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Posted to commits@tvm.apache.org by tq...@apache.org on 2024/01/30 03:44:19 UTC

(tvm-site) branch asf-site updated: deploying docs (apache/tvm@ff9ebadf6ae6bdf2fbfe5eb220d770b0ed9550cd)

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 b0694a59e3 deploying docs (apache/tvm@ff9ebadf6ae6bdf2fbfe5eb220d770b0ed9550cd)
b0694a59e3 is described below

commit b0694a59e3104d602e2d2959538a9451948f0ab5
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Tue Jan 30 03:44:13 2024 +0000

    deploying docs (apache/tvm@ff9ebadf6ae6bdf2fbfe5eb220d770b0ed9550cd)
---
 .../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   |  10 +-
 .../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   |  10 +-
 .../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     |   8 +-
 .../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   |   6 +-
 .../frontend/deploy_classification.rst.txt         |   2 +-
 .../tutorials/frontend/deploy_detection.rst.txt    |   2 +-
 .../tutorials/frontend/sg_execution_times.rst.txt  |   6 +-
 .../tutorials/optimize/sg_execution_times.rst.txt  |   6 +-
 .../topic/vta/tutorials/sg_execution_times.rst.txt |   4 +-
 .../tutorial/auto_scheduler_matmul_x86.rst.txt     |  13 +-
 docs/_sources/tutorial/autotvm_matmul_x86.rst.txt  |  20 +-
 docs/_sources/tutorial/autotvm_relay_x86.rst.txt   |  60 ++---
 .../tutorial/cross_compilation_and_rpc.rst.txt     |   2 +-
 docs/_sources/tutorial/intro_topi.rst.txt          |   2 +-
 docs/_sources/tutorial/sg_execution_times.rst.txt  |  22 +-
 .../tutorial/tensor_expr_get_started.rst.txt       |  42 ++--
 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       |  15 +-
 docs/how_to/compile_models/from_paddle.html        |   2 +-
 docs/how_to/compile_models/from_pytorch.html       |  18 +-
 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 |  21 +-
 .../deploy_models/deploy_model_on_android.html     |   2 +-
 .../deploy_object_detection_pytorch.html           |  59 ++---
 docs/how_to/deploy_models/deploy_prequantized.html |   8 +-
 .../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  |  24 +-
 .../extend_tvm/bring_your_own_datatypes.html       |   2 +-
 docs/how_to/extend_tvm/sg_execution_times.html     |  10 +-
 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                        |  18 +-
 .../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      |  10 +-
 .../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 |   8 +-
 docs/how_to/work_with_schedules/intrin_math.html   |   2 +-
 .../work_with_schedules/sg_execution_times.html    |  18 +-
 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  |   6 +-
 .../tutorials/frontend/deploy_classification.html  |   2 +-
 .../vta/tutorials/frontend/deploy_detection.html   |   2 +-
 .../vta/tutorials/frontend/sg_execution_times.html |   6 +-
 .../vta/tutorials/optimize/sg_execution_times.html |   6 +-
 docs/topic/vta/tutorials/sg_execution_times.html   |   4 +-
 docs/tutorial/auto_scheduler_matmul_x86.html       |   8 +-
 docs/tutorial/autotvm_matmul_x86.html              |  20 +-
 docs/tutorial/autotvm_relay_x86.html               | 263 +++++++++++----------
 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         |  42 ++--
 141 files changed, 878 insertions(+), 875 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 68b07fcac4..9f47addf9b 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  32.012 seconds)
+   **Total running time of the script:** ( 1 minutes  36.143 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 3b23aae1ab..8266429acc 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.zipa2143c9c-cc05-4502-adb3-3915fc411fe6 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+    Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip81703467-a908-4e79-bdf5-9b978b7dec49 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 e3d03b6dd4..73bc6b5c02 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, 55.6MB/s]
     28%|##8       | 11.6M/41.5M [00:00<00:00, 43.6MB/s]
     38%|###8      | 15.9M/41.5M [00:00<00:00, 40.1MB/s]
     54%|#####3    | 22.3M/41.5M [00:00<00:00, 35.1MB/s]
     62%|######2   | 25.8M/41.5M [00:00<00:00, 31.6MB/s]
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     92%|#########2| 38.3M/41.5M [00:01<00:00, 35.3MB/s]
    100%|##########| 41.5M/41.5M [00:01<00:00, 35.6MB/s]
+
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     77%|#######7  | 32.0M/41.5M [00:00<00:00, 45.3MB/s]
     96%|#########6| 40.0M/41.5M [00:00<00:00, 52.1MB/s]
    100%|##########| 41.5M/41.5M [00:00<00:00, 50.3MB/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 8ebd162eb2..b5a847cfb7 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  1.305 seconds)
+   **Total running time of the script:** ( 1 minutes  2.038 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 c7ae7126e8..a9e3975291 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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     54%|#####3    | 24.0M/44.7M [00:00<00:00, 47.9MB/s]
     69%|######9   | 31.0M/44.7M [00:00<00:00, 56.2MB/s]
     82%|########1 | 36.5M/44.7M [00:00<00:00, 52.0MB/s]
     93%|#########2| 41.5M/44.7M [00:00<00:00, 43.4MB/s]
    100%|##########| 44.7M/44.7M [00:00<00:00, 50.9MB/s]
+
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    100%|##########| 44.7M/44.7M [00:01<00:00, 39.3MB/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 3f2e3d8c9c..23c68b9140 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  30.490 seconds)
+   **Total running time of the script:** ( 1 minutes  32.488 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 dd8800dc25..9bdb339b37 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
 =================
-**07:07.307** total execution time for **how_to_compile_models** files:
+**07:18.067** total execution time for **how_to_compile_models** files:
 
