of the script:** ( 1 minutes 39.358 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_x86.py:
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 06b4d99485..5778d5fd4f 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
@@ -5,16 +5,16 @@
Computation times
=================
-**00:23.584** total execution time for **how_to_tune_with_autotvm** files:
+**00:23.787** 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``) | 00:23.545 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:23.747 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``) | 00:00.023 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``) | 00:00.006 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``) | 00:00.005 | 0.0 MB |
-+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``) | 00:00.005 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.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 865f970467..41aa684890 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
@@ -326,7 +326,7 @@ and measure running time.
Best config:
,None
- Time cost of this operator: 0.036982
+ Time cost of this operator: 0.037159
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 3c242d1a9a..97bdf55ac4 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
@@ -360,10 +360,10 @@ Timing the untuned program
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 296.2 98.721 (1, 2, 10, 10, 3) 2 1 [296.2]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.869 0.956 (1, 6, 10, 10) 1 1 [2.869]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.97 0.323 (1, 1, 10, 10, 3) 1 1 [0.97]
- Total_time - 300.039 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 306.7 98.702 (1, 2, 10, 10, 3) 2 1 [306.7]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.046 0.98 (1, 6, 10, 10) 1 1 [3.046]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.986 0.317 (1, 1, 10, 10, 3) 1 1 [0.986]
+ Total_time - 310.733 - - - - -
@@ -428,10 +428,10 @@ Timing the tuned program
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 137.5 98.127 (1, 6, 10, 10, 1) 2 1 [137.5]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.772 1.264 (1, 6, 10, 10) 1 1 [1.772]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.853 0.609 (1, 3, 10, 10, 1) 1 1 [0.853]
- Total_time - 140.125 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 102.8 97.51 (1, 6, 10, 10, 1) 2 1 [102.8]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.778 1.687 (1, 6, 10, 10) 1 1 [1.778]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.847 0.804 (1, 3, 10, 10, 1) 1 1 [0.847]
+ Total_time - 105.426 - - - - -
@@ -439,7 +439,7 @@ Timing the tuned program
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 16.028 seconds)
+ **Total running time of the script:** ( 1 minutes 23.124 seconds)
.. _sphx_glr_download_how_to_work_with_microtvm_micro_autotune.py:
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
index 36600f7d50..56cea0fc91 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
@@ -118,7 +118,7 @@ download a cat image and preprocess it to use as the model input.
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/ao/quantization/utils.py:310: UserWarning: must run observer before calling calculate_qparams. Returning default values.
warnings.warn(
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
-
0%| | 0.00/3.42M [00:00<?, ?B/s]
61%|###### | 2.09M/3.42M [00:00<00:00, 20.5MB/s]
100%|##########| 3.42M/3.42M [00:00<00:00, 32.0MB/s]
+
0%| | 0.00/3.42M [00:00<?, ?B/s]
61%|###### | 2.09M/3.42M [00:00<00:00, 10.9MB/s]
100%|##########| 3.42M/3.42M [00:00<00:00, 17.4MB/s]
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/_utils.py:314: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
device=storage.device,
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -326,7 +326,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 29.556 seconds)
+ **Total running time of the script:** ( 1 minutes 34.973 seconds)
.. _sphx_glr_download_how_to_work_with_microtvm_micro_pytorch.py:
diff --git a/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt b/docs/_sources/how_to/work_with_microtvm/micro_train.rst.txt
index 0e4d0ffaf6..d72fdd4cb8 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
@@ -217,7 +217,7 @@ take about **2 minutes** to download the Stanford Cars, while COCO 2017 validati
.. code-block:: none
- '/tmp/tmpffy6a3q5/images/random'
+ '/tmp/tmp7jf5j3my/images/random'
@@ -317,8 +317,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. code-block:: none
- /tmp/tmpffy6a3q5/images/target contains 8144 images
- /tmp/tmpffy6a3q5/images/random contains 5000 images
+ /tmp/tmp7jf5j3my/images/target contains 8144 images
+ /tmp/tmp7jf5j3my/images/random contains 5000 images
@@ -493,13 +493,13 @@ the time on our validation set).
.. code-block:: none
Epoch 1/3
- 328/328 - 41s - loss: 0.2275 - accuracy: 0.9235 - val_loss: 0.1142 - val_accuracy: 0.9585 - 41s/epoch - 124ms/step
+ 328/328 - 41s - loss: 0.2210 - accuracy: 0.9263 - val_loss: 0.1023 - val_accuracy: 0.9660 - 41s/epoch - 124ms/step
Epoch 2/3
- 328/328 - 36s - loss: 0.1003 - accuracy: 0.9633 - val_loss: 0.0946 - val_accuracy: 0.9671 - 36s/epoch - 109ms/step
+ 328/328 - 36s - loss: 0.0988 - accuracy: 0.9622 - val_loss: 0.0839 - val_accuracy: 0.9705 - 36s/epoch - 111ms/step
Epoch 3/3
- 328/328 - 35s - loss: 0.0646 - accuracy: 0.9748 - val_loss: 0.1023 - val_accuracy: 0.9671 - 35s/epoch - 107ms/step
+ 328/328 - 36s - loss: 0.0674 - accuracy: 0.9744 - val_loss: 0.0828 - val_accuracy: 0.9705 - 36s/epoch - 110ms/step
- <keras.callbacks.History object at 0x7f1537f78700>
+ <keras.callbacks.History object at 0x7f7536057610>
@@ -860,7 +860,7 @@ Arduino tutorial for how to do that `on GitHub <https://github.com/guberti/tvm-a
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 4 minutes 39.678 seconds)
+ **Total running time of the script:** ( 4 minutes 51.144 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 c8c276e24d..497afbd497 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
@@ -5,20 +5,20 @@
Computation times
=================
-**07:54.913** total execution time for **how_to_work_with_microtvm** files:
+**08:20.043** total execution time for **how_to_work_with_microtvm** files:
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:39.678 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:51.144 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:29.556 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:34.973 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 01:16.028 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 01:23.124 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:11.573 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:12.354 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:09.083 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:09.541 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:08.995 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:08.908 | 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 40a781dfd9..29f49eec7b 100644
--- a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
Computation times
=================
-**00:39.026** total execution time for **how_to_work_with_relay** files:
+**00:41.586** total execution time for **how_to_work_with_relay** files:
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:33.861 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:36.085 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:03.195 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:03.325 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.965 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:02.169 | 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 |
+| :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``) | 00:00.007 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
index 9efedd4b59..5461e59899 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
@@ -281,7 +281,7 @@ The following example customizes CUDA lowering rule for :code:`exp`.
.. code-block:: none
- <function my_cuda_math_rule at 0x7f1734111c10>
+ <function my_cuda_math_rule at 0x7f771bb13f70>
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 4ed933a033..cb07df9a5f 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
=================
-**00:05.864** total execution time for **how_to_work_with_schedules** files:
+**00:05.883** total execution time for **how_to_work_with_schedules** files:
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:02.657 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:02.730 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.443 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.311 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.743 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.776 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.737 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.759 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.117 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.124 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.069 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.078 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.065 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.071 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.032 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.033 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
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 c064544297..d807396963 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
=================
-**00:36.336** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:38.172** total execution time for **topic_vta_tutorials_autotvm** files:
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:36.328 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:38.164 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``) | 00:00.008 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
index 7a6486e673..3329c838ae 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -293,7 +293,7 @@ The compilation steps are:
warnings.warn(
/workspace/vta/tutorials/frontend/deploy_classification.py:212: 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.
graph, lib, params = relay.build(
- resnet18_v1 inference graph built in 38.34s!
+ resnet18_v1 inference graph built in 40.96s!
@@ -414,6 +414,11 @@ and an input test image.
+.. rst-class:: sphx-glr-timing
+
+ **Total running time of the script:** ( 1 minutes 2.076 seconds)
+
+
.. _sphx_glr_download_topic_vta_tutorials_frontend_deploy_classification.py:
.. only:: html
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 8886dd329d..0e5fa4a8be 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -337,7 +337,7 @@ The compilation steps are:
/workspace/python/tvm/relay/build_module.py:345: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
warnings.warn(
- yolov3-tiny inference graph built in 26.14s!
+ yolov3-tiny inference graph built in 27.86s!
@@ -445,6 +445,11 @@ Download test image
+.. rst-class:: sphx-glr-timing
+
+ **Total running time of the script:** ( 1 minutes 2.192 seconds)
+
+
.. _sphx_glr_download_topic_vta_tutorials_frontend_deploy_detection.py:
.. only:: html
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 a4ed7692b6..0fbf0ea744 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
=================
-**01:59.207** total execution time for **topic_vta_tutorials_frontend** files:
+**02:04.268** total execution time for **topic_vta_tutorials_frontend** files:
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:59.840 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 01:02.192 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:59.367 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 01:02.076 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/optimize/sg_execution_times.rst.txt
index 6f54af6491..6311f0dfc7 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
=================
-**00:03.387** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.445** total execution time for **topic_vta_tutorials_optimize** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.847 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.903 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.540 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.542 | 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 a4d82e2f53..f899006a0c 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
=================
-**00:00.885** total execution time for **topic_vta_tutorials** files:
+**00:00.890** total execution time for **topic_vta_tutorials** files:
+---------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.457 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.428 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.432 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index 7c14c3cfdd..fb1c6a05e5 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -211,8 +211,8 @@ trials, we can load the best schedule from the log file and apply it.
.. code-block:: none
- *E
+ *E
@@ -325,7 +325,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 97.585 ms
+ Execution time of this operator: 95.797 ms
@@ -441,7 +441,7 @@ operations.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 34.065 seconds)
+ **Total running time of the script:** ( 1 minutes 34.526 seconds)
.. _sphx_glr_download_tutorial_auto_scheduler_matmul_x86.py:
diff --git a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
index 59c71e1002..3dbddfe942 100644
--- a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
@@ -454,16 +454,16 @@ reduce variance, we take 5 measurements and average them.
waiting for device...
device available
Get devices for measurement successfully!
- No: 1 GFLOPS: 14.10/14.10 result: MeasureResult(costs=(0.0190400884,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.580122709274292, timestamp=1706130149.3779674) [('tile_y', [-1, 16]), ('tile_x', [-1, 32])],None,54
- No: 2 GFLOPS: 11.94/14.10 result: MeasureResult(costs=(0.022479538,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6436622142791748, timestamp=1706130149.9956682) [('tile_y', [-1, 16]), ('tile_x', [-1, 16])],None,44
- No: 3 GFLOPS: 0.50/14.10 result: MeasureResult(costs=(0.5322868688,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.790831089019775, timestamp=1706130158.769511) [('tile_y', [-1, 64]), ('tile_x', [-1, 1])],None,6
- No: 4 GFLOPS: 10.39/14.10 result: MeasureResult(costs=(0.0258306808,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6614129543304443, timestamp=1706130159.4383698) [('tile_y', [-1, 2]), ('tile_x', [-1, 32])],None,51
- No: 5 GFLOPS: 12.19/14.10 result: MeasureResult(costs=(0.022020926399999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6428756713867188, timestamp=1706130160.20137) [('tile_y', [-1, 16]), ('tile_x', [-1, 512])],None,94
- No: 6 GFLOPS: 0.51/14.10 result: MeasureResult(costs=(0.5267534702,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.69219446182251, timestamp=1706130168.885319) [('tile_y', [-1, 128]), ('tile_x', [-1, 1])],None,7
- No: 7 GFLOPS: 2.03/14.10 result: MeasureResult(costs=(0.13219608639999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.375584840774536, timestamp=1706130171.2571223) [('tile_y', [-1, 256]), ('tile_x', [-1, 4])],None,28
- No: 8 GFLOPS: 10.57/14.10 result: MeasureResult(costs=(0.0254025296,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.672905445098877, timestamp=1706130171.9207823) [('tile_y', [-1, 4]), ('tile_x', [-1, 16])],None,42
- No: 9 GFLOPS: 7.08/14.10 result: MeasureResult(costs=(0.037902027,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8327691555023193, timestamp=1706130172.897419) [('tile_y', [-1, 512]), ('tile_x', [-1, 16])],None,49
- No: 10 GFLOPS: 10.59/14.10 result: MeasureResult(costs=(0.0253424534,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6769700050354004, timestamp=1706130173.5764592) [('tile_y', [-1, 512]), ('tile_x', [-1, 128])],None,79
+ No: 1 GFLOPS: 6.56/6.56 result: MeasureResult(costs=(0.0409415574,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.9388835430145264, timestamp=1706133341.0289698) [('tile_y', [-1, 512]), ('tile_x', [-1, 16])],None,49
+ No: 2 GFLOPS: 10.19/10.19 result: MeasureResult(costs=(0.0263439514,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6993741989135742, timestamp=1706133341.7222872) [('tile_y', [-1, 256]), ('tile_x', [-1, 256])],None,88
+ No: 3 GFLOPS: 4.17/10.19 result: MeasureResult(costs=(0.0643350868,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.2908637523651123, timestamp=1706133343.0160563) [('tile_y', [-1, 8]), ('tile_x', [-1, 2])],None,13
+ No: 4 GFLOPS: 0.50/10.19 result: MeasureResult(costs=(0.5337769556,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.848292589187622, timestamp=1706133351.8224938) [('tile_y', [-1, 64]), ('tile_x', [-1, 1])],None,6
+ No: 5 GFLOPS: 7.33/10.19 result: MeasureResult(costs=(0.0366167326,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8683803081512451, timestamp=1706133352.8719246) [('tile_y', [-1, 32]), ('tile_x', [-1, 16])],None,45
+ No: 6 GFLOPS: 9.59/10.19 result: MeasureResult(costs=(0.027996526799999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7172234058380127, timestamp=1706133353.5950336) [('tile_y', [-1, 512]), ('tile_x', [-1, 512])],None,99
+ No: 7 GFLOPS: 11.55/11.55 result: MeasureResult(costs=(0.023241088,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7203757762908936, timestamp=1706133354.237779) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
+ No: 8 GFLOPS: 11.04/11.55 result: MeasureResult(costs=(0.0243240294,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6621172428131104, timestamp=1706133354.9001226) [('tile_y', [-1, 4]), ('tile_x', [-1, 512])],None,92
+ No: 9 GFLOPS: 11.52/11.55 result: MeasureResult(costs=(0.0233106398,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6365814208984375, timestamp=1706133355.6678193) [('tile_y', [-1, 16]), ('tile_x', [-1, 512])],None,94
+ No: 10 GFLOPS: 10.38/11.55 result: MeasureResult(costs=(0.0258532104,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6926472187042236, timestamp=1706133356.3468945) [('tile_y', [-1, 8]), ('tile_x', [-1, 64])],None,63
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 0c45f87e18..fa1a20f571 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -311,7 +311,7 @@ standard deviation.
.. code-block:: none
- {'mean': 494.9741758199889, 'median': 495.114422450024, 'std': 1.1117048733914823}
+ {'mean': 500.58081771001525, 'median': 500.23290955004995, 'std': 1.5838218019673596}
@@ -582,30 +582,31 @@ the tuning data to.
.. code-block:: none
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 15.26/ 15.34 GFLOPS | Progress: (4/20) | 8.54 s
[Task 1/25] Current/Best: 8.85/ 22.41 GFLOPS | Progress: (8/20) | 11.99 s
[Task 1/25] Current/Best: 18.81/ 22.42 GFLOPS | Progress: (12/20) | 14.88 s
[Task 1/25] Current/Best: 7.65/ 22.42 GFLOPS | Progress: (16/20) | 18.27 s
[Task 1/25] Current/Best: 14.50/ 23.43 GFLOPS | Progress: (20/20) | 20.58 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 17.84/ 22.44 GFLOPS | Progress: (4/20) | 3.90 s
[Task 2/25] Current/Best: 17.13/ 22.44 GFLOPS | Progress: (8/20) | 5.56 s
[Task 2/25] Current/Best: 19.46/ 22.44 GFLOPS | Progress: (12/20) | 7.32 s
[Task 2/25] Current/Best: 14.08/ 22.44 GFLOPS | Progress: (16/20) | 8.94 s
[Task 2/25] Current/Best: 6.68/ 22.44 GFLOPS | Progress: (20/20) | 10.40 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 20.68/ 20.68 GFLOPS | Progress: (4/20) | 4.66 s
[Task 3/25] Current/Best: 15.27/ 23.60 GFLOPS | Progress: (8/20) | 6.70 s
[Task 3/25] Current/Best: 14.72/ 23.60 GFLOPS | Progress: (12/20) | 9.37 s
[Task 3/25] Current/Best: 19.77/ 23.60 GFLOPS | Progress: (16/20) | 11.34 s
[Task 3/25] Current/Best: 10.73/ 23.60 GFLOPS | Progress: (20/20) | 13.66 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 18.42/ 21.78 GFLOPS | Progress: (4/20) | 4.55 s
[Task 4/25] Current/Best: 23.77/ 23.77 GFLOPS | Progress: (8/20) | 7.47 s
[Task 4/25] Current/Best: 17.35/ 23.77 GFLOPS | Progress: (12/20) | 12.74 s
[Task 4/25] Current/Best: 17.67/ 23.77 GFLOPS | Progress: (16/20) | 15.60 s
[Task 4/25] Current/Best: 13.88/ 23.77 GFLOPS | Progress: (20/20) | 18.33 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 3.35/ 16.27 GFLOPS | Progress: (4/20) | 4.58 s
[Task 5/25] Current/Best: 6.02/ 18.50 GFLOPS | Progress: (8/20) | 6.33 s
[Task 5/25] Current/Best: 5.17/ 21.51 GFLOPS | Progress: (12/20) | 8.20 s
[Task 5/25] Current/Best: 15.40/ 21.51 GFLOPS | Progress: (16/20) | 9.90 s
[Task 5/25] Current/Best: 13.38/ 21.51 GFLOPS | Progress: (20/20) | 12.03 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 6.36/ 13.09 GFLOPS | Progress: (4/20) | 5.20 s
[Task 6/25] Current/Best: 4.07/ 18.16 GFLOPS | Progress: (8/20) | 8.24 s
[Task 6/25] Current/Best: 21.58/ 21.58 GFLOPS | Progress: (12/20) | 10.49 s
[Task 6/25] Current/Best: 8.68/ 21.58 GFLOPS | Progress: (16/20) | 13.30 s
[Task 6/25] Current/Best: 7.99/ 21.58 GFLOPS | Progress: (20/20) | 15.62 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 8.82/ 19.03 GFLOPS | Progress: (4/20) | 5.79 s
[Task 7/25] Current/Best: 19.13/ 19.46 GFLOPS | Progress: (8/20) | 8.19 s
[Task 7/25] Current/Best: 5.08/ 19.81 GFLOPS | Progress: (12/20) | 10.68 s
[Task 7/25] Current/Best: 14.31/ 20.61 GFLOPS | Progress: (16/20) | 13.27 s
[Task 7/25] Current/Best: 9.17/ 21.24 GFLOPS | Progress: (20/20) | 15.45 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 12.12/ 17.01 GFLOPS | Progress: (4/20) | 5.46 s
[Task 8/25] Current/Best: 6.64/ 17.01 GFLOPS | Progress: (8/20) | 12.46 s
[Task 8/25] Current/Best: 4.25/ 17.01 GFLOPS | Progress: (12/20) | 24.25 s
[Task 8/25] Current/Best: 10.60/ 17.01 GFLOPS | Progress: (16/20) | 27.51 s
[Task 8/25] Current/Best: 5.22/ 17.55 GFLOPS | Progress: (20/20) | 30.02 s Done.
-
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 7.56/ 16.45 GFLOPS | Progress: (4/20) | 10.60 s
[Task 9/25] Current/Best: 11.54/ 18.14 GFLOPS | Progress: (8/20) | 12.33 s
[Task 9/25] Current/Best: 11.97/ 18.14 GFLOPS | Progress: (12/20) | 19.85 s
[Task 9/25] Current/Best: 17.41/ 18.14 GFLOPS | Progress: (16/20) | 21.55 s
[Task 9/25] Current/Best: 16.36/ 19.84 GFLOPS | Progress: (20/20) | 24.72 s Done.
-
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 14.65/ 20.59 GFLOPS | Progress: (4/20) | 4.38 s
[Task 10/25] Current/Best: 5.27/ 20.59 GFLOPS | Progress: (8/20) | 6.27 s
[Task 10/25] Current/Best: 8.23/ 20.59 GFLOPS | Progress: (12/20) | 8.19 s
[Task 10/25] Current/Best: 17.69/ 20.59 GFLOPS | Progress: (16/20) | 11.94 s
[Task 10/25] Current/Best: 14.35/ 20.59 GFLOPS | Progress: (20/20) | 14.34 s Done.