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:32.012 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:36.143 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:30.490 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:32.488 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 01:01.305 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 01:02.038 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:41.990 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:42.880 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:37.824 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:39.513 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)           | 00:33.929 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)           | 00:34.130 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:28.689 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:29.481 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:26.587 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:26.645 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:11.674 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:11.905 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.807 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.844 | 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 534a72f659..dfbead7d7d 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)  
-     3994.9549    3993.3806    4005.8477    3991.9933      3.9112                  
+     4060.6587    4060.0478    4068.1229    4057.3194      3.0713                  
 
 
 
@@ -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  17.463 seconds)
+   **Total running time of the script:** ( 1 minutes  19.156 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 df2394839a..6edae91d79 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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    102967424/102967424 [==============================] - 2s 0us/step
+
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    100646912/102967424 [============================>.] - ETA: 0s
    102967424/102967424 [==============================] - 2s 0us/step
 
 
 
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 21384c13be..54ffd809fd 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)  
-      14.8813      14.7918      15.7025      14.4293       0.3654                  
+      15.3189      15.0604      16.8794      14.7576       0.6523                  
 
 
 
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 7b7805d832..616c79c49d 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  34.732 seconds)
+   **Total running time of the script:** ( 3 minutes  35.111 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 bbfc2d9cec..9db5ec9c34 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]
     53%|#####2    | 7.12M/13.6M [00:00<00:00, 74.7MB/s]
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+
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    100%|##########| 13.6M/13.6M [00:00<00:00, 52.3MB/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)  
-      86.3076      86.2584      88.7853      85.8978       0.3716                  
+      87.6607      87.5686      91.7020      87.3378       0.4483                  
 
 
 
@@ -457,7 +457,7 @@ TODO
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  28.708 seconds)
+   **Total running time of the script:** ( 1 minutes  29.509 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 47a8e55100..7ee63f80ea 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)  
-      108.0301     107.8679     118.8993     107.4367      1.1204                  
+      111.0633     110.9595     114.5839     110.2779      0.5693                  
 
 
 
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 0872aa785c..891dbe0bb9 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  52.534 seconds)
+   **Total running time of the script:** ( 1 minutes  56.862 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 d0b9d313f6..8b59b41915 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
 =================
-**11:44.222** total execution time for **how_to_deploy_models** files:
+**11:49.775** 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``) | 03:34.732 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:35.111 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)                               | 01:52.534 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)                               | 01:56.862 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:28.708 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:29.509 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:17.463 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:19.156 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:51.622 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:52.505 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:51.102 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:50.434 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:47.474 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:45.887 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:30.598 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:30.343 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:29.983 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:29.963 | 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 7c5f7cb3d3..fbe2472ecc 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.zipae9fb4fd-6ff9-4157-98f3-3ee21179283e from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+    Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip93db1147-ecd7-4326-8589-9950387d19e7 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 143f4da20d..7e1323e685 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
 =================
-**00:57.757** total execution time for **how_to_extend_tvm** files:
+**00:59.467** 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``) | 00:53.794 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:55.257 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)           | 00:02.790 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)           | 00:02.962 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)                     | 00:01.166 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)                     | 00:01.241 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``)       | 00:00.007 | 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 768b637283..b3429d4b75 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: 24980us [24980us] (48.76%; 48.76%)
-    FoldScaleAxis: 26248us [8us] (51.24%; 51.24%)
-            FoldConstant: 26240us [1832us] (51.22%; 99.97%)
-                    InferType: 24408us [24408us] (47.65%; 93.02%)
+    InferType: 25338us [25338us] (48.29%; 48.29%)
+    FoldScaleAxis: 27130us [9us] (51.71%; 51.71%)
+            FoldConstant: 27121us [1908us] (51.69%; 99.97%)
+                    InferType: 25213us [25213us] (48.05%; 92.96%)
 
 
 
@@ -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: 24398us [24398us] (48.23%; 48.23%)
-    FoldScaleAxis: 26190us [8us] (51.77%; 51.77%)
-            FoldConstant: 26183us [1887us] (51.76%; 99.97%)
-                    InferType: 24295us [24295us] (48.03%; 92.79%)
+    InferType: 25309us [25309us] (48.30%; 48.30%)
+    FoldScaleAxis: 27094us [10us] (51.70%; 51.70%)
+            FoldConstant: 27084us [1933us] (51.68%; 99.96%)
+                    InferType: 25151us [25151us] (48.00%; 92.86%)
 
 
 
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 33ac2bc5b0..b5c137f457 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: 40.226814 ms
+    Convolution: 41.797313 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 90d1297c59..7fe78d6f64 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: 12.267565 ms
+    conv2d with tensor core: 12.267660 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 f37c0f883a..fe5d4e39f9 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: 0.017383
-    Baseline: 3.271250
+    Numpy running time: 0.018671
+    Baseline: 3.308058
 
 
 
@@ -227,7 +227,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
 
  .. code-block:: none
 
-    Opt1: 0.310946
+    Opt1: 0.304783
 
 
 
@@ -318,7 +318,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
 
  .. code-block:: none
 
-    Opt2: 0.313008
+    Opt2: 0.295418
 
 
 
@@ -406,7 +406,7 @@ the access pattern for A matrix is more cache friendly.
 
  .. code-block:: none
 
-    Opt3: 0.114952
+    Opt3: 0.116884
 
 
 
@@ -523,7 +523,7 @@ flattening.
 
  .. code-block:: none
 
-    Opt4: 0.102377
+    Opt4: 0.105651
 
 
 
@@ -635,7 +635,7 @@ write to C when all the block results are ready.
 
  .. code-block:: none
 
-    Opt5: 0.100968
+    Opt5: 0.110050
 
 
 
@@ -748,7 +748,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
 
  .. code-block:: none
 
-    Opt6: 0.120452
+    Opt6: 0.131391
 
 
 
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 ff2c854b64..a7caded1e6 100644
--- a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**00:33.080** total execution time for **how_to_optimize_operators** files:
+**00:33.787** total execution time for **how_to_optimize_operators** files:
 
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:30.081 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:30.766 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.857 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.869 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.141 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.152 | 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 a721d57712..f2c62b36cc 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
 =================
-**03:34.687** total execution time for **how_to_tune_with_autoscheduler** files:
+**03:38.586** 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``)             | 01:33.518 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)             | 01:34.005 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:12.030 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:13.720 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:17.513 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:18.380 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:15.981 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:16.362 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:15.544 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:16.017 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)               | 00:00.101 | 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 |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
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 fa768c2b6a..d2fc954f9f 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: 0.354 ms
+    Execution time of this operator: 0.353 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 452f7d1351..90cd44d2fa 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)  
-       3.3096       3.3085       3.3152       3.3050       0.0043                  
+       3.2771       3.2685       3.2947       3.2682       0.0124                  
 
 
 
@@ -674,7 +674,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  12.030 seconds)
+   **Total running time of the script:** ( 1 minutes  13.720 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 96fe4c26e1..f29b505716 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)  
-      725.6079     726.1941     726.2311     724.3986      0.8553                  
+      744.6371     744.5805     748.4943     740.8363      3.1266                  
 
 
 
@@ -693,7 +693,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  33.518 seconds)
+   **Total running time of the script:** ( 1 minutes  34.005 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 6613364355..ab062fd345 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
 =================
-**00:22.896** total execution time for **how_to_tune_with_autotvm** files:
+**00:24.111** 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``)           | 00:22.859 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)           | 00:24.073 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)               | 00:00.020 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)               | 00:00.022 | 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_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 |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.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 090d8ad1de..e59a2a3afc 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: 0.037264
+    Time cost of this operator: 0.037217
 
 
 
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 cc919d9976..c5ccc6121d 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  298.5     98.745   (1, 2, 10, 10, 3)  2       1        [298.5]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.869     0.949    (1, 6, 10, 10)     1       1        [2.869]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.925     0.306    (1, 1, 10, 10, 3)  1       1        [0.925]           
-    Total_time                                    -                                             302.294   -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  296.1     98.692   (1, 2, 10, 10, 3)  2       1        [296.1]           
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.959     0.986    (1, 6, 10, 10)     1       1        [2.959]           
+    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.966     0.322    (1, 1, 10, 10, 3)  1       1        [0.966]           
+    Total_time                                    -                                             300.025   -        -                  -       -        -                 
 
 
 
@@ -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  133.4     98.128   (1, 6, 10, 10, 1)  2       1        [133.4]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.699     1.25     (1, 6, 10, 10)     1       1        [1.699]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.846     0.622    (1, 3, 10, 10, 1)  1       1        [0.846]           
-    Total_time                                    -                                             135.945   -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  102.6     97.442   (1, 6, 10, 10, 1)  2       1        [102.6]           
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.753     1.665    (1, 6, 10, 10)     1       1        [1.753]           
+    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.94      0.892    (1, 1, 10, 10, 3)  1       1        [0.94]            
+    Total_time                                    -                                             105.293   -        -                  -       -        -                 
 
 
 
@@ -439,7 +439,7 @@ Timing the tuned program
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  22.819 seconds)
+   **Total running time of the script:** ( 1 minutes  25.415 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 48c8c6b735..094896572b 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, 13.4MB/s]
    100%|##########| 3.42M/3.42M [00:00<00:00, 20.7MB/s]
+
      0%|          | 0.00/3.42M [00:00<?, ?B/s]
     61%|######    | 2.09M/3.42M [00:00<00:00, 13.0MB/s]
    100%|##########| 3.42M/3.42M [00:00<00:00, 20.5MB/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  27.017 seconds)
+   **Total running time of the script:** ( 1 minutes  29.429 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 72a1dc48db..4d0b6d9873 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/tmp9467wad2/images/random'
+    '/tmp/tmp2h5t1rho/images/random'
 
 
 
@@ -317,8 +317,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
 
  .. code-block:: none
 
-    /tmp/tmp9467wad2/images/target contains 8144 images
-    /tmp/tmp9467wad2/images/random contains 5000 images
+    /tmp/tmp2h5t1rho/images/target contains 8144 images
+    /tmp/tmp2h5t1rho/images/random contains 5000 images
 
 
 
@@ -493,13 +493,13 @@ the time on our validation set).
  .. code-block:: none
 
     Epoch 1/3
-    328/328 - 39s - loss: 0.2166 - accuracy: 0.9227 - val_loss: 0.1187 - val_accuracy: 0.9543 - 39s/epoch - 118ms/step
+    328/328 - 39s - loss: 0.2284 - accuracy: 0.9224 - val_loss: 0.1106 - val_accuracy: 0.9603 - 39s/epoch - 119ms/step
     Epoch 2/3
-    328/328 - 35s - loss: 0.0960 - accuracy: 0.9653 - val_loss: 0.1039 - val_accuracy: 0.9619 - 35s/epoch - 105ms/step
+    328/328 - 35s - loss: 0.1001 - accuracy: 0.9630 - val_loss: 0.1408 - val_accuracy: 0.9498 - 35s/epoch - 108ms/step
     Epoch 3/3
-    328/328 - 34s - loss: 0.0628 - accuracy: 0.9763 - val_loss: 0.0959 - val_accuracy: 0.9698 - 34s/epoch - 105ms/step
+    328/328 - 35s - loss: 0.0670 - accuracy: 0.9752 - val_loss: 0.1027 - val_accuracy: 0.9690 - 35s/epoch - 107ms/step
 