-
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 8.27/ 23.46 GFLOPS | Progress: (4/20) | 4.44 s
[Task 11/25] Current/Best: 9.91/ 23.46 GFLOPS | Progress: (8/20) | 7.16 s
[Task 11/25] Current/Best: 9.17/ 23.46 GFLOPS | Progress: (12/20) | 9.43 s
[Task 11/25] Current/Best: 12.04/ 23.46 GFLOPS | Progress: (16/20) | 12.31 s
[Task 11/25] Current/Best: 8.71/ 23.46 GFLOPS | Progress: (20/20) | 16.46 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 14.49/ 19.87 GFLOPS | Progress: (4/20) | 5.86 s
[Task 12/25] Current/Best: 12.54/ 19.87 GFLOPS | Progress: (8/20) | 8.48 s
[Task 12/25] Current/Best: 6.02/ 19.87 GFLOPS | Progress: (12/20) | 11.16 s
[Task 12/25] Current/Best: 19.19/ 19.87 GFLOPS | Progress: (16/20) | 16.11 s
[Task 12/25] Current/Best: 15.97/ 19.87 GFLOPS | Progress: (20/20) | 18.86 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 12.15/ 12.23 GFLOPS | Progress: (4/20) | 5.51 s
[Task 13/25] Current/Best: 9.22/ 16.95 GFLOPS | Progress: (8/20) | 8.11 s
[Task 13/25] Current/Best: 12.26/ 17.65 GFLOPS | Progress: (12/20) | 11.88 s
[Task 13/25] Current/Best: 12.40/ 18.60 GFLOPS | Progress: (16/20) | 15.14 s
[Task 13/25] Current/Best: 12.32/ 18.60 GFLOPS | Progress: (20/20) | 17.86 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 11.52/ 14.25 GFLOPS | Progress: (4/20) | 8.27 s
[Task 14/25] Current/Best: 12.18/ 17.56 GFLOPS | Progress: (8/20) | 11.53 s
[Task 14/25] Current/Best: 11.10/ 17.56 GFLOPS | Progress: (12/20) | 18.63 s
[Task 14/25] Current/Best: 14.06/ 17.56 GFLOPS | Progress: (16/20) | 25.00 s
[Task 14/25] Current/Best: 21.69/ 21.69 GFLOPS | Progress: (20/20) | 27.61 s Done.
-
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 3.15/ 17.95 GFLOPS | Progress: (4/20) | 9.49 s
[Task 15/25] Current/Best: 14.34/ 23.94 GFLOPS | Progress: (8/20) | 11.63 s
[Task 15/25] Current/Best: 17.46/ 23.94 GFLOPS | Progress: (12/20) | 13.26 s
[Task 15/25] Current/Best: 7.08/ 23.94 GFLOPS | Progress: (16/20) | 18.85 s
[Task 15/25] Current/Best: 10.52/ 23.94 GFLOPS | Progress: (20/20) | 21.23 s Done.
-
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 18.07/ 19.33 GFLOPS | Progress: (4/20) | 5.78 s
[Task 16/25] Current/Best: 13.32/ 19.33 GFLOPS | Progress: (8/20) | 7.95 s
[Task 16/25] Current/Best: 6.25/ 22.22 GFLOPS | Progress: (12/20) | 9.67 s
[Task 16/25] Current/Best: 14.81/ 22.22 GFLOPS | Progress: (16/20) | 11.90 s
[Task 16/25] Current/Best: 3.08/ 22.22 GFLOPS | Progress: (20/20) | 14.34 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 9.74/ 23.04 GFLOPS | Progress: (4/20) | 5.23 s
[Task 17/25] Current/Best: 21.72/ 23.04 GFLOPS | Progress: (8/20) | 7.12 s
[Task 17/25] Current/Best: 19.59/ 23.04 GFLOPS | Progress: (12/20) | 9.63 s
[Task 17/25] Current/Best: 1.56/ 23.04 GFLOPS | Progress: (16/20) | 14.19 s
[Task 17/25] Current/Best: 9.11/ 23.04 GFLOPS | Progress: (20/20) | 18.24 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 16.74/ 18.83 GFLOPS | Progress: (4/20) | 8.35 s
[Task 18/25] Current/Best: 18.64/ 18.83 GFLOPS | Progress: (8/20) | 10.23 s
[Task 18/25] Current/Best: 14.29/ 18.83 GFLOPS | Progress: (12/20) | 13.01 s
[Task 18/25] Current/Best: 11.09/ 18.83 GFLOPS | Progress: (16/20) | 17.31 s
[Task 18/25] Current/Best: 16.55/ 18.83 GFLOPS | Progress: (20/20) | 19.30 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 20.61/ 20.61 GFLOPS | Progress: (4/20) | 5.43 s
[Task 19/25] Current/Best: 17.77/ 20.61 GFLOPS | Progress: (8/20) | 8.76 s
[Task 19/25] Current/Best: 7.27/ 21.53 GFLOPS | Progress: (12/20) | 12.45 s
[Task 19/25] Current/Best: 6.92/ 21.53 GFLOPS | Progress: (16/20) | 18.68 s
[Task 19/25] Current/Best: 8.66/ 21.53 GFLOPS | Progress: (20/20) | 21.73 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 11.06/ 11.43 GFLOPS | Progress: (4/20) | 6.55 s
[Task 20/25] Current/Best: 5.62/ 20.17 GFLOPS | Progress: (8/20) | 13.12 s
[Task 20/25] Current/Best: 11.98/ 20.17 GFLOPS | Progress: (12/20) | 16.42 s
[Task 20/25] Current/Best: 9.60/ 20.17 GFLOPS | Progress: (16/20) | 27.98 s
[Task 20/25] Current/Best: 2.69/ 20.17 GFLOPS | Progress: (20/20) | 41.05 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 8.11/ 14.25 GFLOPS | Progress: (4/20) | 6.04 s
[Task 21/25] Current/Best: 6.37/ 18.58 GFLOPS | Progress: (8/20) | 7.72 s
[Task 21/25] Current/Best: 14.74/ 18.78 GFLOPS | Progress: (12/20) | 9.51 s
[Task 21/25] Current/Best: 9.43/ 18.78 GFLOPS | Progress: (16/20) | 20.59 s
[Task 21/25] Current/Best: 7.35/ 19.45 GFLOPS | Progress: (20/20
) | 31.41 s Done.
-
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 20.56/ 20.56 GFLOPS | Progress: (4/20) | 4.62 s
[Task 22/25] Current/Best: 12.99/ 20.56 GFLOPS | Progress: (8/20) | 6.56 s
[Task 22/25] Current/Best: 18.53/ 20.56 GFLOPS | Progress: (12/20) | 8.61 s
[Task 22/25] Current/Best: 9.09/ 20.56 GFLOPS | Progress: (16/20) | 14.15 s
[Task 22/25] Current/Best: 2.68/ 20.56 GFLOPS | Progress: (20/20) | 16.65 s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 10.61/ 18.41 GFLOPS | Progress: (4/20) | 6.30 s
[Task 23/25] Current/Best: 21.60/ 21.95 GFLOPS | Progress: (8/20) | 8.53 s
[Task 23/25] Current/Best: 9.70/ 21.95 GFLOPS | Progress: (12/20) | 14.51 s
[Task 23/25] Current/Best: 9.44/ 23.52 GFLOPS | Progress: (16/20) | 17.09 s
[Task 23/25] Current/Best: 18.54/ 23.52 GFLOPS | Progress: (20/20) | 20.27 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 2.97/ 9.71 GFLOPS | Progress: (4/20) | 8.85 s
[Task 24/25] Current/Best: 2.41/ 9.71 GFLOPS | Progress: (8/20) | 15.14 s
[Task 24/25] Current/Best: 1.89/ 9.71 GFLOPS | Progress: (12/20) | 21.21 s
[Task 24/25] Current/Best: 4.71/ 9.71 GFLOPS | Progress: (16/20) | 26.66 s Done.
-
[Task 24/25] Current/Best: 1.25/ 9.71 GFLOPS | Progress: (20/20) | 37.67 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 9.04/ 9.04 GFLOPS | Progress: (4/20) | 5.03 s
[Task 25/25] Current/Best: 2.81/ 9.04 GFLOPS | Progress: (8/20) | 7.90 s
[Task 25/25] Current/Best: 4.07/ 9.04 GFLOPS | Progress: (12/20) | 11.28 s
[Task 25/25] Current/Best: 5.69/ 9.04 GFLOPS | Progress: (16/20) | 22.24 s
[Task 25/25] Current/Best: 1.55/ 9.04 GFLOPS | Progress: (20/20) | 24.76 s
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 13.75/ 17.07 GFLOPS | Progress: (4/20) | 8.90 s
[Task 1/25] Current/Best: 20.87/ 23.99 GFLOPS | Progress: (8/20) | 11.51 s
[Task 1/25] Current/Best: 5.45/ 23.99 GFLOPS | Progress: (12/20) | 15.29 s
[Task 1/25] Current/Best: 16.01/ 23.99 GFLOPS | Progress: (16/20) | 17.35 s
[Task 1/25] Current/Best: 3.41/ 23.99 GFLOPS | Progress: (20/20) | 26.23 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 13.02/ 13.02 GFLOPS | Progress: (4/20) | 4.34 s
[Task 2/25] Current/Best: 2.14/ 17.98 GFLOPS | Progress: (8/20) | 5.87 s
[Task 2/25] Current/Best: 7.67/ 17.98 GFLOPS | Progress: (12/20) | 7.88 s
[Task 2/25] Current/Best: 7.65/ 17.98 GFLOPS | Progress: (16/20) | 9.40 s
[Task 2/25] Current/Best: 15.07/ 17.98 GFLOPS | Progress: (20/20) | 12.27 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 9.96/ 21.91 GFLOPS | Progress: (4/20) | 4.87 s
[Task 3/25] Current/Best: 6.81/ 21.91 GFLOPS | Progress: (8/20) | 7.77 s
[Task 3/25] Current/Best: 19.15/ 21.91 GFLOPS | Progress: (12/20) | 10.05 s
[Task 3/25] Current/Best: 23.71/ 23.71 GFLOPS | Progress: (16/20) | 12.40 s
[Task 3/25] Current/Best: 23.02/ 23.71 GFLOPS | Progress: (20/20) | 14.68 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 14.05/ 18.35 GFLOPS | Progress: (4/20) | 4.44 s
[Task 4/25] Current/Best: 5.23/ 18.35 GFLOPS | Progress: (8/20) | 6.61 s
[Task 4/25] Current/Best: 16.58/ 18.35 GFLOPS | Progress: (12/20) | 8.59 s
[Task 4/25] Current/Best: 10.58/ 20.44 GFLOPS | Progress: (16/20) | 13.73 s
[Task 4/25] Current/Best: 13.74/ 20.44 GFLOPS | Progress: (20/20) | 19.03 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 5.47/ 13.39 GFLOPS | Progress: (4/20) | 4.74 s
[Task 5/25] Current/Best: 3.65/ 14.05 GFLOPS | Progress: (8/20) | 7.11 s
[Task 5/25] Current/Best: 19.26/ 19.89 GFLOPS | Progress: (12/20) | 9.19 s
[Task 5/25] Current/Best: 17.43/ 19.89 GFLOPS | Progress: (16/20) | 11.60 s
[Task 5/25] Current/Best: 14.85/ 19.89 GFLOPS | Progress: (20/20) | 13.50 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 8.41/ 12.74 GFLOPS | Progress: (4/20) | 6.38 s
[Task 6/25] Current/Best: 10.36/ 16.74 GFLOPS | Progress: (8/20) | 9.05 s
[Task 6/25] Current/Best: 11.92/ 16.74 GFLOPS | Progress: (12/20) | 12.43 s
[Task 6/25] Current/Best: 7.61/ 16.74 GFLOPS | Progress: (16/20) | 15.23 s
[Task 6/25] Current/Best: 13.21/ 20.13 GFLOPS | Progress: (20/20) | 17.95 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 18.64/ 18.64 GFLOPS | Progress: (4/20) | 4.92 s
[Task 7/25] Current/Best: 14.86/ 18.64 GFLOPS | Progress: (8/20) | 7.79 s
[Task 7/25] Current/Best: 11.98/ 18.64 GFLOPS | Progress: (12/20) | 10.19 s
[Task 7/25] Current/Best: 7.63/ 18.80 GFLOPS | Progress: (16/20) | 12.88 s
[Task 7/25] Current/Best: 21.08/ 21.08 GFLOPS | Progress: (20/20) | 15.67 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 8.57/ 11.98 GFLOPS | Progress: (4/20) | 6.05 s
[Task 8/25] Current/Best: 8.32/ 13.07 GFLOPS | Progress: (8/20) | 9.49 s
[Task 8/25] Current/Best: 10.40/ 13.45 GFLOPS | Progress: (12/20) | 13.03 s
[Task 8/25] Current/Best: 12.63/ 16.17 GFLOPS | Progress: (16/20) | 16.67 s
[Task 8/25] Current/Best: 5.97/ 16.17 GFLOPS | Progress: (20/20) | 24.67 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 10.03/ 21.53 GFLOPS | Progress: (4/20) | 6.21 s
[Task 9/25] Current/Best: 12.19/ 21.53 GFLOPS | Progress: (8/20) | 11.47 s
[Task 9/25] Current/Best: 18.77/ 21.53 GFLOPS | Progress: (12/20) | 14.33 s
[Task 9/25] Current/Best: 8.40/ 21.53 GFLOPS | Progress: (16/20) | 17.08 s
[Task 9/25] Current/Best: 8.87/ 21.53 GFLOPS | Progress: (20/20) | 22.87 s Done.
+
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 16.59/ 16.59 GFLOPS | Progress: (4/20) | 4.51 s
[Task 10/25] Current/Best: 14.80/ 16.59 GFLOPS | Progress: (8/20) | 7.33 s
[Task 10/25] Current/Best: 5.74/ 18.28 GFLOPS | Progress: (12/20) | 9.69 s
[Task 10/25] Current/Best: 18.15/ 19.47 GFLOPS | Progress: (16/20) | 11.58 s
[Task 10/25] Current/Best: 18.99/ 19.47 GFLOPS | Progress: (20/20) | 13.72 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 18.72/ 19.74 GFLOPS | Progress: (4/20) | 4.52 s
[Task 11/25] Current/Best: 8.94/ 19.74 GFLOPS | Progress: (8/20) | 7.50 s
[Task 11/25] Current/Best: 11.79/ 21.67 GFLOPS | Progress: (12/20) | 10.34 s
[Task 11/25] Current/Best: 23.62/ 23.62 GFLOPS | Progress: (16/20) | 12.64 s
[Task 11/25] Current/Best: 12.01/ 23.62 GFLOPS | Progress: (20/20) | 15.34 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 17.23/ 17.23 GFLOPS | Progress: (4/20) | 6.35 s
[Task 12/25] Current/Best: 14.50/ 17.23 GFLOPS | Progress: (8/20) | 8.52 s
[Task 12/25] Current/Best: 13.65/ 17.23 GFLOPS | Progress: (12/20) | 12.10 s
[Task 12/25] Current/Best: 5.25/ 17.23 GFLOPS | Progress: (16/20) | 18.38 s
[Task 12/25] Current/Best: 10.11/ 17.39 GFLOPS | Progress: (20/20) | 21.77 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 9.43/ 21.08 GFLOPS | Progress: (4/20) | 6.17 s
[Task 13/25] Current/Best: 8.07/ 21.08 GFLOPS | Progress: (8/20) | 9.99 s
[Task 13/25] Current/Best: 16.33/ 22.13 GFLOPS | Progress: (12/20) | 13.51 s
[Task 13/25] Current/Best: 12.08/ 22.13 GFLOPS | Progress: (16/20) | 15.92 s
[Task 13/25] Current/Best: 18.92/ 22.13 GFLOPS | Progress: (20/20) | 18.91 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 8.11/ 12.81 GFLOPS | Progress: (4/20) | 12.80 s
[Task 14/25] Current/Best: 13.07/ 15.15 GFLOPS | Progress: (8/20) | 24.24 s
[Task 14/25] Current/Best: 18.49/ 18.49 GFLOPS | Progress: (12/20) | 31.30 s
[Task 14/25] Current/Best: 4.74/ 18.49 GFLOPS | Progress: (16/20) | 37.78 s
[Task 14/25] Current/Best: 15.56/ 18.49 GFLOPS | Progress: (20/20) | 40.19 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 21.38/ 21.38 GFLOPS | Progress: (4/20) | 5.36 s
[Task 15/25] Current/Best: 8.68/ 21.38 GFLOPS | Progress: (8/20) | 13.83 s
[Task 15/25] Current/Best: 6.94/ 21.38 GFLOPS | Progress: (12/20) | 17.07 s
[Task 15/25] Current/Best: 9.29/ 21.38 GFLOPS | Progress: (16/20) | 23.80 s
[Task 15/25] Current/Best: 3.14/ 21.38 GFLOPS | Progress: (20
/20) | 35.17 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 18.54/ 18.54 GFLOPS | Progress: (4/20) | 5.45 s
[Task 16/25] Current/Best: 14.60/ 18.54 GFLOPS | Progress: (8/20) | 8.70 s
[Task 16/25] Current/Best: 6.69/ 18.54 GFLOPS | Progress: (12/20) | 10.47 s
[Task 16/25] Current/Best: 17.77/ 18.68 GFLOPS | Progress: (16/20) | 12.19 s
[Task 16/25] Current/Best: 5.41/ 18.68 GFLOPS | Progress: (20/20) | 14.50 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 16.22/ 23.22 GFLOPS | Progress: (4/20) | 4.71 s
[Task 17/25] Current/Best: 13.42/ 23.22 GFLOPS | Progress: (8/20) | 7.20 s
[Task 17/25] Current/Best: 6.17/ 23.22 GFLOPS | Progress: (12/20) | 9.59 s
[Task 17/25] Current/Best: 18.89/ 23.22 GFLOPS | Progress: (16/20) | 11.95 s
[Task 17/25] Current/Best: 18.68/ 23.22 GFLOPS | Progress: (20/20) | 14.34 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 7.31/ 18.80 GFLOPS | Progress: (4/20) | 5.07 s
[Task 18/25] Current/Best: 12.60/ 21.66 GFLOPS | Progress: (8/20) | 7.63 s
[Task 18/25] Current/Best: 13.49/ 21.66 GFLOPS | Progress: (12/20) | 9.82 s
[Task 18/25] Current/Best: 20.89/ 21.66 GFLOPS | Progress: (16/20) | 11.88 s
[Task 18/25] Current/Best: 8.61/ 21.66 GFLOPS | Progress: (20/20) | 17.88 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 9.58/ 13.84 GFLOPS | Progress: (4/20) | 6.59 s
[Task 19/25] Current/Best: 20.24/ 20.24 GFLOPS | Progress: (8/20) | 11.18 s
[Task 19/25] Current/Best: 8.72/ 20.24 GFLOPS | Progress: (12/20) | 14.66 s Done.
+ Done.
+
[Task 19/25] Current/Best: 18.13/ 20.24 GFLOPS | Progress: (16/20) | 17.19 s
[Task 19/25] Current/Best: 8.77/ 20.24 GFLOPS | Progress: (20/20) | 20.40 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 16.72/ 16.72 GFLOPS | Progress: (4/20) | 5.14 s
[Task 20/25] Current/Best: 9.79/ 17.19 GFLOPS | Progress: (8/20) | 15.70 s
[Task 20/25] Current/Best: 4.70/ 18.16 GFLOPS | Progress: (12/20) | 22.93 s
[Task 20/25] Current/Best: 18.22/ 18.90 GFLOPS | Progress: (16/20) | 30.24 s
[Task 20/25] Current/Best: 10.43/ 18.90 GFLOPS | Progress: (20/20) | 33.51 s Done.
+
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 6.21/ 14.54 GFLOPS | Progress: (4/20) | 13.88 s
[Task 21/25] Current/Best: 7.40/ 14.54 GFLOPS | Progress: (8/20) | 19.36 s
[Task 21/25] Current/Best: 14.98/ 14.98 GFLOPS | Progress: (12/20) | 30.57 s
[Task 21/25] Current/Best: 17.90/ 21.28 GFLOPS | Progress: (16/20) | 33.41 s
[Task 21/25] Current/Best: 8.54/ 21.28 GFLOPS | Progress: (20/20) | 37.03 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 8.33/ 18.02 GFLOPS | Progress: (4/20) | 5.41 s
[Task 22/25] Current/Best: 17.74/ 18.02 GFLOPS | Progress: (8/20) | 8.07 s
[Task 22/25] Current/Best: 19.94/ 19.94 GFLOPS | Progress: (12/20) | 9.74 s
[Task 22/25] Current/Best: 18.86/ 19.94 GFLOPS | Progress: (16/20) | 12.04 s
[Task 22/25] Current/Best: 14.96/ 19.94 GFLOPS | Progress: (20/2
0) | 15.65 s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 14.56/ 22.04 GFLOPS | Progress: (4/20) | 7.08 s
[Task 23/25] Current/Best: 7.99/ 22.04 GFLOPS | Progress: (8/20) | 13.05 s
[Task 23/25] Current/Best: 10.40/ 22.04 GFLOPS | Progress: (12/20) | 15.65 s
[Task 23/25] Current/Best: 12.70/ 22.04 GFLOPS | Progress: (16/20) | 19.00 s
[Task 23/25] Current/Best: 10.45/ 22.04 GFLOPS | Progress: (20/20) | 22.47 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 2.83/ 2.83 GFLOPS | Progress: (4/20) | 13.33 s
[Task 24/25] Current/Best: 7.73/ 8.96 GFLOPS | Progress: (8/20) | 25.54 s
[Task 24/25] Current/Best: 2.80/ 8.96 GFLOPS | Progress: (12/20) | 37.74 s Done.
+
[Task 24/25] Current/Best: 6.84/ 8.96 GFLOPS | Progress: (16/20) | 48.76 s
[Task 24/25] Current/Best: 1.66/ 9.31 GFLOPS | Progress: (20/20) | 60.66 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 4.81/ 4.81 GFLOPS | Progress: (4/20) | 5.61 s
[Task 25/25] Current/Best: 2.91/ 8.63 GFLOPS | Progress: (8/20) | 8.16 s
[Task 25/25] Current/Best: 8.35/ 9.12 GFLOPS | Progress: (12/20) | 11.89 s
[Task 25/25] Current/Best: 2.83/ 9.12 GFLOPS | Progress: (16/20) | 17.74 s
[Task 25/25] Current/Best: 6.60/ 9.12 GFLOPS | Progress: (20/20) | 19.30 s Done.
+
@@ -707,8 +708,8 @@ Verify that the optimized model runs and produces the same results:
.. code-block:: none
- class='n02123045 tabby, tabby cat' with probability=0.621104
- class='n02123159 tiger cat' with probability=0.356378
+ class='n02123045 tabby, tabby cat' with probability=0.621105
+ class='n02123159 tiger cat' with probability=0.356377
class='n02124075 Egyptian cat' with probability=0.019712
class='n02129604 tiger, Panthera tigris' with probability=0.001215
class='n04040759 radiator' with probability=0.000262
@@ -765,8 +766,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 376.55249478004407, 'median': 374.42979039997226, 'std': 3.3020468792685795}
- unoptimized: {'mean': 494.9741758199889, 'median': 495.114422450024, 'std': 1.1117048733914823}
+ optimized: {'mean': 422.7526840199971, 'median': 422.83610059994317, 'std': 3.5374807866565536}
+ unoptimized: {'mean': 500.58081771001525, 'median': 500.23290955004995, 'std': 1.5838218019673596}
@@ -789,7 +790,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 12 minutes 48.324 seconds)
+ **Total running time of the script:** ( 13 minutes 50.568 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 77d64a8352..5427de57c4 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -274,7 +274,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.209e-07 secs/op
+ 1.274e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index e9f622659c..4ffe14eecd 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -270,7 +270,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0x163f7e60)), stage(b, placeholder(b, 0x1aa51240)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T.Range(0, 10), "DataPar", ""), T.iter_var(ax2, T.Range(0, 10), "DataPar", "")], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[a[ax0, ax1, ax2] * b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T [...]
+ [stage(a, placeholder(a, 0x286982a0)), stage(b, placeholder(b, 0x114e1150)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T.Range(0, 10), "DataPar", ""), T.iter_var(ax2, T.Range(0, 10), "DataPar", "")], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[a[ax0, ax1, ax2] * b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T [...]
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index df95fae218..3b93b27bed 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,32 +5,32 @@
Computation times
=================
-**16:34.857** total execution time for **tutorial** files:
+**17:38.604** total execution time for **tutorial** files:
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 12:48.324 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:34.065 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 00:57.157 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:42.811 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:30.442 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.963 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.857 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.239 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_uma.py` (``uma.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_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_install.py` (``install.py``) | 00:00.000 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 13:50.568 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:34.526 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:04.758 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:44.267 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:22.389 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.1000 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.877 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.220 | 0.0 MB |
++------------------------------------------------------------------------------------------+------------+--------+
+| :ref:`sphx_glr_tutorial_uma.py` (``uma.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_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_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 e20fdfa9e6..47a5188658 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -285,8 +285,8 @@ helper function to run a profile of the TVM generated code.
.. code-block:: none
- Numpy running time: 0.000006
- naive: 0.000007
+ Numpy running time: 0.000007
+ naive: 0.000006
@@ -389,7 +389,7 @@ compile and run this new schedule with the parallel operation applied:
.. code-block:: none
- parallel: 0.000006
+ parallel: 0.000009
@@ -444,7 +444,7 @@ factor to be the number of threads on your CPU.
.. code-block:: none
- vector: 0.000040
+ vector: 0.000039
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -498,10 +498,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 5.981479989713989e-06 1.0
- naive 6.9411e-06 1.1604318683563626
- parallel 6.0809e-06 1.016621306174555
- vector 3.99417e-05 6.677561417690182
+ numpy 6.9311000152083576e-06 1.0
+ naive 5.8438e-06 0.8431273516725221
+ parallel 9.299e-06 1.3416340811120817
+ vector 3.9168900000000004e-05 5.651180896835253
@@ -922,7 +922,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.016288
+ Numpy running time: 0.019049
@@ -980,7 +980,7 @@ optimizations.
.. code-block:: none
- none: 3.231282
+ none: 3.656533
@@ -1080,7 +1080,7 @@ schedule.
.. code-block:: none
- blocking: 0.281630
+ blocking: 0.323000
@@ -1164,7 +1164,7 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- vectorization: 0.259879
+ vectorization: 0.326812
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1230,7 +1230,7 @@ more cache friendly.
.. code-block:: none
- loop permutation: 0.112433
+ loop permutation: 0.137138
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1321,7 +1321,7 @@ optimized schedule.
.. code-block:: none
- array packing: 0.103895
+ array packing: 0.107841
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1404,7 +1404,7 @@ to `C` when all the block results are ready.
.. code-block:: none
- block caching: 0.097481
+ block caching: 0.113076
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1478,7 +1478,7 @@ of thread-level parallelization.
.. code-block:: none
- parallelization: 0.115672
+ parallelization: 0.133928
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1548,13 +1548,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.2312820005 1.0
- blocking 0.28162983869999997 0.08715730742671836
- vectorization 0.2598786084 0.08042585214159181
- loop permutation 0.1124331706 0.03479522077695552
- array packing 0.10389522139999999 0.032152941582914624
- block caching 0.09748085710000001 0.030167858170508204
- parallelization 0.1156715905 0.035797429776200686
+ none 3.6565331299 1.0
+ blocking 0.32300033079999996 0.08833513038861307
+ vectorization 0.3268121641 0.08937760235989925
+ loop permutation 0.1371382546 0.03750499441085346
+ array packing 0.10784103330000001 0.029492699633477486
+ block caching 0.1130755551 0.030924252860001413
+ parallelization 0.1339278657 0.03662700731598806
@@ -1594,6 +1594,11 @@ 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 4.758 seconds)
+
+
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
.. only:: html
diff --git a/docs/commit_hash b/docs/commit_hash
index 964a7c13b6..2418c4ba0f 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-20b08a5c8daf0227d7944eb253cf6e9f0945b8fc
+0e8e4217668183b24a91789150856e1514202a35
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index a13105ac32..d0a1429973 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -605,7 +605,7 @@ class:['truck 0.9266'] left:471 top:83 right:689 bottom:169
class:['bicycle 0.9984'] left:111 top:113 right:577 bottom:447
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 37.452 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 39.440 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 c5a2df231d..0e233588f2 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -459,7 +459,7 @@
<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.zipe673319f-f6c5-4687-9fb1-6095d9f9c68c 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.zip081dde5a-3ce8-4839-afb3-f0527d11d7df from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index c25cd9391f..82a9ca8807 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -469,14 +469,15 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
0%| | 0.00/41.5M [00:00<?, ?B/s]
- 15%|#5 | 6.33M/41.5M [00:00<00:00, 52.9MB/s]
- 27%|##7 | 11.4M/41.5M [00:00<00:00, 41.5MB/s]
- 37%|###7 | 15.4M/41.5M [00:00<00:00, 27.7MB/s]
- 54%|#####3 | 22.3M/41.5M [00:00<00:00, 38.7MB/s]
- 64%|######4 | 26.7M/41.5M [00:00<00:00, 35.4MB/s]
- 77%|#######7 | 32.0M/41.5M [00:00<00:00, 39.4MB/s]
- 96%|#########6| 40.0M/41.5M [00:01<00:00, 49.1MB/s]
-100%|##########| 41.5M/41.5M [00:01<00:00, 43.0MB/s]
+ 15%|#5 | 6.33M/41.5M [00:00<00:01, 28.7MB/s]
+ 22%|##1 | 9.07M/41.5M [00:00<00:01, 26.5MB/s]
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diff --git a/docs/how_to/compile_models/from_paddle.html b/docs/how_to/compile_models/from_paddle.html
index 3707465905..4ca5ef99a3 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -504,7 +504,7 @@ To begin, we’ll install PaddlePaddle>=2.1.3:</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 4.281 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.773 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 bb3d54120a..1b2f0faadf 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -452,15 +452,11 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
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diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index 8b93433afb..b2097de6f8 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -672,7 +672,7 @@ 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 35.034 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 36.250 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-tensorflow-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7f1d3d1b878694c201c614c807cdebc8/from_tensorflow.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_tensorflow.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/sg_execution_times.html b/docs/how_to/compile_models/sg_execution_times.html
index 5f1b2130ac..beb117a8cc 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>07:26.549</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>07:38.638</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -369,43 +369,43 @@
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<tbody>
<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>
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</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>01:36.250</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_paddle.html#sphx-glr-how-to-compile-models-from-paddle-py"><span class="std std-ref">Compile PaddlePaddle Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_paddle.py</span></code>)</p></td>
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+<td><p>01:06.773</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_oneflow.html#sphx-glr-how-to-compile-models-from-oneflow-py"><span class="std std-ref">Compile OneFlow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_oneflow.py</span></code>)</p></td>
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+<td><p>00:45.184</p></td>
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<tr class="row-odd"><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>00:39.331</p></td>
+<td><p>00:40.569</p></td>
<td><p>0.0 MB</p></td>
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<tr class="row-even"><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>
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<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>
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<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>
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<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_tflite.html#sphx-glr-how-to-compile-models-from-tflite-py"><span class="std std-ref">Compile TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tflite.py</span></code>)</p></td>
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+<td><p>00:12.296</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>00:02.975</p></td>
+<td><p>00:02.982</p></td>
<td><p>0.0 MB</p></td>
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diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno.html b/docs/how_to/deploy_models/deploy_model_on_adreno.html
index 02b95962e7..0b43c928c2 100644
--- a/docs/how_to/deploy_models/deploy_model_on_adreno.html
+++ b/docs/how_to/deploy_models/deploy_model_on_adreno.html
@@ -850,10 +850,10 @@ Top5 predictions:
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 4120.8783 4119.6472 4130.9018 4118.2180 3.4969
+ 4128.3883 4125.5310 4150.8472 4124.1747 7.6155
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 19.693 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 21.545 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-model-on-adreno-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/2387d8448da213eb625e6b3d916327d4/deploy_model_on_adreno.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_model_on_adreno.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html b/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html
index b53c8adc80..39a7b4508a 100644
--- a/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html
+++ b/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html
@@ -458,25 +458,32 @@ to run this tutorial with a real device over rpc.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels.h5
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</pre></div>
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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 f7aa417aee..dcdb49d52e 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -682,7 +682,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.7448 16.9271 17.2100 15.9493 0.3913
+ 17.0997 17.2100 17.5490 16.2214 0.3977
</pre></div>
</div>
</div>
diff --git a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
index 3f31cda108..99933959c0 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -474,35 +474,36 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
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/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/nn/functional.py:3912: 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).
(torch.floor((input.size(i + 2).float() * torch.tensor(scale_factors[i], dtype=torch.float32)).float()))
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/ops/boxes.py:157: 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).
@@ -593,7 +594,7 @@ torchvision rcnn models.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get 9 valid boxes
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 38.383 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 57.738 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 6a42e9f6e9..63a7144269 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -515,9 +515,9 @@ training. Other models require a full post training calibration.</p>
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
0%| | 0.00/13.6M [00:00<?, ?B/s]
- 47%|####6 | 6.30M/13.6M [00:00<00:00, 26.5MB/s]
- 65%|######5 | 8.84M/13.6M [00:00<00:00, 23.5MB/s]
-100%|##########| 13.6M/13.6M [00:00<00:00, 29.7MB/s]
+ 47%|####6 | 6.30M/13.6M [00:00<00:00, 63.5MB/s]
+ 91%|#########1| 12.4M/13.6M [00:00<00:00, 40.2MB/s]
+100%|##########| 13.6M/13.6M [00:00<00:00, 46.0MB/s]
</pre></div>
</div>
</div>
@@ -608,7 +608,7 @@ 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)
- 89.1363 89.0420 93.0028 88.8081 0.4420
+ 89.2267 89.1254 90.4185 88.9010 0.2800
</pre></div>
</div>
<div class="admonition note">
@@ -647,7 +647,7 @@ 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 29.620 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 35.040 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 8c942649ba..36a7d43f5b 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -600,7 +600,7 @@ 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)
- 110.4182 110.4049 113.8229 109.6947 0.4790
+ 112.1531 112.0897 113.3706 111.4586 0.3977
</pre></div>
</div>
<div class="admonition note">
diff --git a/docs/how_to/deploy_models/deploy_quantized.html b/docs/how_to/deploy_models/deploy_quantized.html
index 2367408ad9..f170ade695 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -541,7 +541,7 @@ for calibration. But the accuracy might be impacted.</p>
warnings.warn(
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 58.022 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 27.236 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/sg_execution_times.html b/docs/how_to/deploy_models/sg_execution_times.html
index 76e0ca25e1..2e02154bf1 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
+++ b/docs/how_to/deploy_models/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>11:58.297</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>13:06.713</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 86%" />
@@ -369,39 +369,39 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_object_detection_pytorch.html#sphx-glr-how-to-deploy-models-deploy-object-detection-pytorch-py"><span class="std std-ref">Compile PyTorch Object Detection Models</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_object_detection_pytorch.py</span></code>)</p></td>
-<td><p>03:38.383</p></td>
+<td><p>03:57.738</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>01:58.022</p></td>
+<td><p>02:27.236</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>01:29.620</p></td>
+<td><p>01:35.040</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_adreno.html#sphx-glr-how-to-deploy-models-deploy-model-on-adreno-py"><span class="std std-ref">Deploy the Pretrained Model on Adreno™</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_adreno.py</span></code>)</p></td>
-<td><p>01:19.693</p></td>
+<td><p>01:21.545</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>00:52.932</p></td>
+<td><p>00:54.908</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>00:51.538</p></td>
+<td><p>00:54.647</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_adreno_tvmc.html#sphx-glr-how-to-deploy-models-deploy-model-on-adreno-tvmc-py"><span class="std std-ref">Deploy the Pretrained Model on Adreno™ with tvmc Interface</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_adreno_tvmc.py</span></code>)</p></td>
-<td><p>00:47.314</p></td>
+<td><p>00:51.210</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_nano.html#sphx-glr-how-to-deploy-models-deploy-model-on-nano-py"><span class="std std-ref">Deploy the Pretrained Model on Jetson Nano</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_nano.py</span></code>)</p></td>
-<td><p>00:30.568</p></td>
+<td><p>00:32.455</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>00:30.221</p></td>
+<td><p>00:31.928</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 1d44fa000c..c2069b7da8 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -639,7 +639,7 @@ 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.zip5eea2627-759f-4fc8-89d8-d131d45bbf3e 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.zipc9b40a5d-fd36-4694-b3e7-3757ecac6510 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
</pre></div>
</div>
<p>It’s easy to execute MobileNet with native TVM:</p>
diff --git a/docs/how_to/extend_tvm/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index b8661f38aa..fa1e1a37b6 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>00:59.595</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>01:03.038</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -369,15 +369,15 @@
</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>00:55.503</p></td>
+<td><p>00:58.708</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>00:02.865</p></td>
+<td><p>00:03.042</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="use_pass_infra.html#sphx-glr-how-to-extend-tvm-use-pass-infra-py"><span class="std std-ref">How to Use TVM Pass Infra</span></a> (<code class="docutils literal notranslate"><span class="pre">use_pass_infra.py</span></code>)</p></td>
-<td><p>00:01.218</p></td>
+<td><p>00:01.281</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="low_level_custom_pass.html#sphx-glr-how-to-extend-tvm-low-level-custom-pass-py"><span class="std std-ref">Writing a Customized Pass</span></a> (<code class="docutils literal notranslate"><span class="pre">low_level_custom_pass.py</span></code>)</p></td>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 4b5bafefb7..d661f898ce 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -546,10 +546,10 @@ 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: 25286us [25286us] (48.62%; 48.62%)
-FoldScaleAxis: 26722us [8us] (51.38%; 51.38%)
- FoldConstant: 26714us [1818us] (51.37%; 99.97%)
- InferType: 24897us [24897us] (47.87%; 93.20%)
+InferType: 26080us [26080us] (48.43%; 48.43%)
+FoldScaleAxis: 27772us [10us] (51.57%; 51.57%)
+ FoldConstant: 27762us [1914us] (51.55%; 99.96%)
+ InferType: 25848us [25848us] (48.00%; 93.10%)
</pre></div>
</div>
</div>
@@ -571,10 +571,10 @@ 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: 25148us [25148us] (48.26%; 48.26%)
-FoldScaleAxis: 26960us [8us] (51.74%; 51.74%)
- FoldConstant: 26952us [1925us] (51.72%; 99.97%)
- InferType: 25027us [25027us] (48.03%; 92.86%)
+InferType: 26044us [26044us] (48.37%; 48.37%)
+FoldScaleAxis: 27798us [10us] (51.63%; 51.63%)
+ FoldConstant: 27788us [1955us] (51.61%; 99.96%)
+ InferType: 25832us [25832us] (47.98%; 92.96%)
</pre></div>
</div>
<p>Register empty list to clear existing instruments.</p>
diff --git a/docs/how_to/optimize_operators/opt_conv_cuda.html b/docs/how_to/optimize_operators/opt_conv_cuda.html
index 8714b430d3..3627abd695 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -595,7 +595,7 @@ latency of convolution.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Convolution: </span><span class="si">%f</span><span class="s2"> ms"</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">*</span> <span cl [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 53.581600 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 52.110080 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 e2e90bc692..457983f5e7 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -877,7 +877,7 @@ 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: 12.266588 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 11.292902 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 2bebc35467..007339b3cc 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -492,8 +492,8 @@ 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: 0.018203
-Baseline: 3.394873
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.019308
+Baseline: 3.694823
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -552,7 +552,7 @@ 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: 0.297073
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.328926
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -609,7 +609,7 @@ 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: 0.282980
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.329192
</pre></div>
</div>
<p>Here is the generated IR after vectorization.</p>
@@ -664,7 +664,7 @@ 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: 0.114630
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.141160
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -741,7 +741,7 @@ 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: 0.107914
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.111365
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -819,7 +819,7 @@ 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: 0.112693
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.115196
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -899,7 +899,7 @@ class Module:
<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: 0.132949
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.136598
</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 2dc610a2f6..9731eb1e2c 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>00:34.050</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:36.717</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -369,15 +369,15 @@
</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>00:30.890</p></td>
+<td><p>00:33.425</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>00:01.933</p></td>
+<td><p>00:02.066</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="opt_conv_cuda.html#sphx-glr-how-to-optimize-operators-opt-conv-cuda-py"><span class="std std-ref">How to optimize convolution on GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">opt_conv_cuda.py</span></code>)</p></td>
-<td><p>00:01.227</p></td>
+<td><p>00:01.226</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 d3f3a95154..524dedb88f 100644
--- a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
+++ b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>03:39.512</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>03:49.952</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -369,27 +369,27 @@
</colgroup>
<tbody>
<tr class="row-odd"><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>01:35.153</p></td>
+<td><p>01:39.358</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-cuda-py"><span class="std std-ref">Auto-scheduling a Neural Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_cuda.py</span></code>)</p></td>
-<td><p>01:13.282</p></td>
+<td><p>01:16.809</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_arm.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-arm-py"><span class="std std-ref">Auto-scheduling a Neural Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_arm.py</span></code>)</p></td>
-<td><p>00:18.135</p></td>
+<td><p>00:19.314</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
-<td><p>00:16.706</p></td>
+<td><p>00:17.570</p></td>
<td><p>0.0 MB</p></td>
</tr>
<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>00:16.135</p></td>
+<td><p>00:16.796</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>00:00.102</p></td>
+<td><p>00:00.104</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 28c71739be..5351667c8b 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
@@ -1032,7 +1032,7 @@ class Module:
<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: 0.337 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.331 ms
</pre></div>
</div>
</div>
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 0715229827..f4aa3abf94 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -936,7 +936,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 3.1987 3.1983 3.1996 3.1981 0.0007
+ 3.2059 3.2060 3.2065 3.2053 0.0005
</pre></div>
</div>
</div>
@@ -958,7 +958,7 @@ 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 13.282 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 16.809 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-cuda-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/eafe360d52540634c9eea0fa89e804bd/tune_network_cuda.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_cuda.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
index 9b35813450..e8b6966ca8 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -955,7 +955,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 767.3287 767.4479 768.3663 766.1720 0.8998
+ 764.8503 764.1512 768.0400 762.3597 2.3711
</pre></div>
</div>
</div>
@@ -977,7 +977,7 @@ 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 35.153 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 39.358 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_autotvm/sg_execution_times.html b/docs/how_to/tune_with_autotvm/sg_execution_times.html
index 5f0385e76a..e63cabaffe 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -360,7 +360,7 @@
<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>00:23.584</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:23.787</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -369,7 +369,7 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-conv2d-cuda-py"><span class="std std-ref">Tuning High Performance Convolution on NVIDIA GPUs</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_cuda.py</span></code>)</p></td>
-<td><p>00:23.545</p></td>
+<td><p>00:23.747</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>
@@ -380,11 +380,11 @@
<td><p>00:00.006</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_arm.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-arm-py"><span class="std std-ref">Auto-tuning a Convolutional Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_arm.py</span></code>)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_mobile_gpu.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-mobile-gpu-py"><span class="std std-ref">Auto-tuning a Convolutional Network for Mobile GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_mobile_gpu.py</span></code>)</p></td>
<td><p>00:00.005</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_mobile_gpu.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-mobile-gpu-py"><span class="std std-ref">Auto-tuning a Convolutional Network for Mobile GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_mobile_gpu.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_arm.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-arm-py"><span class="std std-ref">Auto-tuning a Convolutional Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_arm.py</span></code>)</p></td>
<td><p>00:00.005</p></td>
<td><p>0.0 MB</p></td>
</tr>
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 6da2b557f9..9a91778e2f 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -630,7 +630,7 @@ and measure running time.</p>
Best config:
,None
-Time cost of this operator: 0.036982
+Time cost of this operator: 0.037159
</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 88e147eb43..02fe0fd56e 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -664,10 +664,10 @@ the tuned operator.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 296.2 98.721 (1, 2, 10, 10, 3) 2 1 [296.2]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.869 0.956 (1, 6, 10, 10) 1 1 [2.869]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.97 0.323 (1, 1, 10, 10, 3) 1 1 [0.97]
-Total_time - 300.039 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 306.7 98.702 (1, 2, 10, 10, 3) 2 1 [306.7]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.046 0.98 (1, 6, 10, 10) 1 1 [3.046]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.986 0.317 (1, 1, 10, 10, 3) 1 1 [0.986]
+Total_time - 310.733 - - - - -
</pre></div>
</div>
</div>
@@ -719,13 +719,13 @@ Total_time -
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 137.5 98.127 (1, 6, 10, 10, 1) 2 1 [137.5]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.772 1.264 (1, 6, 10, 10) 1 1 [1.772]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.853 0.609 (1, 3, 10, 10, 1) 1 1 [0.853]
-Total_time - 140.125 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 102.8 97.51 (1, 6, 10, 10, 1) 2 1 [102.8]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.778 1.687 (1, 6, 10, 10) 1 1 [1.778]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.847 0.804 (1, 3, 10, 10, 1) 1 1 [0.847]
+Total_time - 105.426 - - - - -
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 16.028 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 23.124 seconds)</p>
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index 901ca5c1f4..e31c07bb3d 100644
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+++ b/docs/how_to/work_with_microtvm/micro_pytorch.html
@@ -475,8 +475,8 @@ download a cat image and preprocess it to use as the model input.</p>
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
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/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/_utils.py:314: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
device=storage.device,
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -604,7 +604,7 @@ via the host <cite>main.cc`</cite> or if a Zephyr emulated board is selected as
Torch top-1 id: 282, class name: tiger cat
</pre></div>
</div>
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<p><a class="reference download internal" download="" href="../../_downloads/12b9ecc04c41abaa12022061771821d1/micro_pytorch.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">micro_pytorch.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/micro_train.html b/docs/how_to/work_with_microtvm/micro_train.html
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--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -543,7 +543,7 @@ 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 [...]