-    <keras.callbacks.History object at 0x7f43a51dbfa0>
+    <keras.callbacks.History object at 0x7f537816a220>
 
 
 
@@ -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  38.351 seconds)
+   **Total running time of the script:** ( 4 minutes  30.070 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 36e1e34166..8ef846cccc 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
 =================
-**07:57.019** total execution time for **how_to_work_with_microtvm** files:
+**07:54.061** total execution time for **how_to_work_with_microtvm** files:
 
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:38.351 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:30.070 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:27.017 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:29.429 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:22.819 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:25.415 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:11.778 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:11.802 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:08.885 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:09.183 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:08.169 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:08.162 | 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 7678435e97..897250b860 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
 =================
-**00:38.516** total execution time for **how_to_work_with_relay** files:
+**00:39.428** 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``) | 00:33.572 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:34.234 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.119 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.154 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:01.819 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:02.033 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)                 | 00:00.006 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
index 87b97bdac8..b20784b327 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 0x7f458a08eee0>
+    <function my_cuda_math_rule at 0x7f537953d280>
 
 
 
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 a2cacfd3d2..df81c8f694 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
 =================
-**00:05.573** total execution time for **how_to_work_with_schedules** files:
+**00:05.710** total execution time for **how_to_work_with_schedules** files:
 
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.525 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.577 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:01.346 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:01.395 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.717 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.728 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.704 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.718 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.115 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.120 | 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``) | 00:00.073 | 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``)                               | 00:00.067 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)               | 00:00.031 | 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 eabfa2b06e..63c6e99d0b 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
 =================
-**00:35.290** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:35.440** total execution time for **topic_vta_tutorials_autotvm** files:
 
 +---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:35.282 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:35.432 | 0.0 MB |
 +---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``)     | 00:00.007 | 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 bc89ef48b0..5da9a770d3 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 37.56s!
+    resnet18_v1 inference graph built in 39.01s!
 
 
 
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 bc04d41e75..8e194d3b4b 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 25.39s!
+    yolov3-tiny inference graph built in 26.65s!
 
 
 
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 055df73d45..91c0677384 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
 =================
-**01:56.070** total execution time for **topic_vta_tutorials_frontend** files:
+**01:59.329** total execution time for **topic_vta_tutorials_frontend** files:
 
 +------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)           | 00:58.202 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)           | 00:59.700 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:57.868 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:59.630 | 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 bbe2474f78..8912506946 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
 =================
-**00:03.238** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.301** total execution time for **topic_vta_tutorials_optimize** files:
 
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.745 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.812 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.493 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.488 | 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 fcf2d5d8e0..1d54aa423e 100644
--- a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
@@ -8,7 +8,7 @@ Computation times
 **00:00.806** total execution time for **topic_vta_tutorials** files:
 
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.416 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.414 | 0.0 MB |
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.391 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.392 | 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 61ff3d72d1..9dcfb8aa5d 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -207,13 +207,6 @@ trials, we can load the best schedule from the log file and apply it.
 
 
 
-.. rst-class:: sphx-glr-script-out
-
- .. code-block:: none
-
-    *E
-
-
 
 
 
@@ -325,7 +318,7 @@ We build the binary and check its correctness and performance.
 
  .. code-block:: none
 
-    Execution time of this operator: 94.321 ms
+    Execution time of this operator: 92.121 ms
 
 
 
@@ -423,7 +416,7 @@ resume the status and do more 5 trials.
  .. code-block:: none
 
     Resume search:
-
+    .T
 
 
 