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</pre></div>
</div>
</div>
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<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>
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</pre></div>
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</div>
@@ -716,13 +716,13 @@ the time on our validation set).</p>
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Epoch 2/3
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+328/328 - 36s - loss: 0.0988 - accuracy: 0.9622 - val_loss: 0.0839 - val_accuracy: 0.9705 - 36s/epoch - 111ms/step
Epoch 3/3
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+328/328 - 36s - loss: 0.0674 - accuracy: 0.9744 - val_loss: 0.0828 - val_accuracy: 0.9705 - 36s/epoch - 110ms/step
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@@ -986,7 +986,7 @@ 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>
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<div class="section" id="computation-times">
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index c95200d574..feae6abe2e 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -572,7 +572,7 @@ 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>
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</pre></div>
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<p>Register the rule to TVM with override option to override existing rule.
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<div class="section" id="computation-times">
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<p class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
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<li class="toctree-l1 current"><a class="reference internal" href="index.html">Installing TVM</a><ul class="current">
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+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="from_source.html#enable-c-tests">Enable C++ Tests</a></li>
+</ul>
+</li>
<li class="toctree-l2"><a class="reference internal" href="docker.html">Docker Images</a></li>
<li class="toctree-l2 current"><a class="current reference internal" href="#">NNPACK Contrib Installation</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#conditions">Conditions</a></li>
diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index 0ebfcc463d..253cd55753 100644
--- a/docs/reference/api/python/auto_scheduler.html
+++ b/docs/reference/api/python/auto_scheduler.html
@@ -1637,7 +1637,7 @@ history states as starting point to perform Evolutionary Search).</p></li>
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy">
-<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
+<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
<dd><p>The search policy that searches in a hierarchical search space defined by sketches.
The policy randomly samples programs from the space defined by sketches and use evolutionary
search to fine-tune them.</p>
@@ -1921,7 +1921,7 @@ Candidates:
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.auto_schedule">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
<dd><p>THIS API IS DEPRECATED.</p>
<p>Run auto scheduling search for a task.</p>
<dl class="field-list simple">
diff --git a/docs/reference/api/typedoc/classes/ArtifactCache.html b/docs/reference/api/typedoc/classes/ArtifactCache.html
index b8050f10dd..90e6967ec1 100644
--- a/docs/reference/api/typedoc/classes/ArtifactCache.html
+++ b/docs/reference/api/typedoc/classes/ArtifactCache.html
@@ -24,7 +24,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">ArtifactCache</span></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L988">runtime.ts:988</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L988">runtime.ts:988</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -53,7 +53,7 @@
<h5><span class="tsd-kind-parameter">scope</span>: <span class="tsd-signature-type">string</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="ArtifactCache.html" class="tsd-signature-type tsd-kind-class">ArtifactCache</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L992">runtime.ts:992</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L992">runtime.ts:992</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="fetchWithCache" class="tsd-anchor"></a>
@@ -68,7 +68,7 @@
<h5><span class="tsd-kind-parameter">url</span>: <span class="tsd-signature-type">string</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type ">Response</span><span class="tsd-signature-symbol">></span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L996">runtime.ts:996</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L996">runtime.ts:996</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="hasAllKeys" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>has<wbr/>All<wbr/>Keys</span><a href="#hasAllKeys" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -81,7 +81,7 @@
<h5><span class="tsd-kind-parameter">keys</span>: <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">[]</span></h5></li></ul></div>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1012">runtime.ts:1012</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1012">runtime.ts:1012</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
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diff --git a/docs/reference/api/typedoc/classes/DLDataType.html b/docs/reference/api/typedoc/classes/DLDataType.html
index 4ae4bcc38e..9ffe6d3cd6 100644
--- a/docs/reference/api/typedoc/classes/DLDataType.html
+++ b/docs/reference/api/typedoc/classes/DLDataType.html
@@ -24,7 +24,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">DLDataType</span></li></ul></section><aside class="tsd-sources">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L398">runtime.ts:398</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L398">runtime.ts:398</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -63,7 +63,7 @@
<h5><span class="tsd-kind-parameter">lanes</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="DLDataType.html" class="tsd-signature-type tsd-kind-class">DLDataType</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L406">runtime.ts:406</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L406">runtime.ts:406</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="bits" class="tsd-anchor"></a>
@@ -73,7 +73,7 @@
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L402">runtime.ts:402</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L402">runtime.ts:402</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="code" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>code</span><a href="#code" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">code</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
@@ -81,7 +81,7 @@
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L400">runtime.ts:400</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L400">runtime.ts:400</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="lanes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>lanes</span><a href="#lanes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">lanes</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
@@ -89,7 +89,7 @@
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L404">runtime.ts:404</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L404">runtime.ts:404</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="numStorageBytes" class="tsd-anchor"></a>
@@ -99,7 +99,7 @@
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L421">runtime.ts:421</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L421">runtime.ts:421</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>String</span><a href="#toString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -107,7 +107,7 @@
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><aside class="tsd-sources">
<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L412">runtime.ts:412</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/DLDevice.html b/docs/reference/api/typedoc/classes/DLDevice.html
index 6af46c76f5..ae424a330e 100644
--- a/docs/reference/api/typedoc/classes/DLDevice.html
+++ b/docs/reference/api/typedoc/classes/DLDevice.html
@@ -24,7 +24,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">DLDevice</span></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L338">runtime.ts:338</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L338">runtime.ts:338</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -62,7 +62,7 @@
<h5><span class="tsd-kind-parameter">lib</span>: <a href="_internal_.FFILibrary.html" class="tsd-signature-type tsd-kind-class">FFILibrary</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="DLDevice.html" class="tsd-signature-type tsd-kind-class">DLDevice</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L346">runtime.ts:346</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L346">runtime.ts:346</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="deviceId" class="tsd-anchor"></a>
@@ -72,7 +72,7 @@
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L342">runtime.ts:342</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L342">runtime.ts:342</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="deviceType" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>device<wbr/>Type</span><a href="#deviceType" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">device<wbr/>Type</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
@@ -80,7 +80,7 @@
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L340">runtime.ts:340</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L340">runtime.ts:340</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="sync" class="tsd-anchor"></a>
@@ -93,7 +93,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">></span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L365">runtime.ts:365</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L365">runtime.ts:365</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>String</span><a href="#toString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -101,7 +101,7 @@
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L372">runtime.ts:372</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L372">runtime.ts:372</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/Instance.html b/docs/reference/api/typedoc/classes/Instance.html
index 4aa9914923..29e7d1a1fb 100644
--- a/docs/reference/api/typedoc/classes/Instance.html
+++ b/docs/reference/api/typedoc/classes/Instance.html
@@ -41,7 +41,7 @@ are not tracked through JS native garbage collection mechanism.</p>
<ul class="tsd-hierarchy">
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1040">runtime.ts:1040</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1040">runtime.ts:1040</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
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@@ -145,24 +145,24 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<h4>See</h4><p>Please use the async version <a href="../functions/instantiate.html" class="tsd-kind-function">instantiate</a> when targeting browsers.</p>
</div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1069">runtime.ts:1069</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1069">runtime.ts:1069</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="cacheMetadata" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>cache<wbr/>Metadata</span><a href="#cacheMetadata" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">cache<wbr/>Metadata</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">any</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/20b08a5c8/web/src/runtime.ts#L1043">runtime.ts:1043</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1043">runtime.ts:1043</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="exports" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>exports</span><a href="#exports" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">exports</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 ">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/20b08a5c8/web/src/runtime.ts#L1042">runtime.ts:1042</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1042">runtime.ts:1042</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="memory" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>memory</span><a href="#memory" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">memory</span><span class="tsd-signature-symbol">:</span> <a href="_internal_.Memory.html" class="tsd-signature-type tsd-kind-class">Memory</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1041">runtime.ts:1041</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1041">runtime.ts:1041</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="applyRepetitionPenalty" class="tsd-anchor"></a>
@@ -193,7 +193,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">any</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1756">runtime.ts:1756</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1756">runtime.ts:1756</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="applySoftmaxWithTemperature" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>apply<wbr/>Softmax<wbr/>With<wbr/>Temperature</span><a href="#applySoftmaxWithTemperature" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -217,7 +217,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1765">runtime.ts:1765</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1765">runtime.ts:1765</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="asyncLoadWebGPUPipelines" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>async<wbr/>Load<wbr/>WebGPUPipelines</span><a href="#asyncLoadWebGPUPipelines" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -236,7 +236,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol"><</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">></span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1923">runtime.ts:1923</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1923">runtime.ts:1923</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="attachToCurrentScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>attach<wbr/>To<wbr/>Current<wbr/>Scope</span><a href="#attachToCurrentScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -265,7 +265,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<a href="Instance.html#detachFromCurrentScope" class="tsd-kind-method">detachFromCurrentScope</a> to create a detached object.</p>
</div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1192">runtime.ts:1192</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1192">runtime.ts:1192</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="beginScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>begin<wbr/>Scope</span><a href="#beginScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -276,7 +276,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1151">runtime.ts:1151</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1151">runtime.ts:1151</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="benchmark" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>benchmark</span><a href="#benchmark" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -312,7 +312,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<h4>Repeat</h4><p>The number of times to repeat the run.</p>
</div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1110">runtime.ts:1110</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1110">runtime.ts:1110</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="bindCanvas" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>bind<wbr/>Canvas</span><a href="#bindCanvas" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -331,7 +331,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1773">runtime.ts:1773</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1773">runtime.ts:1773</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="clearCanvas" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>clear<wbr/>Canvas</span><a href="#clearCanvas" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -342,7 +342,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1804">runtime.ts:1804</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1804">runtime.ts:1804</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="cpu" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>cpu</span><a href="#cpu" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -361,7 +361,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1654">runtime.ts:1654</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1654">runtime.ts:1654</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="createVirtualMachine" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>create<wbr/>Virtual<wbr/>Machine</span><a href="#createVirtualMachine" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -381,7 +381,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1370">runtime.ts:1370</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1370">runtime.ts:1370</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="detachFromCurrentScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>detach<wbr/>From<wbr/>Current<wbr/>Scope</span><a href="#detachFromCurrentScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -409,7 +409,7 @@ so it won't be released via auto-release during endscope.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1219">runtime.ts:1219</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1219">runtime.ts:1219</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="device" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>device</span><a href="#device" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -434,7 +434,7 @@ so it won't be released via auto-release during endscope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1646">runtime.ts:1646</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1646">runtime.ts:1646</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -448,7 +448,7 @@ only the first call will take effect.</p>
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<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1131">runtime.ts:1131</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1131">runtime.ts:1131</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="empty" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>empty</span><a href="#empty" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -478,7 +478,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1674">runtime.ts:1674</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1674">runtime.ts:1674</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="endScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>end<wbr/>Scope</span><a href="#endScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -492,7 +492,7 @@ a value to parent scope.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1162">runtime.ts:1162</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1162">runtime.ts:1162</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="fetchNDArrayCache" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>fetchNDArray<wbr/>Cache</span><a href="#fetchNDArrayCache" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -522,7 +522,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1461">runtime.ts:1461</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1461">runtime.ts:1461</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getGlobalFunc" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Global<wbr/>Func</span><a href="#getGlobalFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -542,7 +542,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1307">runtime.ts:1307</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1307">runtime.ts:1307</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getParamsFromCache" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Params<wbr/>From<wbr/>Cache</span><a href="#getParamsFromCache" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -566,7 +566,7 @@ a value to parent scope.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1398">runtime.ts:1398</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1398">runtime.ts:1398</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getParamsFromCacheByName" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Params<wbr/>From<wbr/>Cache<wbr/>By<wbr/>Name</span><a href="#getParamsFromCacheByName" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -586,7 +586,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1409">runtime.ts:1409</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="initWebGPU" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>init<wbr/>WebGPU</span><a href="#initWebGPU" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -605,7 +605,7 @@ a value to parent scope.</p>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1988">runtime.ts:1988</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1988">runtime.ts:1988</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="isPackedFunc" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>is<wbr/>Packed<wbr/>Func</span><a href="#isPackedFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -625,7 +625,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1342">runtime.ts:1342</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="listGlobalFuncNames" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>list<wbr/>Global<wbr/>Func<wbr/>Names</span><a href="#listGlobalFuncNames" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -637,7 +637,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1235">runtime.ts:1235</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="makeShapeTuple" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>make<wbr/>Shape<wbr/>Tuple</span><a href="#makeShapeTuple" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -657,7 +657,7 @@ a value to parent scope.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1838">runtime.ts:1838</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="makeString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>make<wbr/>String</span><a href="#makeString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -677,7 +677,7 @@ a value to parent scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1829">runtime.ts:1829</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="makeTVMArray" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>makeTVMArray</span><a href="#makeTVMArray" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -699,7 +699,7 @@ and needs to b explicitly disposed.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1817">runtime.ts:1817</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="moveToParentScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>move<wbr/>To<wbr/>Parent<wbr/>Scope</span><a href="#moveToParentScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -726,7 +726,7 @@ alive when exit the current scope.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1205">runtime.ts:1205</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1422">runtime.ts:1422</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1431">runtime.ts:1431</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1440">runtime.ts:1440</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1896">runtime.ts:1896</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1274">runtime.ts:1274</a></li></ul></aside></li></ul></section>
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<h3 class="tsd-anchor-link"><span>register<wbr/>Init<wbr/>Progress<wbr/>Callback</span><a href="#registerInitProgressCallback" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1387">runtime.ts:1387</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1875">runtime.ts:1875</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1140">runtime.ts:1140</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1746">runtime.ts:1746</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="scalar" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>scalar</span><a href="#scalar" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1636">runtime.ts:1636</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="setPackedArguments" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>set<wbr/>Packed<wbr/>Arguments</span><a href="#setPackedArguments" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L2121">runtime.ts:2121</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1782">runtime.ts:1782</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="systemLib" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>system<wbr/>Lib</span><a href="#systemLib" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1228">runtime.ts:1228</a></li></ul></aside></li></ul></section>
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<h3 class="tsd-anchor-link"><span>toDLData<wbr/>Type</span><a href="#toDLDataType" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1590">runtime.ts:1590</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toPackedFunc" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>Packed<wbr/>Func</span><a href="#toPackedFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1353">runtime.ts:1353</a></li></ul></aside></li></ul></section>
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<h3 class="tsd-anchor-link"><span>type<wbr/>Key2<wbr/>Index</span><a href="#typeKey2Index" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1847">runtime.ts:1847</a></li></ul></aside></li></ul></section>
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<h3 class="tsd-anchor-link"><span>uniform</span><a href="#uniform" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1720">runtime.ts:1720</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="webgpu" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>webgpu</span><a href="#webgpu" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -1154,7 +1154,7 @@ System lib is a global module that contains self register functions in startup.<
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L1662">runtime.ts:1662</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1662">runtime.ts:1662</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="withNewScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>with<wbr/>New<wbr/>Scope</span><a href="#withNewScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L1176">runtime.ts:1176</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/Module.html b/docs/reference/api/typedoc/classes/Module.html
index 5ea0ccc2ed..a392884761 100644
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L686">runtime.ts:686</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L686">runtime.ts:686</a></li></ul></aside>
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<h4 class="tsd-returns-title">Returns <a href="Module.html" class="tsd-signature-type tsd-kind-class">Module</a></h4><aside class="tsd-sources">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L691">runtime.ts:691</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L691">runtime.ts:691</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
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@@ -90,7 +90,7 @@ only the first call will take effect.</p>
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<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L701">runtime.ts:701</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L701">runtime.ts:701</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getFunction" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Function</span><a href="#getFunction" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L729">runtime.ts:729</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -135,7 +135,7 @@ only the first call will take effect.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L716">runtime.ts:716</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="importModule" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>import<wbr/>Module</span><a href="#importModule" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L763">runtime.ts:763</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L429">runtime.ts:429</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L449">runtime.ts:449</a></li></ul></aside></li></ul></section></section>
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<h2>Properties</h2>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L439">runtime.ts:439</a></li></ul></aside></section>
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<div class="tsd-signature"><span class="tsd-kind-property">dtype</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div>
@@ -95,7 +95,7 @@
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L435">runtime.ts:435</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L441">runtime.ts:441</a></li></ul></aside></section>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L433">runtime.ts:433</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L433">runtime.ts:433</a></li></ul></aside></section>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L437">runtime.ts:437</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L437">runtime.ts:437</a></li></ul></aside></section></section>
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<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="copyFrom" class="tsd-anchor"></a>
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L549">runtime.ts:549</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="copyFromRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>copy<wbr/>From<wbr/>Raw<wbr/>Bytes</span><a href="#copyFromRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -162,7 +162,7 @@ The number of elements must match.</p>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L593">runtime.ts:593</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L593">runtime.ts:593</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -176,7 +176,7 @@ only the first call will take effect.</p>
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<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L534">runtime.ts:534</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L534">runtime.ts:534</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getDataPtr" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Data<wbr/>Ptr</span><a href="#getDataPtr" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -188,7 +188,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L527">runtime.ts:527</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L527">runtime.ts:527</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -208,7 +208,7 @@ only the first call will take effect.</p>
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<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L515">runtime.ts:515</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toArray" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>Array</span><a href="#toArray" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -221,7 +221,7 @@ the dtype of the NDArray.</p>
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<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L659">runtime.ts:659</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>Raw<wbr/>Bytes</span><a href="#toRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -233,7 +233,7 @@ the dtype of the NDArray.</p>
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<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L628">runtime.ts:628</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="view" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>view</span><a href="#view" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -253,7 +253,7 @@ the dtype of the NDArray.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L504">runtime.ts:504</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/RPCServer.html b/docs/reference/api/typedoc/classes/RPCServer.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li></ul></aside>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/rpc_server.ts#L100">rpc_server.ts:100</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L100">rpc_server.ts:100</a></li></ul></aside></li></ul></section></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L83">rpc_server.ts:83</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="key" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>key</span><a href="#key" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="logger" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>logger</span><a href="#logger" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li></ul></aside></section>
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<h3 class="tsd-anchor-link"><span>state</span><a href="#state" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="url" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li></ul></aside></section></section></div>
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<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/Scalar.html b/docs/reference/api/typedoc/classes/Scalar.html
index 52df115f61..84747e3084 100644
--- a/docs/reference/api/typedoc/classes/Scalar.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L276">runtime.ts:276</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L276">runtime.ts:276</a></li></ul></aside>
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<h4 class="tsd-returns-title">Returns <a href="Scalar.html" class="tsd-signature-type tsd-kind-class">Scalar</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L282">runtime.ts:282</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L282">runtime.ts:282</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
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<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L280">runtime.ts:280</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L280">runtime.ts:280</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="value" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>value</span><a href="#value" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">value</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
@@ -74,7 +74,7 @@ argument to PackedFunc calls.</p>
</div>
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L278">runtime.ts:278</a></li></ul></aside></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L278">runtime.ts:278</a></li></ul></aside></section></section></div>
<div class="col-sidebar">
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diff --git a/docs/reference/api/typedoc/classes/TVMArray.html b/docs/reference/api/typedoc/classes/TVMArray.html
index 54c99cdf1e..ab051de6b1 100644
--- a/docs/reference/api/typedoc/classes/TVMArray.html
+++ b/docs/reference/api/typedoc/classes/TVMArray.html
@@ -26,7 +26,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">TVMArray</span></li></ul></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L860">runtime.ts:860</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L860">runtime.ts:860</a></li></ul></aside>
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@@ -64,7 +64,7 @@
<h4 class="tsd-returns-title">Returns <a href="TVMArray.html" class="tsd-signature-type tsd-kind-class">TVMArray</a></h4><aside class="tsd-sources">
<p>Overrides <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#constructor">constructor</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L861">runtime.ts:861</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L861">runtime.ts:861</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="dispose" class="tsd-anchor"></a>
@@ -80,7 +80,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="get" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get</span><a href="#get" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -100,7 +100,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L880">runtime.ts:880</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L880">runtime.ts:880</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -121,7 +121,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#getHandle">getHandle</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="size" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>size</span><a href="#size" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -131,7 +131,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L872">runtime.ts:872</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L872">runtime.ts:872</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="typeIndex" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Index</span><a href="#typeIndex" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -143,7 +143,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#typeIndex">typeIndex</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="typeKey" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Key</span><a href="#typeKey" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -155,7 +155,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#typeKey">typeKey</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
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<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/TVMObject.html b/docs/reference/api/typedoc/classes/TVMObject.html
index 687e7e4bfb..787f21a61b 100644
--- a/docs/reference/api/typedoc/classes/TVMObject.html
+++ b/docs/reference/api/typedoc/classes/TVMObject.html
@@ -31,7 +31,7 @@
<ul class="tsd-hierarchy">
<li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L776">runtime.ts:776</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L776">runtime.ts:776</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -66,7 +66,7 @@
<h5><span class="tsd-kind-parameter">ctx</span>: <a href="_internal_.RuntimeContext.html" class="tsd-signature-type tsd-kind-class">RuntimeContext</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="TVMObject.html" class="tsd-signature-type tsd-kind-class">TVMObject</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L781">runtime.ts:781</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L781">runtime.ts:781</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
@@ -82,7 +82,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -102,7 +102,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="typeIndex" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Index</span><a href="#typeIndex" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -113,7 +113,7 @@ only the first call will take effect.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="typeKey" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Key</span><a href="#typeKey" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -124,7 +124,7 @@ only the first call will take effect.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
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<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/VirtualMachine.html b/docs/reference/api/typedoc/classes/VirtualMachine.html
index 74b6fe1202..a4f48be06a 100644
--- a/docs/reference/api/typedoc/classes/VirtualMachine.html
+++ b/docs/reference/api/typedoc/classes/VirtualMachine.html
@@ -31,7 +31,7 @@
<ul class="tsd-hierarchy">
<li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L915">runtime.ts:915</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L915">runtime.ts:915</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -72,7 +72,7 @@
<h4 class="tsd-returns-title">Returns <a href="VirtualMachine.html" class="tsd-signature-type tsd-kind-class">VirtualMachine</a></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L922">runtime.ts:922</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L922">runtime.ts:922</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
@@ -88,7 +88,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L935">runtime.ts:935</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L935">runtime.ts:935</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getFunction" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Function</span><a href="#getFunction" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -108,7 +108,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L943">runtime.ts:943</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L943">runtime.ts:943</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getInternalModule" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Internal<wbr/>Module</span><a href="#getInternalModule" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -119,7 +119,7 @@ only the first call will take effect.</p>
<h4 class="tsd-returns-title">Returns <a href="Module.html" class="tsd-signature-type tsd-kind-class">Module</a></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L950">runtime.ts:950</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L950">runtime.ts:950</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html b/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
index 2782ab6bae..258fb37c10 100644
--- a/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
+++ b/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
@@ -37,7 +37,7 @@ can still call into storeXX</li>
<ul class="tsd-hierarchy">
<li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -87,7 +87,7 @@ can still call into storeXX</li>
<h5><span class="tsd-kind-parameter">freeSpace</span>: <a href="../types/_internal_.FTVMWasmFreeSpace.html" class="tsd-signature-type tsd-kind-type-alias">FTVMWasmFreeSpace</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.CachedCallStack.html" class="tsd-signature-type tsd-kind-class">CachedCallStack</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L225">memory.ts:225</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L225">memory.ts:225</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="tempArgs" class="tsd-anchor"></a>
@@ -97,7 +97,7 @@ can still call into storeXX</li>
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L208">memory.ts:208</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L208">memory.ts:208</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="allocPtrArray" class="tsd-anchor"></a>
@@ -119,7 +119,7 @@ can still call into storeXX</li>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L312">memory.ts:312</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L312">memory.ts:312</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="allocRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>alloc<wbr/>Raw<wbr/>Bytes</span><a href="#allocRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -140,7 +140,7 @@ can still call into storeXX</li>
<h4>Note</h4><p>This function always allocate space that aligns to 64bit.</p>
</div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L284">memory.ts:284</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L284">memory.ts:284</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="allocThenSetArgBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>alloc<wbr/>Then<wbr/>Set<wbr/>Arg<wbr/>Bytes</span><a href="#allocThenSetArgBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -165,7 +165,7 @@ Allocate new temporary space for bytes.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L389">memory.ts:389</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L389">memory.ts:389</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="allocThenSetArgString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>alloc<wbr/>Then<wbr/>Set<wbr/>Arg<wbr/>String</span><a href="#allocThenSetArgString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -192,7 +192,7 @@ and will be filled when we commit the data.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L377">memory.ts:377</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L377">memory.ts:377</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="commitToWasmMemory" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>commit<wbr/>To<wbr/>Wasm<wbr/>Memory</span><a href="#commitToWasmMemory" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -213,7 +213,7 @@ No further store function should be called.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L267">memory.ts:267</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L267">memory.ts:267</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -227,7 +227,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L243">memory.ts:243</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L243">memory.ts:243</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="ptrFromOffset" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>ptr<wbr/>From<wbr/>Offset</span><a href="#ptrFromOffset" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -247,7 +247,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L321">memory.ts:321</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L321">memory.ts:321</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="reset" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>reset</span><a href="#reset" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -258,7 +258,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L252">memory.ts:252</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L252">memory.ts:252</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeF64" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>F64</span><a href="#storeF64" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -273,7 +273,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L360">memory.ts:360</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L360">memory.ts:360</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeI32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>I32</span><a href="#storeI32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -288,7 +288,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L342">memory.ts:342</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L342">memory.ts:342</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeI64" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>I64</span><a href="#storeI64" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -303,7 +303,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L350">memory.ts:350</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L350">memory.ts:350</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storePtr" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>Ptr</span><a href="#storePtr" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -318,7 +318,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L326">memory.ts:326</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L326">memory.ts:326</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>Raw<wbr/>Bytes</span><a href="#storeRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -333,7 +333,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">bytes</span>: <span class="tsd-signature-type ">Uint8Array</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L364">memory.ts:364</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L364">memory.ts:364</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeU32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>U32</span><a href="#storeU32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -348,7 +348,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L346">memory.ts:346</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L346">memory.ts:346</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeUSize" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>storeUSize</span><a href="#storeUSize" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -363,7 +363,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
<h5><span class="tsd-kind-parameter">value</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L334">memory.ts:334</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L334">memory.ts:334</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html b/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
index fc6287f9e4..208e9ca28d 100644
--- a/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
+++ b/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
@@ -30,7 +30,7 @@ which needs to be explicitly disposed.</p>
<ul class="tsd-hierarchy">
<li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L158">webgpu.ts:158</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L158">webgpu.ts:158</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -62,7 +62,7 @@ which needs to be explicitly disposed.</p>
<h5><span class="tsd-kind-parameter">canvas</span>: <span class="tsd-signature-type ">HTMLCanvasElement</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.CanvasRenderManager.html" class="tsd-signature-type tsd-kind-class">CanvasRenderManager</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L167">webgpu.ts:167</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L167">webgpu.ts:167</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="clear" class="tsd-anchor"></a>
@@ -72,7 +72,7 @@ which needs to be explicitly disposed.</p>
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L241">webgpu.ts:241</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L241">webgpu.ts:241</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -86,7 +86,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L317">webgpu.ts:317</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L317">webgpu.ts:317</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="draw" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>draw</span><a href="#draw" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -103,7 +103,7 @@ only the first call will take effect.</p>
<h5><span class="tsd-kind-parameter">width</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L267">webgpu.ts:267</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L267">webgpu.ts:267</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.Environment.html b/docs/reference/api/typedoc/classes/_internal_.Environment.html
index 3066906901..4d84fd1e14 100644
--- a/docs/reference/api/typedoc/classes/_internal_.Environment.html
+++ b/docs/reference/api/typedoc/classes/_internal_.Environment.html
@@ -29,7 +29,7 @@
<ul class="tsd-hierarchy">
<li><a href="../interfaces/LibraryProvider.html" class="tsd-signature-type tsd-kind-interface">LibraryProvider</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L68">environment.ts:68</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L68">environment.ts:68</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -77,7 +77,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4></li></ul></li></ul></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.Environment.html" class="tsd-signature-type tsd-kind-class">Environment</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L88">environment.ts:88</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L88">environment.ts:88</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="imports" class="tsd-anchor"></a>
@@ -88,7 +88,7 @@
<div class="tsd-comment tsd-typography"></div><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/20b08a5c8/web/src/environment.ts#L70">environment.ts:70</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L70">environment.ts:70</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="logger" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>logger</span><a href="#logger" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">logger</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">(</span><span class="tsd-kind-parameter">msg</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol"> => </span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">)</span></div>
@@ -106,7 +106,7 @@
<h5><span class="tsd-kind-parameter">msg</span>: <span class="tsd-signature-type">string</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4></li></ul></li></ul></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L69">environment.ts:69</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L69">environment.ts:69</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="packedCFuncTable" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>packedCFunc<wbr/>Table</span><a href="#packedCFuncTable" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">packedCFunc<wbr/>Table</span><span class="tsd-signature-symbol">:</span> <a href="../types/_internal_.FTVMWasmPackedCFunc.html" class="tsd-signature-type tsd-kind-type-alias">FTVMWasmPackedCFunc</a><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> = ...</span></div>
@@ -117,7 +117,7 @@ of functions that do not maps to the address space.</p>
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L78">environment.ts:78</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L78">environment.ts:78</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="packedCFuncTableFreeId" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>packedCFunc<wbr/>Table<wbr/>Free<wbr/>Id</span><a href="#packedCFuncTableFreeId" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">packedCFunc<wbr/>Table<wbr/>Free<wbr/>Id</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>
@@ -125,7 +125,7 @@ of functions that do not maps to the address space.</p>
</div>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L84">environment.ts:84</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L84">environment.ts:84</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="start" class="tsd-anchor"></a>
@@ -144,7 +144,7 @@ of functions that do not maps to the address space.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/LibraryProvider.html">LibraryProvider</a>.<a href="../interfaces/LibraryProvider.html#start">start</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/environment.ts#L105">environment.ts:105</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/environment.ts#L105">environment.ts:105</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
index 76d1c2730b..29c63935f7 100644
--- a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
+++ b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
@@ -29,7 +29,7 @@
<ul class="tsd-hierarchy">
<li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L43">runtime.ts:43</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L43">runtime.ts:43</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
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@@ -70,29 +70,29 @@
<h5><span class="tsd-kind-parameter">imports</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></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.FFILibrary.html" class="tsd-signature-type tsd-kind-class">FFILibrary</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L51">runtime.ts:51</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L51">runtime.ts:51</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="exports" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>exports</span><a href="#exports" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">exports</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 ">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/20b08a5c8/web/src/runtime.ts#L46">runtime.ts:46</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L46">runtime.ts:46</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="memory" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>memory</span><a href="#memory" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">memory</span><span class="tsd-signature-symbol">:</span> <a href="_internal_.Memory.html" class="tsd-signature-type tsd-kind-class">Memory</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L45">runtime.ts:45</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L45">runtime.ts:45</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="wasm32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>wasm32</span><a href="#wasm32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">wasm32</span><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/20b08a5c8/web/src/runtime.ts#L44">runtime.ts:44</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L44">runtime.ts:44</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="webGPUContext" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><code class="tsd-tag ts-flagOptional">Optional</code> <span>webGPUContext</span><a href="#webGPUContext" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">webGPUContext</span><span class="tsd-signature-symbol">?:</span> <a href="_internal_.WebGPUContext.html" class="tsd-signature-type tsd-kind-class">WebGPUContext</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L47">runtime.ts:47</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L47">runtime.ts:47</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="checkCall" class="tsd-anchor"></a>
@@ -107,7 +107,7 @@
<h5><span class="tsd-kind-parameter">code</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L77">runtime.ts:77</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L77">runtime.ts:77</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -121,7 +121,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L66">runtime.ts:66</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L66">runtime.ts:66</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getOrAllocCallStack" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Or<wbr/>Alloc<wbr/>Call<wbr/>Stack</span><a href="#getOrAllocCallStack" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -129,7 +129,7 @@ only the first call will take effect.</p>
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <a href="_internal_.CachedCallStack.html" class="tsd-signature-type tsd-kind-class">CachedCallStack</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L86">runtime.ts:86</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L86">runtime.ts:86</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="recycleCallStack" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>recycle<wbr/>Call<wbr/>Stack</span><a href="#recycleCallStack" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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@@ -142,7 +142,7 @@ only the first call will take effect.</p>
<h5><span class="tsd-kind-parameter">callstack</span>: <a href="_internal_.CachedCallStack.html" class="tsd-signature-type tsd-kind-class">CachedCallStack</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L97">runtime.ts:97</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L97">runtime.ts:97</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="sizeofPtr" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>sizeof<wbr/>Ptr</span><a href="#sizeofPtr" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -150,7 +150,7 @@ only the first call will take effect.</p>
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L73">runtime.ts:73</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L73">runtime.ts:73</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.Memory.html b/docs/reference/api/typedoc/classes/_internal_.Memory.html
index 3132eb6814..5844dc4b20 100644
--- a/docs/reference/api/typedoc/classes/_internal_.Memory.html
+++ b/docs/reference/api/typedoc/classes/_internal_.Memory.html
@@ -25,7 +25,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">Memory</span></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L31">memory.ts:31</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L31">memory.ts:31</a></li></ul></aside>
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@@ -71,19 +71,19 @@
<h5><span class="tsd-kind-parameter">memory</span>: <span class="tsd-signature-type ">Memory</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.Memory.html" class="tsd-signature-type tsd-kind-class">Memory</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L42">memory.ts:42</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L42">memory.ts:42</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="memory" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>memory</span><a href="#memory" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">memory</span><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/20b08a5c8/web/src/memory.ts#L32">memory.ts:32</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L32">memory.ts:32</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="wasm32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>wasm32</span><a href="#wasm32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">wasm32</span><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/20b08a5c8/web/src/memory.ts#L33">memory.ts:33</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L33">memory.ts:33</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="loadCString" class="tsd-anchor"></a>
@@ -104,7 +104,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L154">memory.ts:154</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L154">memory.ts:154</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadF32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>F32</span><a href="#loadF32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -117,7 +117,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L90">memory.ts:90</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L90">memory.ts:90</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadF64" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>F64</span><a href="#loadF64" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -130,7 +130,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L97">memory.ts:97</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L97">memory.ts:97</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadI32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>I32</span><a href="#loadI32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -143,7 +143,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L74">memory.ts:74</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L74">memory.ts:74</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadI64" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>I64</span><a href="#loadI64" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -156,7 +156,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L81">memory.ts:81</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L81">memory.ts:81</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadPointer" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>Pointer</span><a href="#loadPointer" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -169,7 +169,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L104">memory.ts:104</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L104">memory.ts:104</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>Raw<wbr/>Bytes</span><a href="#loadRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -193,7 +193,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Uint8Array</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L132">memory.ts:132</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L132">memory.ts:132</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadTVMBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>loadTVMBytes</span><a href="#loadTVMBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -212,7 +212,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Uint8Array</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L145">memory.ts:145</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L145">memory.ts:145</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadU16" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>U16</span><a href="#loadU16" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -225,7 +225,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L60">memory.ts:60</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L60">memory.ts:60</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadU32" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>U32</span><a href="#loadU32" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -238,7 +238,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L67">memory.ts:67</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L67">memory.ts:67</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadU8" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>load<wbr/>U8</span><a href="#loadU8" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -251,7 +251,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L53">memory.ts:53</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L53">memory.ts:53</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="loadUSize" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>loadUSize</span><a href="#loadUSize" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -264,7 +264,7 @@
<h5><span class="tsd-kind-parameter">ptr</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L114">memory.ts:114</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L114">memory.ts:114</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="sizeofPtr" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>sizeof<wbr/>Ptr</span><a href="#sizeofPtr" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -272,7 +272,7 @@
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L124">memory.ts:124</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L124">memory.ts:124</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="storeRawBytes" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>store<wbr/>Raw<wbr/>Bytes</span><a href="#storeRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -296,7 +296,7 @@
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/memory.ts#L175">memory.ts:175</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/memory.ts#L175">memory.ts:175</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html b/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html
index cea1ab43c6..c44594e8b7 100644
--- a/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html
+++ b/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html
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<ul class="tsd-hierarchy">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L291">runtime.ts:291</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L291">runtime.ts:291</a></li></ul></aside>
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<section class="tsd-panel tsd-index-panel">
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<h5><span class="tsd-kind-parameter">lib</span>: <a href="_internal_.FFILibrary.html" class="tsd-signature-type tsd-kind-class">FFILibrary</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.PackedFuncCell.html" class="tsd-signature-type tsd-kind-class">PackedFuncCell</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L295">runtime.ts:295</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L295">runtime.ts:295</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
@@ -76,7 +76,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L300">runtime.ts:300</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L300">runtime.ts:300</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -89,7 +89,7 @@ only the first call will take effect.</p>