@@ -441,7 +434,7 @@ operations.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  33.025 seconds)
+   **Total running time of the script:** ( 1 minutes  29.500 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 bb6d46a422..fe81e789e7 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: 2.17/2.17       result: MeasureResult(costs=(0.1238816818,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.230107069015503, timestamp=1706571339.625364) [('tile_y', [-1, 4]), ('tile_x', [-1, 1])],None,2
-    No: 2   GFLOPS: 7.92/7.92       result: MeasureResult(costs=(0.0339051936,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8027594089508057, timestamp=1706571340.4259365)       [('tile_y', [-1, 512]), ('tile_x', [-1, 16])],None,49
-    No: 3   GFLOPS: 2.17/7.92       result: MeasureResult(costs=(0.1236930316,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.2226710319519043, timestamp=1706571342.6601648)       [('tile_y', [-1, 32]), ('tile_x', [-1, 4])],None,25
-    No: 4   GFLOPS: 11.61/11.61     result: MeasureResult(costs=(0.0231276226,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6599793434143066, timestamp=1706571343.29226) [('tile_y', [-1, 128]), ('tile_x', [-1, 256])],None,87
-    No: 5   GFLOPS: 2.09/11.61      result: MeasureResult(costs=(0.1287003534,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3154706954956055, timestamp=1706571345.760802)        [('tile_y', [-1, 64]), ('tile_x', [-1, 4])],None,26
-    No: 6   GFLOPS: 13.35/13.35     result: MeasureResult(costs=(0.020101387,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6268157958984375, timestamp=1706571346.3466408)        [('tile_y', [-1, 128]), ('tile_x', [-1, 128])],None,77
-    No: 7   GFLOPS: 3.00/13.35      result: MeasureResult(costs=(0.0896176782,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6861565113067627, timestamp=1706571348.037459)        [('tile_y', [-1, 16]), ('tile_x', [-1, 2])],None,14
-    No: 8   GFLOPS: 1.50/13.35      result: MeasureResult(costs=(0.1787965154,), error_no=MeasureErrorNo.NO_ERROR, all_cost=3.0967469215393066, timestamp=1706571351.1551347)       [('tile_y', [-1, 1]), ('tile_x', [-1, 1])],None,0
-    No: 9   GFLOPS: 11.80/13.35     result: MeasureResult(costs=(0.022750107600000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.584221601486206, timestamp=1706571351.849052) [('tile_y', [-1, 128]), ('tile_x', [-1, 512])],None,97
-    No: 10  GFLOPS: 11.49/13.35     result: MeasureResult(costs=(0.0233557672,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6027917861938477, timestamp=1706571352.4954147)       [('tile_y', [-1, 256]), ('tile_x', [-1, 512])],None,98
+    No: 1   GFLOPS: 9.49/9.49       result: MeasureResult(costs=(0.028277249999999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8736984729766846, timestamp=1706583503.4926963)       [('tile_y', [-1, 8]), ('tile_x', [-1, 128])],None,73
+    No: 2   GFLOPS: 9.61/9.61       result: MeasureResult(costs=(0.0279214988,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8893542289733887, timestamp=1706583504.203972)        [('tile_y', [-1, 2]), ('tile_x', [-1, 128])],None,71
+    No: 3   GFLOPS: 7.58/9.61       result: MeasureResult(costs=(0.035415316999999995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.82696533203125, timestamp=1706583505.0347772) [('tile_y', [-1, 2]), ('tile_x', [-1, 4])],None,21
+    No: 4   GFLOPS: 14.09/14.09     result: MeasureResult(costs=(0.0190562692,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6014492511749268, timestamp=1706583505.597567)        [('tile_y', [-1, 128]), ('tile_x', [-1, 64])],None,67
+    No: 5   GFLOPS: 11.76/14.09     result: MeasureResult(costs=(0.0228304454,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6438071727752686, timestamp=1706583506.4033966)       [('tile_y', [-1, 4]), ('tile_x', [-1, 256])],None,82
+    No: 6   GFLOPS: 9.11/14.09      result: MeasureResult(costs=(0.029456308200000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7988314628601074, timestamp=1706583507.1352098)       [('tile_y', [-1, 512]), ('tile_x', [-1, 64])],None,69
+    No: 7   GFLOPS: 10.24/14.09     result: MeasureResult(costs=(0.026208645799999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6654329299926758, timestamp=1706583507.818901)        [('tile_y', [-1, 512]), ('tile_x', [-1, 512])],None,99
+    No: 8   GFLOPS: 11.19/14.09     result: MeasureResult(costs=(0.0239912734,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.696274995803833, timestamp=1706583508.4603906)        [('tile_y', [-1, 1]), ('tile_x', [-1, 64])],None,60
+    No: 9   GFLOPS: 9.20/14.09      result: MeasureResult(costs=(0.029177793400000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6892180442810059, timestamp=1706583509.2608345)       [('tile_y', [-1, 512]), ('tile_x', [-1, 256])],None,89
+    No: 10  GFLOPS: 2.06/14.09      result: MeasureResult(costs=(0.1303867132,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.308297872543335, timestamp=1706583511.6073163)        [('tile_y', [-1, 256]), ('tile_x', [-1, 4])],None,28
 
 
 
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 9e4a045ca2..3a4a6a575a 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': 472.78118281999923, 'median': 472.4927659500054, 'std': 1.7815587371850354}
+    {'mean': 488.96065589000045, 'median': 489.13092864997907, 'std': 2.8590050185786398}
 
 
 
@@ -582,31 +582,30 @@ the tuning data to.
 