<h5><span class="tsd-kind-parameter">requireNotNull</span>: <span class="tsd-signature-type">boolean</span><span class="tsd-signature-symbol"> = true</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L309">runtime.ts:309</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L309">runtime.ts:309</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html b/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html
index 83a49dfbe7..90c93a0283 100644
--- a/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html
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<ul class="tsd-hierarchy">
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<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L143">runtime.ts:143</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L143">runtime.ts:143</a></li></ul></aside>
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<h4 class="tsd-returns-title">Returns <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></h4></li></ul></li></ul></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.RuntimeContext.html" class="tsd-signature-type tsd-kind-class">RuntimeContext</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L165">runtime.ts:165</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L165">runtime.ts:165</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="applyRepetitionPenalty" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>apply<wbr/>Repetition<wbr/>Penalty</span><a href="#applyRepetitionPenalty" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">apply<wbr/>Repetition<wbr/>Penalty</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L160">runtime.ts:160</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L160">runtime.ts:160</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="applySoftmaxWithTemperature" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>apply<wbr/>Softmax<wbr/>With<wbr/>Temperature</span><a href="#applySoftmaxWithTemperature" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">apply<wbr/>Softmax<wbr/>With<wbr/>Temperature</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L161">runtime.ts:161</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L161">runtime.ts:161</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayCacheClear" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Cache<wbr/>Clear</span><a href="#arrayCacheClear" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Cache<wbr/>Clear</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L153">runtime.ts:153</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L153">runtime.ts:153</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayCacheGet" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Cache<wbr/>Get</span><a href="#arrayCacheGet" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Cache<wbr/>Get</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L150">runtime.ts:150</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L150">runtime.ts:150</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayCacheRemove" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Cache<wbr/>Remove</span><a href="#arrayCacheRemove" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Cache<wbr/>Remove</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L152">runtime.ts:152</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L152">runtime.ts:152</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayCacheUpdate" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Cache<wbr/>Update</span><a href="#arrayCacheUpdate" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Cache<wbr/>Update</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L151">runtime.ts:151</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L151">runtime.ts:151</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayDecodeStorage" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Decode<wbr/>Storage</span><a href="#arrayDecodeStorage" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Decode<wbr/>Storage</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L154">runtime.ts:154</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L154">runtime.ts:154</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayGetItem" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Get<wbr/>Item</span><a href="#arrayGetItem" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Get<wbr/>Item</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L144">runtime.ts:144</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L144">runtime.ts:144</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayGetSize" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Get<wbr/>Size</span><a href="#arrayGetSize" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Get<wbr/>Size</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L145">runtime.ts:145</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L145">runtime.ts:145</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="arrayMake" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>array<wbr/>Make</span><a href="#arrayMake" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">array<wbr/>Make</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L146">runtime.ts:146</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L146">runtime.ts:146</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="getFFIString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>getFFIString</span><a href="#getFFIString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">getFFIString</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L148">runtime.ts:148</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L148">runtime.ts:148</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="getSysLib" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Sys<wbr/>Lib</span><a href="#getSysLib" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">get<wbr/>Sys<wbr/>Lib</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L149">runtime.ts:149</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L149">runtime.ts:149</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="makeShapeTuple" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>make<wbr/>Shape<wbr/>Tuple</span><a href="#makeShapeTuple" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">make<wbr/>Shape<wbr/>Tuple</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L157">runtime.ts:157</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L157">runtime.ts:157</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="ndarrayCreateView" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>ndarray<wbr/>Create<wbr/>View</span><a href="#ndarrayCreateView" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">ndarray<wbr/>Create<wbr/>View</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L158">runtime.ts:158</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L158">runtime.ts:158</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="paramModuleFromCache" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>param<wbr/>Module<wbr/>From<wbr/>Cache</span><a href="#paramModuleFromCache" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">param<wbr/>Module<wbr/>From<wbr/>Cache</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L155">runtime.ts:155</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L155">runtime.ts:155</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="paramModuleFromCacheByName" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>param<wbr/>Module<wbr/>From<wbr/>Cache<wbr/>By<wbr/>Name</span><a href="#paramModuleFromCacheByName" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">param<wbr/>Module<wbr/>From<wbr/>Cache<wbr/>By<wbr/>Name</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L156">runtime.ts:156</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L156">runtime.ts:156</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="sampleTopPFromLogits" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>sample<wbr/>TopPFrom<wbr/>Logits</span><a href="#sampleTopPFromLogits" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">sample<wbr/>TopPFrom<wbr/>Logits</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="stringMake" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>string<wbr/>Make</span><a href="#stringMake" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">string<wbr/>Make</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L147">runtime.ts:147</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L147">runtime.ts:147</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="attachToCurrentScope" class="tsd-anchor"></a>
@@ -216,7 +216,7 @@
The return value of PackedFunc will be automatically tracked.</p>
</div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L234">runtime.ts:234</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L234">runtime.ts:234</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="beginScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>begin<wbr/>Scope</span><a href="#beginScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -224,7 +224,7 @@
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L208">runtime.ts:208</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L208">runtime.ts:208</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="detachFromCurrentScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>detach<wbr/>From<wbr/>Current<wbr/>Scope</span><a href="#detachFromCurrentScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -242,7 +242,7 @@
<h5><span class="tsd-kind-parameter">obj</span>: <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L253">runtime.ts:253</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L253">runtime.ts:253</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -256,7 +256,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L186">runtime.ts:186</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L186">runtime.ts:186</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="endScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>end<wbr/>Scope</span><a href="#endScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -264,7 +264,7 @@ only the first call will take effect.</p>
<li class="tsd-description">
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L212">runtime.ts:212</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L212">runtime.ts:212</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="moveToParentScope" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>move<wbr/>To<wbr/>Parent<wbr/>Scope</span><a href="#moveToParentScope" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -282,7 +282,7 @@ only the first call will take effect.</p>
<h5><span class="tsd-kind-parameter">obj</span>: <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L243">runtime.ts:243</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L243">runtime.ts:243</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.TVMString.html b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
index 9af247c635..a4265246f0 100644
--- a/docs/reference/api/typedoc/classes/_internal_.TVMString.html
+++ b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
@@ -27,7 +27,7 @@
<ul class="tsd-hierarchy">
<li><span class="target">TVMString</span></li></ul></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L886">runtime.ts:886</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L886">runtime.ts:886</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -64,7 +64,7 @@
<h4 class="tsd-returns-title">Returns <a href="_internal_.TVMString.html" class="tsd-signature-type tsd-kind-class">TVMString</a></h4><aside class="tsd-sources">
<p>Overrides <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#constructor">constructor</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L887">runtime.ts:887</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L887">runtime.ts:887</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="dispose" class="tsd-anchor"></a>
@@ -80,7 +80,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#dispose">dispose</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L791">runtime.ts:791</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="getHandle" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -101,7 +101,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#getHandle">getHandle</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L806">runtime.ts:806</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="toString" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>to<wbr/>String</span><a href="#toString" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -111,7 +111,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L898">runtime.ts:898</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L898">runtime.ts:898</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="typeIndex" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Index</span><a href="#typeIndex" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -123,7 +123,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#typeIndex">typeIndex</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L814">runtime.ts:814</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member tsd-is-inherited"><a id="typeKey" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>type<wbr/>Key</span><a href="#typeKey" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures tsd-is-inherited">
@@ -135,7 +135,7 @@ only the first call will take effect.</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#typeKey">typeKey</a></p>
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
<div class="col-sidebar">
<div class="page-menu">
<div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html b/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
index 7753fc8a14..17d9f9f725 100644
--- a/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
+++ b/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
@@ -26,7 +26,7 @@ Manages all the webgpu resources here.</p>
<ul class="tsd-hierarchy">
<li><span class="target">WebGPUContext</span></li></ul></section><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L335">webgpu.ts:335</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L335">webgpu.ts:335</a></li></ul></aside>
<section class="tsd-panel-group tsd-index-group">
<section class="tsd-panel tsd-index-panel">
<details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -70,19 +70,19 @@ Manages all the webgpu resources here.</p>
<h5><span class="tsd-kind-parameter">device</span>: <span class="tsd-signature-type ">GPUDevice</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <a href="_internal_.WebGPUContext.html" class="tsd-signature-type tsd-kind-class">WebGPUContext</a></h4><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L360">webgpu.ts:360</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L360">webgpu.ts:360</a></li></ul></aside></li></ul></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Properties</h2>
<section class="tsd-panel tsd-member"><a id="device" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>device</span><a href="#device" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">device</span><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/20b08a5c8/web/src/webgpu.ts#L336">webgpu.ts:336</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L336">webgpu.ts:336</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="memory" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>memory</span><a href="#memory" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<div class="tsd-signature"><span class="tsd-kind-property">memory</span><span class="tsd-signature-symbol">:</span> <a href="_internal_.Memory.html" class="tsd-signature-type tsd-kind-class">Memory</a></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L337">webgpu.ts:337</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L337">webgpu.ts:337</a></li></ul></aside></section></section>
<section class="tsd-panel-group tsd-member-group">
<h2>Methods</h2>
<section class="tsd-panel tsd-member"><a id="bindCanvas" class="tsd-anchor"></a>
@@ -103,7 +103,7 @@ Manages all the webgpu resources here.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L444">webgpu.ts:444</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L444">webgpu.ts:444</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="clearCanvas" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>clear<wbr/>Canvas</span><a href="#clearCanvas" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -114,7 +114,7 @@ Manages all the webgpu resources here.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L436">webgpu.ts:436</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L436">webgpu.ts:436</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="copyRawBytesToBuffer" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>copy<wbr/>Raw<wbr/>Bytes<wbr/>To<wbr/>Buffer</span><a href="#copyRawBytesToBuffer" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -148,7 +148,7 @@ Manages all the webgpu resources here.</p>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L418">webgpu.ts:418</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L418">webgpu.ts:418</a></li></ul></aside></li></ul></section>
<section class="tsd-panel tsd-member"><a id="createShader" class="tsd-anchor"></a>
<h3 class="tsd-anchor-link"><span>create<wbr/>Shader</span><a href="#createShader" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
<ul class="tsd-signatures">
@@ -171,7 +171,7 @@ via createComputePipeline</p>
<div class="tsd-comment tsd-typography"></div><aside class="tsd-sources">
<ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L456">webgpu.ts:456</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L2417">runtime.ts:2417</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L28">webgpu.ts:28</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L29">webgpu.ts:29</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L29">webgpu.ts:29</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L30">webgpu.ts:30</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L976">runtime.ts:976</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L979">runtime.ts:979</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L979">runtime.ts:979</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L977">runtime.ts:977</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L977">runtime.ts:977</a></li></ul></aside></section>
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<h3 class="tsd-anchor-link"><span>text</span><a href="#text" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L980">runtime.ts:980</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L980">runtime.ts:980</a></li></ul></aside></section>
<section class="tsd-panel tsd-member"><a id="timeElapsed" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L978">runtime.ts:978</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/interfaces/LibraryProvider.html b/docs/reference/api/typedoc/interfaces/LibraryProvider.html
index 2205265147..41a73f6ae9 100644
--- a/docs/reference/api/typedoc/interfaces/LibraryProvider.html
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/types.ts#L32">types.ts:32</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/types.ts#L34">types.ts:34</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/types.ts#L34">types.ts:34</a></li></ul></aside></section>
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<h3 class="tsd-anchor-link"><span>start</span><a href="#start" aria-label="Permalink" class="tsd-anchor-icon"><svg viewBox="0 0 24 24"><use href="#icon-anchor"></use></svg></a></h3>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/types.ts#L39">types.ts:39</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/interfaces/_internal_.FunctionInfo.html b/docs/reference/api/typedoc/interfaces/_internal_.FunctionInfo.html
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L325">webgpu.ts:325</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L327">webgpu.ts:327</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/webgpu.ts#L328">webgpu.ts:328</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L328">webgpu.ts:328</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/webgpu.ts#L326">webgpu.ts:326</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/interfaces/_internal_.NDArrayCacheEntry.html b/docs/reference/api/typedoc/interfaces/_internal_.NDArrayCacheEntry.html
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L960">runtime.ts:960</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L965">runtime.ts:965</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L965">runtime.ts:965</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L963">runtime.ts:963</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L963">runtime.ts:963</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L964">runtime.ts:964</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L964">runtime.ts:964</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L961">runtime.ts:961</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L961">runtime.ts:961</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/20b08a5c8/web/src/runtime.ts#L966">runtime.ts:966</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L966">runtime.ts:966</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L962">runtime.ts:962</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L969">runtime.ts:969</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/runtime.ts#L970">runtime.ts:970</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/ctypes.ts#L194">ctypes.ts:194</a></li></ul></aside></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/ctypes.ts#L206">ctypes.ts:206</a></li></ul></aside></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0e8e42176/web/src/ctypes.ts#L25">ctypes.ts:25</a></li></ul></aside></div>
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diff --git a/docs/topic/vta/tutorials/autotvm/sg_execution_times.html b/docs/topic/vta/tutorials/autotvm/sg_execution_times.html
index 31969b2d56..5bbe447932 100644
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+++ b/docs/topic/vta/tutorials/autotvm/sg_execution_times.html
@@ -360,7 +360,7 @@
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<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>00:36.336</strong> total execution time for <strong>topic_vta_tutorials_autotvm</strong> files:</p>
+<p><strong>00:38.172</strong> total execution time for <strong>topic_vta_tutorials_autotvm</strong> files:</p>
<table class="docutils align-default">
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<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>
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diff --git a/docs/topic/vta/tutorials/frontend/deploy_classification.html b/docs/topic/vta/tutorials/frontend/deploy_classification.html
index 1f707997e2..27ca12d76c 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_classification.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_classification.html
@@ -603,7 +603,7 @@ and dense layer which will both be executed in fp32 on the CPU.</p></li>
warnings.warn(
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graph, lib, params = relay.build(
-resnet18_v1 inference graph built in 38.34s!
+resnet18_v1 inference graph built in 40.96s!
</pre></div>
</div>
</div>
@@ -700,6 +700,7 @@ resnet18_v1 prediction for sample 0
#5: Persian cat
</pre></div>
</div>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 2.076 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-topic-vta-tutorials-frontend-deploy-classification-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../../../_downloads/9e8de33a5822b31748bfd76861009f92/deploy_classification.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_classification.py</span></code></a></p>
diff --git a/docs/topic/vta/tutorials/frontend/deploy_detection.html b/docs/topic/vta/tutorials/frontend/deploy_detection.html
index f2263df7ae..e7237e6c0f 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_detection.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_detection.html
@@ -621,7 +621,7 @@ and dense layer which will both be executed in fp32 on the CPU.</p></li>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/relay/build_module.py:345: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
warnings.warn(
-yolov3-tiny inference graph built in 26.14s!
+yolov3-tiny inference graph built in 27.86s!
</pre></div>
</div>
</div>
@@ -706,6 +706,7 @@ Download test image</p>
alu_counter : 849056
</pre></div>
</div>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 2.192 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-topic-vta-tutorials-frontend-deploy-detection-py">
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diff --git a/docs/topic/vta/tutorials/frontend/sg_execution_times.html b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
index 68be8cf90a..2aa0b5b7d8 100644
--- a/docs/topic/vta/tutorials/frontend/sg_execution_times.html
+++ b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
@@ -360,7 +360,7 @@
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<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>01:59.207</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
+<p><strong>02:04.268</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -369,11 +369,11 @@
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<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>00:59.840</p></td>
+<td><p>01:02.192</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>00:59.367</p></td>
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<td><p>0.0 MB</p></td>
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diff --git a/docs/topic/vta/tutorials/optimize/sg_execution_times.html b/docs/topic/vta/tutorials/optimize/sg_execution_times.html
index 10a203b6d1..8e0f40ac23 100644
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@@ -360,7 +360,7 @@
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-<p><strong>00:03.387</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
+<p><strong>00:03.445</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
<table class="docutils align-default">
<colgroup>
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@@ -369,11 +369,11 @@
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-<td><p>00:00.540</p></td>
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<td><p>0.0 MB</p></td>
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+++ b/docs/topic/vta/tutorials/sg_execution_times.html
@@ -360,7 +360,7 @@
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-<p><strong>00:00.885</strong> total execution time for <strong>topic_vta_tutorials</strong> files:</p>
+<p><strong>00:00.890</strong> total execution time for <strong>topic_vta_tutorials</strong> files:</p>
<table class="docutils align-default">
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@@ -373,7 +373,7 @@
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-<td><p>00:00.428</p></td>
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<td><p>0.0 MB</p></td>
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diff --git a/docs/tutorial/auto_scheduler_matmul_x86.html b/docs/tutorial/auto_scheduler_matmul_x86.html
index 16d4679a6f..7871da243a 100644
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@@ -664,7 +664,7 @@ automatically optimize a matrix multiplication, without the need to specify a
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-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 34.065 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 34.526 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-auto-scheduler-matmul-x86-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../_downloads/eac4389b114db015e95cb3cdf8b86b83/auto_scheduler_matmul_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">auto_scheduler_matmul_x86.py</span></code></a></p>
diff --git a/docs/tutorial/autotvm_matmul_x86.html b/docs/tutorial/autotvm_matmul_x86.html
index 3079a5e806..8e5066579f 100644
--- a/docs/tutorial/autotvm_matmul_x86.html
+++ b/docs/tutorial/autotvm_matmul_x86.html
@@ -700,16 +700,16 @@ 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: 14.10/14.10 result: MeasureResult(costs=(0.0190400884,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.580122709274292, timestamp=1706130149.3779674) [('tile_y', [-1, 16]), ('tile_x', [-1, 32])],None,54
-No: 2 GFLOPS: 11.94/14.10 result: MeasureResult(costs=(0.022479538,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6436622142791748, timestamp=1706130149.9956682) [('tile_y', [-1, 16]), ('tile_x', [-1, 16])],None,44
-No: 3 GFLOPS: 0.50/14.10 result: MeasureResult(costs=(0.5322868688,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.790831089019775, timestamp=1706130158.769511) [('tile_y', [-1, 64]), ('tile_x', [-1, 1])],None,6
-No: 4 GFLOPS: 10.39/14.10 result: MeasureResult(costs=(0.0258306808,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6614129543304443, timestamp=1706130159.4383698) [('tile_y', [-1, 2]), ('tile_x', [-1, 32])],None,51
-No: 5 GFLOPS: 12.19/14.10 result: MeasureResult(costs=(0.022020926399999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6428756713867188, timestamp=1706130160.20137) [('tile_y', [-1, 16]), ('tile_x', [-1, 512])],None,94
-No: 6 GFLOPS: 0.51/14.10 result: MeasureResult(costs=(0.5267534702,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.69219446182251, timestamp=1706130168.885319) [('tile_y', [-1, 128]), ('tile_x', [-1, 1])],None,7
-No: 7 GFLOPS: 2.03/14.10 result: MeasureResult(costs=(0.13219608639999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.375584840774536, timestamp=1706130171.2571223) [('tile_y', [-1, 256]), ('tile_x', [-1, 4])],None,28
-No: 8 GFLOPS: 10.57/14.10 result: MeasureResult(costs=(0.0254025296,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.672905445098877, timestamp=1706130171.9207823) [('tile_y', [-1, 4]), ('tile_x', [-1, 16])],None,42
-No: 9 GFLOPS: 7.08/14.10 result: MeasureResult(costs=(0.037902027,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8327691555023193, timestamp=1706130172.897419) [('tile_y', [-1, 512]), ('tile_x', [-1, 16])],None,49
-No: 10 GFLOPS: 10.59/14.10 result: MeasureResult(costs=(0.0253424534,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6769700050354004, timestamp=1706130173.5764592) [('tile_y', [-1, 512]), ('tile_x', [-1, 128])],None,79
+No: 1 GFLOPS: 6.56/6.56 result: MeasureResult(costs=(0.0409415574,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.9388835430145264, timestamp=1706133341.0289698) [('tile_y', [-1, 512]), ('tile_x', [-1, 16])],None,49
+No: 2 GFLOPS: 10.19/10.19 result: MeasureResult(costs=(0.0263439514,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6993741989135742, timestamp=1706133341.7222872) [('tile_y', [-1, 256]), ('tile_x', [-1, 256])],None,88
+No: 3 GFLOPS: 4.17/10.19 result: MeasureResult(costs=(0.0643350868,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.2908637523651123, timestamp=1706133343.0160563) [('tile_y', [-1, 8]), ('tile_x', [-1, 2])],None,13
+No: 4 GFLOPS: 0.50/10.19 result: MeasureResult(costs=(0.5337769556,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.848292589187622, timestamp=1706133351.8224938) [('tile_y', [-1, 64]), ('tile_x', [-1, 1])],None,6
+No: 5 GFLOPS: 7.33/10.19 result: MeasureResult(costs=(0.0366167326,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8683803081512451, timestamp=1706133352.8719246) [('tile_y', [-1, 32]), ('tile_x', [-1, 16])],None,45
+No: 6 GFLOPS: 9.59/10.19 result: MeasureResult(costs=(0.027996526799999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7172234058380127, timestamp=1706133353.5950336) [('tile_y', [-1, 512]), ('tile_x', [-1, 512])],None,99
+No: 7 GFLOPS: 11.55/11.55 result: MeasureResult(costs=(0.023241088,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7203757762908936, timestamp=1706133354.237779) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
+No: 8 GFLOPS: 11.04/11.55 result: MeasureResult(costs=(0.0243240294,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6621172428131104, timestamp=1706133354.9001226) [('tile_y', [-1, 4]), ('tile_x', [-1, 512])],None,92
+No: 9 GFLOPS: 11.52/11.55 result: MeasureResult(costs=(0.0233106398,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6365814208984375, timestamp=1706133355.6678193) [('tile_y', [-1, 16]), ('tile_x', [-1, 512])],None,94
+No: 10 GFLOPS: 10.38/11.55 result: MeasureResult(costs=(0.0258532104,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6926472187042236, timestamp=1706133356.3468945) [('tile_y', [-1, 8]), ('tile_x', [-1, 64])],None,63
</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 1ae2f0cbd0..2381fd5020 100644
--- a/docs/tutorial/autotvm_relay_x86.html
+++ b/docs/tutorial/autotvm_relay_x86.html
@@ -578,7 +578,7 @@ 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': 494.9741758199889, 'median': 495.114422450024, 'std': 1.1117048733914823}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{'mean': 500.58081771001525, 'median': 500.23290955004995, 'std': 1.5838218019673596}
</pre></div>
</div>
</div>
@@ -767,178 +767,178 @@ depending on the specifics of the model and the target platform.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 1/25] Current/Best: 15.26/ 15.34 GFLOPS | Progress: (4/20) | 8.54 s
-[Task 1/25] Current/Best: 8.85/ 22.41 GFLOPS | Progress: (8/20) | 11.99 s
-[Task 1/25] Current/Best: 18.81/ 22.42 GFLOPS | Progress: (12/20) | 14.88 s
-[Task 1/25] Current/Best: 7.65/ 22.42 GFLOPS | Progress: (16/20) | 18.27 s
-[Task 1/25] Current/Best: 14.50/ 23.43 GFLOPS | Progress: (20/20) | 20.58 s Done.