  .. code-block:: none
 
-
    [Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  1/25]  Current/Best:    9.41/  24.05 GFLOPS | Progress: (4/20) | 7.08 s
    [Task  1/25]  Current/Best:    7.80/  24.05 GFLOPS | Progress: (8/20) | 9.90 s
    [Task  1/25]  Current/Best:    6.75/  24.05 GFLOPS | Progress: (12/20) | 13.12 s
    [Task  1/25]  Current/Best:   12.15/  24.05 GFLOPS | Progress: (16/20) | 15.78 s
    [Task  1/25]  Current/Best:    3.43/  24.05 GFLOPS | Progress: (20/20) | 18.48 s Done.
-
    [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  2/25]  Current/Best:   14.20/  22.23 GFLOPS | Progress: (4/20) | 3.85 s
    [Task  2/25]  Current/Best:   15.66/  22.23 GFLOPS | Progress: (8/20) | 5.21 s
    [Task  2/25]  Current/Best:   14.15/  22.23 GFLOPS | Progress: (12/20) | 6.63 s
    [Task  2/25]  Current/Best:   12.37/  22.23 GFLOPS | Progress: (16/20) | 9.14 s
    [Task  2/25]  Current/Best:   17.64/  22.23 GFLOPS | Progress: (20/20) | 10.72 s Done.
-
    [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  3/25]  Current/Best:   10.57/  20.81 GFLOPS | Progress: (4/20) | 5.61 s
    [Task  3/25]  Current/Best:   24.49/  24.49 GFLOPS | Progress: (8/20) | 7.69 s
    [Task  3/25]  Current/Best:    5.44/  24.49 GFLOPS | Progress: (12/20) | 10.44 s
    [Task  3/25]  Current/Best:   10.80/  24.49 GFLOPS | Progress: (16/20) | 12.88 s
    [Task  3/25]  Current/Best:   14.27/  24.49 GFLOPS | Progress: (20/20) | 15.69 s Done.
-
    [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  4/25]  Current/Best:   12.31/  17.40 GFLOPS | Progress: (4/20) | 4.92 s
    [Task  4/25]  Current/Best:   13.07/  18.37 GFLOPS | Progress: (8/20) | 7.20 s
    [Task  4/25]  Current/Best:   13.00/  20.36 GFLOPS | Progress: (12/20) | 8.78 s
    [Task  4/25]  Current/Best:   10.33/  20.36 GFLOPS | Progress: (16/20) | 11.96 s
    [Task  4/25]  Current/Best:   19.09/  20.36 GFLOPS | Progress: (20/20) | 16.11 s Done.
-
    [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  5/25]  Current/Best:    5.54/  20.53 GFLOPS | Progress: (4/20) | 4.38 s
    [Task  5/25]  Current/Best:    8.31/  20.53 GFLOPS | Progress: (8/20) | 6.31 s
    [Task  5/25]  Current/Best:   11.58/  20.53 GFLOPS | Progress: (12/20) | 8.24 s
    [Task  5/25]  Current/Best:   17.85/  20.53 GFLOPS | Progress: (16/20) | 10.67 s
    [Task  5/25]  Current/Best:   14.35/  20.53 GFLOPS | Progress: (20/20) | 12.71 s Done.
-
    [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  6/25]  Current/Best:   11.51/  23.74 GFLOPS | Progress: (4/20) | 5.96 s
    [Task  6/25]  Current/Best:   14.68/  23.74 GFLOPS | Progress: (8/20) | 9.01 s
    [Task  6/25]  Current/Best:   15.76/  23.74 GFLOPS | Progress: (12/20) | 11.49 s
    [Task  6/25]  Current/Best:    5.85/  23.74 GFLOPS | Progress: (16/20) | 14.02 s
    [Task  6/25]  Current/Best:   15.00/  23.74 GFLOPS | Progress: (20/20) | 17.00 s Done.
-
    [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  7/25]  Current/Best:    9.28/  13.36 GFLOPS | Progress: (4/20) | 5.10 s
    [Task  7/25]  Current/Best:   13.00/  18.10 GFLOPS | Progress: (8/20) | 7.62 s
    [Task  7/25]  Current/Best:   20.16/  20.53 GFLOPS | Progress: (12/20) | 9.71 s
    [Task  7/25]  Current/Best:   16.35/  20.53 GFLOPS | Progress: (16/20) | 12.53 s
    [Task  7/25]  Current/Best:   19.57/  23.51 GFLOPS | Progress: (20/20) | 14.67 s Done.
-
    [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  8/25]  Current/Best:    8.17/  16.66 GFLOPS | Progress: (4/20) | 5.07 s
    [Task  8/25]  Current/Best:   12.54/  16.66 GFLOPS | Progress: (8/20) | 7.42 s
    [Task  8/25]  Current/Best:    7.84/  16.66 GFLOPS | Progress: (12/20) | 13.39 s
    [Task  8/25]  Current/Best:   16.38/  16.66 GFLOPS | Progress: (16/20) | 18.11 s
    [Task  8/25]  Current/Best:   12.42/  16.66 GFLOPS | Progress: (20/20) | 23.07 s Done.
-
    [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  9/25]  Current/Best:   22.31/  22.31 GFLOPS | Progress: (4/20) | 4.29 s
    [Task  9/25]  Current/Best:   17.14/  22.31 GFLOPS | Progress: (8/20) | 8.07 s
    [Task  9/25]  Current/Best:   13.72/  22.31 GFLOPS | Progress: (12/20) | 15.38 s
    [Task  9/25]  Current/Best:   11.18/  22.31 GFLOPS | Progress: (16/20) | 21.34 s
    [Task  9/25]  Current/Best:   11.39/  22.31 GFLOPS | Progress: (20/20) | 26.29 s Done.
-
    [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 10/25]  Current/Best:   12.67/  19.11 GFLOPS | Progress: (4/20) | 5.52 s
    [Task 10/25]  Current/Best:   19.03/  19.11 GFLOPS | Progress: (8/20) | 9.46 s
    [Task 10/25]  Current/Best:   20.57/  20.57 GFLOPS | Progress: (12/20) | 11.61 s
    [Task 10/25]  Current/Best:    6.26/  20.57 GFLOPS | Progress: (16/20) | 13.67 s
    [Task 10/25]  Current/Best:   11.15/  21.29 GFLOPS | Progress: (20/20) | 16.61 s Done.
-
    [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 11/25]  Current/Best:   20.36/  20.36 GFLOPS | Progress: (4/20) | 4.45 s