+[Task 1/25] Current/Best: 13.75/ 17.07 GFLOPS | Progress: (4/20) | 8.90 s
+[Task 1/25] Current/Best: 20.87/ 23.99 GFLOPS | Progress: (8/20) | 11.51 s
+[Task 1/25] Current/Best: 5.45/ 23.99 GFLOPS | Progress: (12/20) | 15.29 s
+[Task 1/25] Current/Best: 16.01/ 23.99 GFLOPS | Progress: (16/20) | 17.35 s
+[Task 1/25] Current/Best: 3.41/ 23.99 GFLOPS | Progress: (20/20) | 26.23 s Done.
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 2/25] Current/Best: 17.84/ 22.44 GFLOPS | Progress: (4/20) | 3.90 s
-[Task 2/25] Current/Best: 17.13/ 22.44 GFLOPS | Progress: (8/20) | 5.56 s
-[Task 2/25] Current/Best: 19.46/ 22.44 GFLOPS | Progress: (12/20) | 7.32 s
-[Task 2/25] Current/Best: 14.08/ 22.44 GFLOPS | Progress: (16/20) | 8.94 s
-[Task 2/25] Current/Best: 6.68/ 22.44 GFLOPS | Progress: (20/20) | 10.40 s Done.
+[Task 2/25] Current/Best: 13.02/ 13.02 GFLOPS | Progress: (4/20) | 4.34 s
+[Task 2/25] Current/Best: 2.14/ 17.98 GFLOPS | Progress: (8/20) | 5.87 s
+[Task 2/25] Current/Best: 7.67/ 17.98 GFLOPS | Progress: (12/20) | 7.88 s
+[Task 2/25] Current/Best: 7.65/ 17.98 GFLOPS | Progress: (16/20) | 9.40 s
+[Task 2/25] Current/Best: 15.07/ 17.98 GFLOPS | Progress: (20/20) | 12.27 s Done.
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 3/25] Current/Best: 20.68/ 20.68 GFLOPS | Progress: (4/20) | 4.66 s
-[Task 3/25] Current/Best: 15.27/ 23.60 GFLOPS | Progress: (8/20) | 6.70 s
-[Task 3/25] Current/Best: 14.72/ 23.60 GFLOPS | Progress: (12/20) | 9.37 s
-[Task 3/25] Current/Best: 19.77/ 23.60 GFLOPS | Progress: (16/20) | 11.34 s
-[Task 3/25] Current/Best: 10.73/ 23.60 GFLOPS | Progress: (20/20) | 13.66 s Done.
+[Task 3/25] Current/Best: 9.96/ 21.91 GFLOPS | Progress: (4/20) | 4.87 s
+[Task 3/25] Current/Best: 6.81/ 21.91 GFLOPS | Progress: (8/20) | 7.77 s
+[Task 3/25] Current/Best: 19.15/ 21.91 GFLOPS | Progress: (12/20) | 10.05 s
+[Task 3/25] Current/Best: 23.71/ 23.71 GFLOPS | Progress: (16/20) | 12.40 s
+[Task 3/25] Current/Best: 23.02/ 23.71 GFLOPS | Progress: (20/20) | 14.68 s Done.
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 4/25] Current/Best: 18.42/ 21.78 GFLOPS | Progress: (4/20) | 4.55 s
-[Task 4/25] Current/Best: 23.77/ 23.77 GFLOPS | Progress: (8/20) | 7.47 s
-[Task 4/25] Current/Best: 17.35/ 23.77 GFLOPS | Progress: (12/20) | 12.74 s
-[Task 4/25] Current/Best: 17.67/ 23.77 GFLOPS | Progress: (16/20) | 15.60 s
-[Task 4/25] Current/Best: 13.88/ 23.77 GFLOPS | Progress: (20/20) | 18.33 s Done.
+[Task 4/25] Current/Best: 14.05/ 18.35 GFLOPS | Progress: (4/20) | 4.44 s
+[Task 4/25] Current/Best: 5.23/ 18.35 GFLOPS | Progress: (8/20) | 6.61 s
+[Task 4/25] Current/Best: 16.58/ 18.35 GFLOPS | Progress: (12/20) | 8.59 s
+[Task 4/25] Current/Best: 10.58/ 20.44 GFLOPS | Progress: (16/20) | 13.73 s
+[Task 4/25] Current/Best: 13.74/ 20.44 GFLOPS | Progress: (20/20) | 19.03 s Done.
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 5/25] Current/Best: 3.35/ 16.27 GFLOPS | Progress: (4/20) | 4.58 s
-[Task 5/25] Current/Best: 6.02/ 18.50 GFLOPS | Progress: (8/20) | 6.33 s
-[Task 5/25] Current/Best: 5.17/ 21.51 GFLOPS | Progress: (12/20) | 8.20 s
-[Task 5/25] Current/Best: 15.40/ 21.51 GFLOPS | Progress: (16/20) | 9.90 s
-[Task 5/25] Current/Best: 13.38/ 21.51 GFLOPS | Progress: (20/20) | 12.03 s Done.
+[Task 5/25] Current/Best: 5.47/ 13.39 GFLOPS | Progress: (4/20) | 4.74 s
+[Task 5/25] Current/Best: 3.65/ 14.05 GFLOPS | Progress: (8/20) | 7.11 s
+[Task 5/25] Current/Best: 19.26/ 19.89 GFLOPS | Progress: (12/20) | 9.19 s
+[Task 5/25] Current/Best: 17.43/ 19.89 GFLOPS | Progress: (16/20) | 11.60 s
+[Task 5/25] Current/Best: 14.85/ 19.89 GFLOPS | Progress: (20/20) | 13.50 s Done.
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 6/25] Current/Best: 6.36/ 13.09 GFLOPS | Progress: (4/20) | 5.20 s
-[Task 6/25] Current/Best: 4.07/ 18.16 GFLOPS | Progress: (8/20) | 8.24 s
-[Task 6/25] Current/Best: 21.58/ 21.58 GFLOPS | Progress: (12/20) | 10.49 s
-[Task 6/25] Current/Best: 8.68/ 21.58 GFLOPS | Progress: (16/20) | 13.30 s
-[Task 6/25] Current/Best: 7.99/ 21.58 GFLOPS | Progress: (20/20) | 15.62 s Done.
+[Task 6/25] Current/Best: 8.41/ 12.74 GFLOPS | Progress: (4/20) | 6.38 s
+[Task 6/25] Current/Best: 10.36/ 16.74 GFLOPS | Progress: (8/20) | 9.05 s
+[Task 6/25] Current/Best: 11.92/ 16.74 GFLOPS | Progress: (12/20) | 12.43 s
+[Task 6/25] Current/Best: 7.61/ 16.74 GFLOPS | Progress: (16/20) | 15.23 s
+[Task 6/25] Current/Best: 13.21/ 20.13 GFLOPS | Progress: (20/20) | 17.95 s Done.
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 7/25] Current/Best: 8.82/ 19.03 GFLOPS | Progress: (4/20) | 5.79 s
-[Task 7/25] Current/Best: 19.13/ 19.46 GFLOPS | Progress: (8/20) | 8.19 s
-[Task 7/25] Current/Best: 5.08/ 19.81 GFLOPS | Progress: (12/20) | 10.68 s
-[Task 7/25] Current/Best: 14.31/ 20.61 GFLOPS | Progress: (16/20) | 13.27 s
-[Task 7/25] Current/Best: 9.17/ 21.24 GFLOPS | Progress: (20/20) | 15.45 s Done.
+[Task 7/25] Current/Best: 18.64/ 18.64 GFLOPS | Progress: (4/20) | 4.92 s
+[Task 7/25] Current/Best: 14.86/ 18.64 GFLOPS | Progress: (8/20) | 7.79 s
+[Task 7/25] Current/Best: 11.98/ 18.64 GFLOPS | Progress: (12/20) | 10.19 s
+[Task 7/25] Current/Best: 7.63/ 18.80 GFLOPS | Progress: (16/20) | 12.88 s
+[Task 7/25] Current/Best: 21.08/ 21.08 GFLOPS | Progress: (20/20) | 15.67 s Done.
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 8/25] Current/Best: 12.12/ 17.01 GFLOPS | Progress: (4/20) | 5.46 s
-[Task 8/25] Current/Best: 6.64/ 17.01 GFLOPS | Progress: (8/20) | 12.46 s
-[Task 8/25] Current/Best: 4.25/ 17.01 GFLOPS | Progress: (12/20) | 24.25 s
-[Task 8/25] Current/Best: 10.60/ 17.01 GFLOPS | Progress: (16/20) | 27.51 s
-[Task 8/25] Current/Best: 5.22/ 17.55 GFLOPS | Progress: (20/20) | 30.02 s Done.
+[Task 8/25] Current/Best: 8.57/ 11.98 GFLOPS | Progress: (4/20) | 6.05 s
+[Task 8/25] Current/Best: 8.32/ 13.07 GFLOPS | Progress: (8/20) | 9.49 s
+[Task 8/25] Current/Best: 10.40/ 13.45 GFLOPS | Progress: (12/20) | 13.03 s
+[Task 8/25] Current/Best: 12.63/ 16.17 GFLOPS | Progress: (16/20) | 16.67 s
+[Task 8/25] Current/Best: 5.97/ 16.17 GFLOPS | Progress: (20/20) | 24.67 s Done.
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 9/25] Current/Best: 7.56/ 16.45 GFLOPS | Progress: (4/20) | 10.60 s
-[Task 9/25] Current/Best: 11.54/ 18.14 GFLOPS | Progress: (8/20) | 12.33 s
-[Task 9/25] Current/Best: 11.97/ 18.14 GFLOPS | Progress: (12/20) | 19.85 s
-[Task 9/25] Current/Best: 17.41/ 18.14 GFLOPS | Progress: (16/20) | 21.55 s
-[Task 9/25] Current/Best: 16.36/ 19.84 GFLOPS | Progress: (20/20) | 24.72 s Done.
+[Task 9/25] Current/Best: 10.03/ 21.53 GFLOPS | Progress: (4/20) | 6.21 s
+[Task 9/25] Current/Best: 12.19/ 21.53 GFLOPS | Progress: (8/20) | 11.47 s
+[Task 9/25] Current/Best: 18.77/ 21.53 GFLOPS | Progress: (12/20) | 14.33 s
+[Task 9/25] Current/Best: 8.40/ 21.53 GFLOPS | Progress: (16/20) | 17.08 s
+[Task 9/25] Current/Best: 8.87/ 21.53 GFLOPS | Progress: (20/20) | 22.87 s Done.
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 10/25] Current/Best: 14.65/ 20.59 GFLOPS | Progress: (4/20) | 4.38 s
-[Task 10/25] Current/Best: 5.27/ 20.59 GFLOPS | Progress: (8/20) | 6.27 s
-[Task 10/25] Current/Best: 8.23/ 20.59 GFLOPS | Progress: (12/20) | 8.19 s
-[Task 10/25] Current/Best: 17.69/ 20.59 GFLOPS | Progress: (16/20) | 11.94 s
-[Task 10/25] Current/Best: 14.35/ 20.59 GFLOPS | Progress: (20/20) | 14.34 s Done.
+[Task 10/25] Current/Best: 16.59/ 16.59 GFLOPS | Progress: (4/20) | 4.51 s
+[Task 10/25] Current/Best: 14.80/ 16.59 GFLOPS | Progress: (8/20) | 7.33 s
+[Task 10/25] Current/Best: 5.74/ 18.28 GFLOPS | Progress: (12/20) | 9.69 s
+[Task 10/25] Current/Best: 18.15/ 19.47 GFLOPS | Progress: (16/20) | 11.58 s
+[Task 10/25] Current/Best: 18.99/ 19.47 GFLOPS | Progress: (20/20) | 13.72 s Done.
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 11/25] Current/Best: 8.27/ 23.46 GFLOPS | Progress: (4/20) | 4.44 s
-[Task 11/25] Current/Best: 9.91/ 23.46 GFLOPS | Progress: (8/20) | 7.16 s
-[Task 11/25] Current/Best: 9.17/ 23.46 GFLOPS | Progress: (12/20) | 9.43 s
-[Task 11/25] Current/Best: 12.04/ 23.46 GFLOPS | Progress: (16/20) | 12.31 s
-[Task 11/25] Current/Best: 8.71/ 23.46 GFLOPS | Progress: (20/20) | 16.46 s Done.
+[Task 11/25] Current/Best: 18.72/ 19.74 GFLOPS | Progress: (4/20) | 4.52 s
+[Task 11/25] Current/Best: 8.94/ 19.74 GFLOPS | Progress: (8/20) | 7.50 s
+[Task 11/25] Current/Best: 11.79/ 21.67 GFLOPS | Progress: (12/20) | 10.34 s
+[Task 11/25] Current/Best: 23.62/ 23.62 GFLOPS | Progress: (16/20) | 12.64 s
+[Task 11/25] Current/Best: 12.01/ 23.62 GFLOPS | Progress: (20/20) | 15.34 s Done.
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 12/25] Current/Best: 14.49/ 19.87 GFLOPS | Progress: (4/20) | 5.86 s
-[Task 12/25] Current/Best: 12.54/ 19.87 GFLOPS | Progress: (8/20) | 8.48 s
-[Task 12/25] Current/Best: 6.02/ 19.87 GFLOPS | Progress: (12/20) | 11.16 s
-[Task 12/25] Current/Best: 19.19/ 19.87 GFLOPS | Progress: (16/20) | 16.11 s
-[Task 12/25] Current/Best: 15.97/ 19.87 GFLOPS | Progress: (20/20) | 18.86 s Done.
+[Task 12/25] Current/Best: 17.23/ 17.23 GFLOPS | Progress: (4/20) | 6.35 s
+[Task 12/25] Current/Best: 14.50/ 17.23 GFLOPS | Progress: (8/20) | 8.52 s
+[Task 12/25] Current/Best: 13.65/ 17.23 GFLOPS | Progress: (12/20) | 12.10 s
+[Task 12/25] Current/Best: 5.25/ 17.23 GFLOPS | Progress: (16/20) | 18.38 s
+[Task 12/25] Current/Best: 10.11/ 17.39 GFLOPS | Progress: (20/20) | 21.77 s Done.
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 13/25] Current/Best: 12.15/ 12.23 GFLOPS | Progress: (4/20) | 5.51 s
-[Task 13/25] Current/Best: 9.22/ 16.95 GFLOPS | Progress: (8/20) | 8.11 s
-[Task 13/25] Current/Best: 12.26/ 17.65 GFLOPS | Progress: (12/20) | 11.88 s
-[Task 13/25] Current/Best: 12.40/ 18.60 GFLOPS | Progress: (16/20) | 15.14 s
-[Task 13/25] Current/Best: 12.32/ 18.60 GFLOPS | Progress: (20/20) | 17.86 s Done.
+[Task 13/25] Current/Best: 9.43/ 21.08 GFLOPS | Progress: (4/20) | 6.17 s
+[Task 13/25] Current/Best: 8.07/ 21.08 GFLOPS | Progress: (8/20) | 9.99 s
+[Task 13/25] Current/Best: 16.33/ 22.13 GFLOPS | Progress: (12/20) | 13.51 s
+[Task 13/25] Current/Best: 12.08/ 22.13 GFLOPS | Progress: (16/20) | 15.92 s
+[Task 13/25] Current/Best: 18.92/ 22.13 GFLOPS | Progress: (20/20) | 18.91 s Done.
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 14/25] Current/Best: 11.52/ 14.25 GFLOPS | Progress: (4/20) | 8.27 s
-[Task 14/25] Current/Best: 12.18/ 17.56 GFLOPS | Progress: (8/20) | 11.53 s
-[Task 14/25] Current/Best: 11.10/ 17.56 GFLOPS | Progress: (12/20) | 18.63 s
-[Task 14/25] Current/Best: 14.06/ 17.56 GFLOPS | Progress: (16/20) | 25.00 s
-[Task 14/25] Current/Best: 21.69/ 21.69 GFLOPS | Progress: (20/20) | 27.61 s Done.
-
+[Task 14/25] Current/Best: 8.11/ 12.81 GFLOPS | Progress: (4/20) | 12.80 s
+[Task 14/25] Current/Best: 13.07/ 15.15 GFLOPS | Progress: (8/20) | 24.24 s
+[Task 14/25] Current/Best: 18.49/ 18.49 GFLOPS | Progress: (12/20) | 31.30 s
+[Task 14/25] Current/Best: 4.74/ 18.49 GFLOPS | Progress: (16/20) | 37.78 s
+[Task 14/25] Current/Best: 15.56/ 18.49 GFLOPS | Progress: (20/20) | 40.19 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 15/25] Current/Best: 3.15/ 17.95 GFLOPS | Progress: (4/20) | 9.49 s
-[Task 15/25] Current/Best: 14.34/ 23.94 GFLOPS | Progress: (8/20) | 11.63 s
-[Task 15/25] Current/Best: 17.46/ 23.94 GFLOPS | Progress: (12/20) | 13.26 s
-[Task 15/25] Current/Best: 7.08/ 23.94 GFLOPS | Progress: (16/20) | 18.85 s
-[Task 15/25] Current/Best: 10.52/ 23.94 GFLOPS | Progress: (20/20) | 21.23 s Done.
-
+[Task 15/25] Current/Best: 21.38/ 21.38 GFLOPS | Progress: (4/20) | 5.36 s
+[Task 15/25] Current/Best: 8.68/ 21.38 GFLOPS | Progress: (8/20) | 13.83 s
+[Task 15/25] Current/Best: 6.94/ 21.38 GFLOPS | Progress: (12/20) | 17.07 s
+[Task 15/25] Current/Best: 9.29/ 21.38 GFLOPS | Progress: (16/20) | 23.80 s
+[Task 15/25] Current/Best: 3.14/ 21.38 GFLOPS | Progress: (20/20) | 35.17 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 16/25] Current/Best: 18.07/ 19.33 GFLOPS | Progress: (4/20) | 5.78 s
-[Task 16/25] Current/Best: 13.32/ 19.33 GFLOPS | Progress: (8/20) | 7.95 s
-[Task 16/25] Current/Best: 6.25/ 22.22 GFLOPS | Progress: (12/20) | 9.67 s
-[Task 16/25] Current/Best: 14.81/ 22.22 GFLOPS | Progress: (16/20) | 11.90 s
-[Task 16/25] Current/Best: 3.08/ 22.22 GFLOPS | Progress: (20/20) | 14.34 s Done.
+[Task 16/25] Current/Best: 18.54/ 18.54 GFLOPS | Progress: (4/20) | 5.45 s
+[Task 16/25] Current/Best: 14.60/ 18.54 GFLOPS | Progress: (8/20) | 8.70 s
+[Task 16/25] Current/Best: 6.69/ 18.54 GFLOPS | Progress: (12/20) | 10.47 s
+[Task 16/25] Current/Best: 17.77/ 18.68 GFLOPS | Progress: (16/20) | 12.19 s
+[Task 16/25] Current/Best: 5.41/ 18.68 GFLOPS | Progress: (20/20) | 14.50 s Done.
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 17/25] Current/Best: 9.74/ 23.04 GFLOPS | Progress: (4/20) | 5.23 s
-[Task 17/25] Current/Best: 21.72/ 23.04 GFLOPS | Progress: (8/20) | 7.12 s
-[Task 17/25] Current/Best: 19.59/ 23.04 GFLOPS | Progress: (12/20) | 9.63 s
-[Task 17/25] Current/Best: 1.56/ 23.04 GFLOPS | Progress: (16/20) | 14.19 s
-[Task 17/25] Current/Best: 9.11/ 23.04 GFLOPS | Progress: (20/20) | 18.24 s Done.
+[Task 17/25] Current/Best: 16.22/ 23.22 GFLOPS | Progress: (4/20) | 4.71 s
+[Task 17/25] Current/Best: 13.42/ 23.22 GFLOPS | Progress: (8/20) | 7.20 s
+[Task 17/25] Current/Best: 6.17/ 23.22 GFLOPS | Progress: (12/20) | 9.59 s
+[Task 17/25] Current/Best: 18.89/ 23.22 GFLOPS | Progress: (16/20) | 11.95 s
+[Task 17/25] Current/Best: 18.68/ 23.22 GFLOPS | Progress: (20/20) | 14.34 s Done.
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 18/25] Current/Best: 16.74/ 18.83 GFLOPS | Progress: (4/20) | 8.35 s
-[Task 18/25] Current/Best: 18.64/ 18.83 GFLOPS | Progress: (8/20) | 10.23 s
-[Task 18/25] Current/Best: 14.29/ 18.83 GFLOPS | Progress: (12/20) | 13.01 s
-[Task 18/25] Current/Best: 11.09/ 18.83 GFLOPS | Progress: (16/20) | 17.31 s
-[Task 18/25] Current/Best: 16.55/ 18.83 GFLOPS | Progress: (20/20) | 19.30 s Done.
+[Task 18/25] Current/Best: 7.31/ 18.80 GFLOPS | Progress: (4/20) | 5.07 s
+[Task 18/25] Current/Best: 12.60/ 21.66 GFLOPS | Progress: (8/20) | 7.63 s
+[Task 18/25] Current/Best: 13.49/ 21.66 GFLOPS | Progress: (12/20) | 9.82 s
+[Task 18/25] Current/Best: 20.89/ 21.66 GFLOPS | Progress: (16/20) | 11.88 s
+[Task 18/25] Current/Best: 8.61/ 21.66 GFLOPS | Progress: (20/20) | 17.88 s Done.
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 19/25] Current/Best: 20.61/ 20.61 GFLOPS | Progress: (4/20) | 5.43 s
-[Task 19/25] Current/Best: 17.77/ 20.61 GFLOPS | Progress: (8/20) | 8.76 s
-[Task 19/25] Current/Best: 7.27/ 21.53 GFLOPS | Progress: (12/20) | 12.45 s
-[Task 19/25] Current/Best: 6.92/ 21.53 GFLOPS | Progress: (16/20) | 18.68 s
-[Task 19/25] Current/Best: 8.66/ 21.53 GFLOPS | Progress: (20/20) | 21.73 s Done.
+[Task 19/25] Current/Best: 9.58/ 13.84 GFLOPS | Progress: (4/20) | 6.59 s
+[Task 19/25] Current/Best: 20.24/ 20.24 GFLOPS | Progress: (8/20) | 11.18 s
+[Task 19/25] Current/Best: 8.72/ 20.24 GFLOPS | Progress: (12/20) | 14.66 s Done.
+ Done.
+
+[Task 19/25] Current/Best: 18.13/ 20.24 GFLOPS | Progress: (16/20) | 17.19 s
+[Task 19/25] Current/Best: 8.77/ 20.24 GFLOPS | Progress: (20/20) | 20.40 s Done.
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 20/25] Current/Best: 11.06/ 11.43 GFLOPS | Progress: (4/20) | 6.55 s
-[Task 20/25] Current/Best: 5.62/ 20.17 GFLOPS | Progress: (8/20) | 13.12 s
-[Task 20/25] Current/Best: 11.98/ 20.17 GFLOPS | Progress: (12/20) | 16.42 s
-[Task 20/25] Current/Best: 9.60/ 20.17 GFLOPS | Progress: (16/20) | 27.98 s
-[Task 20/25] Current/Best: 2.69/ 20.17 GFLOPS | Progress: (20/20) | 41.05 s
-[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 21/25] Current/Best: 8.11/ 14.25 GFLOPS | Progress: (4/20) | 6.04 s
-[Task 21/25] Current/Best: 6.37/ 18.58 GFLOPS | Progress: (8/20) | 7.72 s
-[Task 21/25] Current/Best: 14.74/ 18.78 GFLOPS | Progress: (12/20) | 9.51 s
-[Task 21/25] Current/Best: 9.43/ 18.78 GFLOPS | Progress: (16/20) | 20.59 s
-[Task 21/25] Current/Best: 7.35/ 19.45 GFLOPS | Progress: (20/20) | 31.41 s Done.
+[Task 20/25] Current/Best: 16.72/ 16.72 GFLOPS | Progress: (4/20) | 5.14 s
+[Task 20/25] Current/Best: 9.79/ 17.19 GFLOPS | Progress: (8/20) | 15.70 s
+[Task 20/25] Current/Best: 4.70/ 18.16 GFLOPS | Progress: (12/20) | 22.93 s
+[Task 20/25] Current/Best: 18.22/ 18.90 GFLOPS | Progress: (16/20) | 30.24 s
+[Task 20/25] Current/Best: 10.43/ 18.90 GFLOPS | Progress: (20/20) | 33.51 s Done.
+[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
+[Task 21/25] Current/Best: 6.21/ 14.54 GFLOPS | Progress: (4/20) | 13.88 s
+[Task 21/25] Current/Best: 7.40/ 14.54 GFLOPS | Progress: (8/20) | 19.36 s
+[Task 21/25] Current/Best: 14.98/ 14.98 GFLOPS | Progress: (12/20) | 30.57 s
+[Task 21/25] Current/Best: 17.90/ 21.28 GFLOPS | Progress: (16/20) | 33.41 s
+[Task 21/25] Current/Best: 8.54/ 21.28 GFLOPS | Progress: (20/20) | 37.03 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 22/25] Current/Best: 20.56/ 20.56 GFLOPS | Progress: (4/20) | 4.62 s
-[Task 22/25] Current/Best: 12.99/ 20.56 GFLOPS | Progress: (8/20) | 6.56 s
-[Task 22/25] Current/Best: 18.53/ 20.56 GFLOPS | Progress: (12/20) | 8.61 s
-[Task 22/25] Current/Best: 9.09/ 20.56 GFLOPS | Progress: (16/20) | 14.15 s
-[Task 22/25] Current/Best: 2.68/ 20.56 GFLOPS | Progress: (20/20) | 16.65 s Done.
+[Task 22/25] Current/Best: 8.33/ 18.02 GFLOPS | Progress: (4/20) | 5.41 s
+[Task 22/25] Current/Best: 17.74/ 18.02 GFLOPS | Progress: (8/20) | 8.07 s
+[Task 22/25] Current/Best: 19.94/ 19.94 GFLOPS | Progress: (12/20) | 9.74 s
+[Task 22/25] Current/Best: 18.86/ 19.94 GFLOPS | Progress: (16/20) | 12.04 s
+[Task 22/25] Current/Best: 14.96/ 19.94 GFLOPS | Progress: (20/20) | 15.65 s Done.
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 23/25] Current/Best: 10.61/ 18.41 GFLOPS | Progress: (4/20) | 6.30 s
-[Task 23/25] Current/Best: 21.60/ 21.95 GFLOPS | Progress: (8/20) | 8.53 s
-[Task 23/25] Current/Best: 9.70/ 21.95 GFLOPS | Progress: (12/20) | 14.51 s
-[Task 23/25] Current/Best: 9.44/ 23.52 GFLOPS | Progress: (16/20) | 17.09 s
-[Task 23/25] Current/Best: 18.54/ 23.52 GFLOPS | Progress: (20/20) | 20.27 s Done.
+[Task 23/25] Current/Best: 14.56/ 22.04 GFLOPS | Progress: (4/20) | 7.08 s
+[Task 23/25] Current/Best: 7.99/ 22.04 GFLOPS | Progress: (8/20) | 13.05 s
+[Task 23/25] Current/Best: 10.40/ 22.04 GFLOPS | Progress: (12/20) | 15.65 s
+[Task 23/25] Current/Best: 12.70/ 22.04 GFLOPS | Progress: (16/20) | 19.00 s
+[Task 23/25] Current/Best: 10.45/ 22.04 GFLOPS | Progress: (20/20) | 22.47 s Done.
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 24/25] Current/Best: 2.97/ 9.71 GFLOPS | Progress: (4/20) | 8.85 s
-[Task 24/25] Current/Best: 2.41/ 9.71 GFLOPS | Progress: (8/20) | 15.14 s
-[Task 24/25] Current/Best: 1.89/ 9.71 GFLOPS | Progress: (12/20) | 21.21 s
-[Task 24/25] Current/Best: 4.71/ 9.71 GFLOPS | Progress: (16/20) | 26.66 s Done.
+[Task 24/25] Current/Best: 2.83/ 2.83 GFLOPS | Progress: (4/20) | 13.33 s
+[Task 24/25] Current/Best: 7.73/ 8.96 GFLOPS | Progress: (8/20) | 25.54 s
+[Task 24/25] Current/Best: 2.80/ 8.96 GFLOPS | Progress: (12/20) | 37.74 s Done.
-[Task 24/25] Current/Best: 1.25/ 9.71 GFLOPS | Progress: (20/20) | 37.67 s
+[Task 24/25] Current/Best: 6.84/ 8.96 GFLOPS | Progress: (16/20) | 48.76 s
+[Task 24/25] Current/Best: 1.66/ 9.31 GFLOPS | Progress: (20/20) | 60.66 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 25/25] Current/Best: 9.04/ 9.04 GFLOPS | Progress: (4/20) | 5.03 s
-[Task 25/25] Current/Best: 2.81/ 9.04 GFLOPS | Progress: (8/20) | 7.90 s
-[Task 25/25] Current/Best: 4.07/ 9.04 GFLOPS | Progress: (12/20) | 11.28 s
-[Task 25/25] Current/Best: 5.69/ 9.04 GFLOPS | Progress: (16/20) | 22.24 s
-[Task 25/25] Current/Best: 1.55/ 9.04 GFLOPS | Progress: (20/20) | 24.76 s
+[Task 25/25] Current/Best: 4.81/ 4.81 GFLOPS | Progress: (4/20) | 5.61 s
+[Task 25/25] Current/Best: 2.91/ 8.63 GFLOPS | Progress: (8/20) | 8.16 s
+[Task 25/25] Current/Best: 8.35/ 9.12 GFLOPS | Progress: (12/20) | 11.89 s
+[Task 25/25] Current/Best: 2.83/ 9.12 GFLOPS | Progress: (16/20) | 17.74 s
+[Task 25/25] Current/Best: 6.60/ 9.12 GFLOPS | Progress: (20/20) | 19.30 s Done.
</pre></div>
</div>
<p>The output from this tuning process will look something like this:</p>
@@ -1002,8 +1002,8 @@ model using optimized operators to speed up our computations.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"class='</span><span class="si">%s</span><span class="s2">' with probability=</span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>class='n02123045 tabby, tabby cat' with probability=0.621104
-class='n02123159 tiger cat' with probability=0.356378
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>class='n02123045 tabby, tabby cat' with probability=0.621105
+class='n02123159 tiger cat' with probability=0.356377
class='n02124075 Egyptian cat' with probability=0.019712
class='n02129604 tiger, Panthera tigris' with probability=0.001215
class='n04040759 radiator' with probability=0.000262
@@ -1040,8 +1040,8 @@ 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': 376.55249478004407, 'median': 374.42979039997226, 'std': 3.3020468792685795}
-unoptimized: {'mean': 494.9741758199889, 'median': 495.114422450024, 'std': 1.1117048733914823}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {'mean': 422.7526840199971, 'median': 422.83610059994317, 'std': 3.5374807866565536}
+unoptimized: {'mean': 500.58081771001525, 'median': 500.23290955004995, 'std': 1.5838218019673596}
</pre></div>
</div>
</div>
@@ -1055,7 +1055,7 @@ 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> ( 12 minutes 48.324 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 13 minutes 50.568 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 d2a38de7d8..16c4e719d8 100644
--- a/docs/tutorial/cross_compilation_and_rpc.html
+++ b/docs/tutorial/cross_compilation_and_rpc.html
@@ -558,7 +558,7 @@ 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>1.209e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.274e-07 secs/op
</pre></div>
</div>
</div>
diff --git a/docs/tutorial/intro_topi.html b/docs/tutorial/intro_topi.html
index 9c697271bc..18d7675966 100644
--- a/docs/tutorial/intro_topi.html
+++ b/docs/tutorial/intro_topi.html
@@ -528,7 +528,7 @@ class Module:
<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, 0x163f7e60)), stage(b, placeholder(b, 0x1aa51240)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T.Range(0, 10), "DataPar", ""), T.iter_var(ax2, T.Range(0, 10), "DataPar", "")], reduce_axis=[], tag=broadcast, attr [...]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[stage(a, placeholder(a, 0x286982a0)), stage(b, placeholder(b, 0x114e1150)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), "DataPar", ""), T.iter_var(ax1, T.Range(0, 10), "DataPar", ""), T.iter_var(ax2, T.Range(0, 10), "DataPar", "")], reduce_axis=[], tag=broadcast, attr [...]
</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/sg_execution_times.html b/docs/tutorial/sg_execution_times.html
index 4cc99597a9..c1152bac8c 100644
--- a/docs/tutorial/sg_execution_times.html
+++ b/docs/tutorial/sg_execution_times.html
@@ -360,44 +360,44 @@
<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>16:34.857</strong> total execution time for <strong>tutorial</strong> files:</p>
+<p><strong>17:38.604</strong> total execution time for <strong>tutorial</strong> files:</p>
<table class="docutils align-default">
<colgroup>
-<col style="width: 83%" />
-<col style="width: 10%" />
+<col style="width: 82%" />
+<col style="width: 11%" />
<col style="width: 7%" />
</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>12:48.324</p></td>
+<td><p>13:50.568</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>01:34.065</p></td>
+<td><p>01:34.526</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:57.157</p></td>
+<td><p>01:04.758</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>00:42.811</p></td>
+<td><p>00:44.267</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>00:30.442</p></td>
+<td><p>00:22.389</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>00:00.963</p></td>
+<td><p>00:00.1000</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>00:00.857</p></td>
+<td><p>00:00.877</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>00:00.239</p></td>
+<td><p>00:00.220</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="uma.html#sphx-glr-tutorial-uma-py"><span class="std std-ref">Making your Hardware Accelerator TVM-ready with UMA</span></a> (<code class="docutils literal notranslate"><span class="pre">uma.py</span></code>)</p></td>
diff --git a/docs/tutorial/tensor_expr_get_started.html b/docs/tutorial/tensor_expr_get_started.html
index 0e976e7a71..3ef94ee8f0 100644
--- a/docs/tutorial/tensor_expr_get_started.html
+++ b/docs/tutorial/tensor_expr_get_started.html
@@ -569,8 +569,8 @@ helper function to run a profile of the TVM generated code.</p>
<span class="n">evaluate_addition</span><span class="p">(</span><span class="n">fadd</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">"naive"</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#list" ti [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000006
-naive: 0.000007
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000007
+naive: 0.000006
</pre></div>
</div>
</div>
@@ -625,7 +625,7 @@ 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>parallel: 0.000006
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallel: 0.000009
</pre></div>
</div>
</div>
@@ -664,7 +664,7 @@ 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>vector: 0.000040
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector: 0.000039
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -701,10 +701,10 @@ class Module:
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Operator Timing Performance
- numpy 5.981479989713989e-06 1.0
- naive 6.9411e-06 1.1604318683563626
-parallel 6.0809e-06 1.016621306174555
- vector 3.99417e-05 6.677561417690182
+ numpy 6.9311000152083576e-06 1.0
+ naive 5.8438e-06 0.8431273516725221
+parallel 9.299e-06 1.3416340811120817
+ vector 3.9168900000000004e-05 5.651180896835253
</pre></div>
</div>
<div class="admonition-code-specialization admonition">
@@ -1020,7 +1020,7 @@ 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: 0.016288
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.019049
</pre></div>
</div>
<p>Now we write a basic matrix multiplication using TVM TE and verify that it
@@ -1061,7 +1061,7 @@ 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>none: 3.231282
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>none: 3.656533
</pre></div>
</div>
<p>Let’s take a look at the intermediate representation of the operator and
@@ -1125,7 +1125,7 @@ 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>blocking: 0.281630
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>blocking: 0.323000
</pre></div>
</div>
<p>By reordering the computation to take advantage of caching, you should see a
@@ -1174,7 +1174,7 @@ 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>vectorization: 0.259879
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vectorization: 0.326812
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1223,7 +1223,7 @@ 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>loop permutation: 0.112433
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>loop permutation: 0.137138
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1293,7 +1293,7 @@ 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>array packing: 0.103895
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array packing: 0.107841
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1359,7 +1359,7 @@ 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>block caching: 0.097481
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>block caching: 0.113076
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1416,7 +1416,7 @@ 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>parallelization: 0.115672
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallelization: 0.133928
# from tvm.script import ir as I
# from tvm.script import tir as T
@@ -1469,13 +1469,13 @@ 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 3.2312820005 1.0
- blocking 0.28162983869999997 0.08715730742671836
- vectorization 0.2598786084 0.08042585214159181
-loop permutation 0.1124331706 0.03479522077695552
- array packing 0.10389522139999999 0.032152941582914624
- block caching 0.09748085710000001 0.030167858170508204
- parallelization 0.1156715905 0.035797429776200686
+ none 3.6565331299 1.0
+ blocking 0.32300033079999996 0.08833513038861307
+ vectorization 0.3268121641 0.08937760235989925
+loop permutation 0.1371382546 0.03750499441085346
+ array packing 0.10784103330000001 0.029492699633477486
+ block caching 0.1130755551 0.030924252860001413
+ parallelization 0.1339278657 0.03662700731598806
</pre></div>
</div>
<p>Note that the outputs on the web page reflect the running times on a
@@ -1507,6 +1507,7 @@ 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 4.758 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>