    [Task 11/25]  Current/Best:   10.94/  22.90 GFLOPS | Progress: (8/20) | 6.71 s
    [Task 11/25]  Current/Best:    7.54/  22.90 GFLOPS | Progress: (12/20) | 9.29 s
    [Task 11/25]  Current/Best:   20.55/  24.10 GFLOPS | Progress: (16/20) | 11.58 s
    [Task 11/25]  Current/Best:   15.64/  24.10 GFLOPS | Progress: (20/20) | 13.92 s Done.
-
    [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 12/25]  Current/Best:   12.33/  15.12 GFLOPS | Progress: (4/20) | 4.43 s
    [Task 12/25]  Current/Best:    9.00/  15.94 GFLOPS | Progress: (8/20) | 8.37 s
    [Task 12/25]  Current/Best:    9.49/  15.94 GFLOPS | Progress: (12/20) | 14.16 s
    [Task 12/25]  Current/Best:   17.99/  20.76 GFLOPS | Progress: (16/20) | 20.46 s
    [Task 12/25]  Current/Best:   19.57/  20.76 GFLOPS | Progress: (20/20) | 23.31 s Done.
-
    [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 13/25]  Current/Best:    1.62/  19.58 GFLOPS | Progress: (4/20) | 6.02 s
    [Task 13/25]  Current/Best:   11.07/  19.58 GFLOPS | Progress: (8/20) | 8.70 s
    [Task 13/25]  Current/Best:   10.19/  21.24 GFLOPS | Progress: (12/20) | 12.42 s
    [Task 13/25]  Current/Best:    3.18/  21.24 GFLOPS | Progress: (16/20) | 16.18 s
    [Task 13/25]  Current/Best:   22.19/  22.19 GFLOPS | Progress: (20/20) | 19.01 s Done.
-
    [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 14/25]  Current/Best:    7.39/  14.16 GFLOPS | Progress: (4/20) | 5.20 s
    [Task 14/25]  Current/Best:    9.95/  17.39 GFLOPS | Progress: (8/20) | 7.40 s
    [Task 14/25]  Current/Best:    6.97/  17.39 GFLOPS | Progress: (12/20) | 16.01 s
    [Task 14/25]  Current/Best:    5.70/  17.39 GFLOPS | Progress: (16/20) | 28.51 s
    [Task 14/25]  Current/Best:   11.15/  17.39 GFLOPS | Progress: (20/20) | 39.02 s Done.
-
    [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 15/25]  Current/Best:   18.78/  20.92 GFLOPS | Progress: (4/20) | 8.32 s
    [Task 15/25]  Current/Best:    8.70/  20.92 GFLOPS | Progress: (8/20) | 17.07 s
    [Task 15/25]  Current/Best:    7.55/  20.92 GFLOPS | Progress: (12/20) | 18.67 s
    [Task 15/25]  Current/Best:   17.16/  20.92 GFLOPS | Progress: (16/20) | 20.33 s
    [Task 15/25]  Current/Best:   19.26/  20.92 GFLOPS | Progress: (20/20) | 26.97 s Done.
-
    [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 16/25]  Current/Best:   16.64/  16.64 GFLOPS | Progress: (4/20) | 4.79 s
    [Task 16/25]  Current/Best:   19.98/  19.98 GFLOPS | Progress: (8/20) | 7.57 s
    [Task 16/25]  Current/Best:   13.40/  19.98 GFLOPS | Progress: (12/20) | 9.83 s
    [Task 16/25]  Current/Best:    3.99/  19.98 GFLOPS | Progress: (16/20) | 12.14 s
    [Task 16/25]  Current/Best:   20.30/  20.30 GFLOPS | Progress: (20/20) | 13.98 s Done.
-
    [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 17/25]  Current/Best:   12.03/  19.70 GFLOPS | Progress: (4/20) | 4.50 s
    [Task 17/25]  Current/Best:   21.41/  22.35 GFLOPS | Progress: (8/20) | 6.39 s
    [Task 17/25]  Current/Best:   21.42/  22.35 GFLOPS | Progress: (12/20) | 8.65 s
    [Task 17/25]  Current/Best:   15.67/  22.35 GFLOPS | Progress: (16/20) | 11.23 s
    [Task 17/25]  Current/Best:   19.67/  24.13 GFLOPS | Progress: (20/20) | 13.54 s Done.
-
    [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 18/25]  Current/Best:   18.98/  18.98 GFLOPS | Progress: (4/20) | 4.47 s
    [Task 18/25]  Current/Best:    6.43/  18.98 GFLOPS | Progress: (8/20) | 8.27 s
    [Task 18/25]  Current/Best:   15.06/  18.98 GFLOPS | Progress: (12/20) | 10.56 s
    [Task 18/25]  Current/Best:   14.08/  18.98 GFLOPS | Progress: (16/20) | 13.50 s
    [Task 18/25]  Current/Best:   16.04/  18.98 GFLOPS | Progress: (20/20) | 17.56 s Done.
-
    [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 19/25]  Current/Best:    5.49/  18.83 GFLOPS | Progress: (4/20) | 6.29 s
    [Task 19/25]  Current/Best:   12.08/  18.83 GFLOPS | Progress: (8/20) | 9.71 s
    [Task 19/25]  Current/Best:    5.09/  18.83 GFLOPS | Progress: (12/20) | 13.58 s
    [Task 19/25]  Current/Best:   22.12/  22.12 GFLOPS | Progress: (16/20) | 16.87 s
    [Task 19/25]  Current/Best:   17.32/  22.12 GFLOPS | Progress: (20/20) | 20.22 s Done.
-
    [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 20/25]  Current/Best:    8.61/  12.09 GFLOPS | Progress: (4/20) | 6.79 s
    [Task 20/25]  Current/Best:   18.14/  18.14 GFLOPS | Progress: (8/20) | 9.83 s
    [Task 20/25]  Current/Best:    8.52/  18.58 GFLOPS | Progress: (12/20) | 13.98 s
    [Task 20/25]  Current/Best:    3.18/  20.98 GFLOPS | Progress: (16/20) | 25.93 s
    [Task 20/25]  Current/Best:   12.37/  20.98 GFLOPS | Progress: (20/20) | 37.38 s
    [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 21/25]  Current/Best:    9.67/  21.38 GFLOPS | Progress: (4/20) | 13.61 s
    [Task 21/25]  Current/Best:    8.86/  21.38 GFLOPS | Progress: (8/20) | 20.48 s
    [Task 21/25]  Current/Best:   16.18/  21.38 GFLOPS | Progress: (12/20) | 31.79 s Done.
-
    [Task 21/25]  Current/Best:   19.02/  21.38 GFLOPS | Progress: (16/20) | 34.38 s
    [Task 21/25]  Current/Best:   15.22/  21.38 GFLOPS | Progress: (20/20) | 36.27 s Done.
-
    [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 22/25]  Current/Best:   16.64/  22.37 GFLOPS | Progress: (4/20) | 3.94 s
    [Task 22/25]  Current/Best:   11.51/  22.37 GFLOPS | Progress: (8/20) | 7.44 s
    [Task 22/25]  Current/Best:   16.70/  22.37 GFLOPS | Progress: (12/20) | 9.12 s
    [Task 22/25]  Current/Best:    2.83/  22.37 GFLOPS | Progress: (16/20) | 11.01 s
    [Task 22/25]  Current/Best:   14.16/  22.37 GFLOPS | Progress: (20/20) | 12.79 s Done.
-
    [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 23/25]  Current/Best:   12.29/  19.38 GFLOPS | Progress: (4/20) | 5.68 s
    [Task 23/25]  Current/Best:   18.27/  20.24 GFLOPS | Progress: (8/20) | 9.25 s
    [Task 23/25]  Current/Best:   22.35/  22.35 GFLOPS | Progress: (12/20) | 12.82 s
    [Task 23/25]  Current/Best:   11.33/  22.35 GFLOPS | Progress: (16/20) | 17.50 s
    [Task 23/25]  Current/Best:   12.41/  22.35 GFLOPS | Progress: (20/20) | 19.87 s Done.
-
    [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 24/25]  Current/Best:    2.20/  10.19 GFLOPS | Progress: (4/20) | 11.42 s
    [Task 24/25]  Current/Best:    3.63/  10.19 GFLOPS | Progress: (8/20) | 22.35 s
    [Task 24/25]  Current/Best:    9.85/  10.19 GFLOPS | Progress: (12/20) | 34.16 s
    [Task 24/25]  Current/Best:    3.94/  10.19 GFLOPS | Progress: (16/20) | 46.27 s
    [Task 24/25]  Current/Best:    4.99/  10.19 GFLOPS | Progress: (20/20) | 48.85 s
    [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 25/25]  Current/Best:    7.98/   7.98 GFLOPS | Progress: (4/20) | 7.53 s
    [Task 25/25]  Current/Best:    3.09/   9.96 GFLOPS | Progress: (8/20) | 9.13 s
    [Task 25/25]  Current/Best:    9.80/   9.96 GFLOPS | Progress: (12/20) | 11.51 s
    [Task 25/25]  Current/Best:    3.10/   9.96 GFLOPS | Progress: (16/20) | 13.54 s
    [Task 25/25]  Current/Best:    8.05/   9.96 GFLOPS | Progress: (20/
 20) | 14.89 s Done.
-
+
    [Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  1/25]  Current/Best:   11.97/  20.90 GFLOPS | Progress: (4/20) | 10.33 s
    [Task  1/25]  Current/Best:    8.73/  20.90 GFLOPS | Progress: (8/20) | 12.86 s
    [Task  1/25]  Current/Best:    7.55/  20.90 GFLOPS | Progress: (12/20) | 15.16 s
    [Task  1/25]  Current/Best:   17.20/  20.90 GFLOPS | Progress: (16/20) | 18.04 s
    [Task  1/25]  Current/Best:   11.02/  20.90 GFLOPS | Progress: (20/20) | 21.62 s Done.
+
    [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  2/25]  Current/Best:   13.62/  13.62 GFLOPS | Progress: (4/20) | 4.08 s
    [Task  2/25]  Current/Best:    7.51/  13.62 GFLOPS | Progress: (8/20) | 5.88 s
    [Task  2/25]  Current/Best:    6.59/  20.45 GFLOPS | Progress: (12/20) | 7.26 s
    [Task  2/25]  Current/Best:    9.07/  20.45 GFLOPS | Progress: (16/20) | 10.04 s
    [Task  2/25]  Current/Best:   12.25/  20.45 GFLOPS | Progress: (20/20) | 12.65 s Done.
+
    [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  3/25]  Current/Best:   19.34/  22.77 GFLOPS | Progress: (4/20) | 5.01 s
    [Task  3/25]  Current/Best:   24.34/  24.34 GFLOPS | Progress: (8/20) | 6.96 s
    [Task  3/25]  Current/Best:   13.34/  24.34 GFLOPS | Progress: (12/20) | 9.22 s
    [Task  3/25]  Current/Best:   12.57/  24.34 GFLOPS | Progress: (16/20) | 12.00 s
    [Task  3/25]  Current/Best:   19.77/  24.34 GFLOPS | Progress: (20/20) | 14.70 s Done.
+
    [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  4/25]  Current/Best:   11.06/  15.91 GFLOPS | Progress: (4/20) | 4.32 s
    [Task  4/25]  Current/Best:    7.50/  16.24 GFLOPS | Progress: (8/20) | 6.90 s
    [Task  4/25]  Current/Best:   20.21/  20.21 GFLOPS | Progress: (12/20) | 8.90 s
    [Task  4/25]  Current/Best:   10.42/  20.21 GFLOPS | Progress: (16/20) | 13.51 s
    [Task  4/25]  Current/Best:   11.16/  21.85 GFLOPS | Progress: (20/20) | 21.28 s Done.
+
    [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  5/25]  Current/Best:   14.94/  16.75 GFLOPS | Progress: (4/20) | 4.53 s
    [Task  5/25]  Current/Best:   19.22/  19.22 GFLOPS | Progress: (8/20) | 6.53 s
    [Task  5/25]  Current/Best:   14.33/  19.22 GFLOPS | Progress: (12/20) | 8.53 s
    [Task  5/25]  Current/Best:   14.36/  19.22 GFLOPS | Progress: (16/20) | 10.65 s
    [Task  5/25]  Current/Best:   16.57/  19.22 GFLOPS | Progress: (20/20) | 12.94 s Done.
+
    [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  6/25]  Current/Best:   17.13/  17.13 GFLOPS | Progress: (4/20) | 5.45 s
    [Task  6/25]  Current/Best:    6.82/  17.47 GFLOPS | Progress: (8/20) | 7.71 s
    [Task  6/25]  Current/Best:   14.40/  17.47 GFLOPS | Progress: (12/20) | 10.38 s
    [Task  6/25]  Current/Best:   11.57/  17.92 GFLOPS | Progress: (16/20) | 12.49 s
    [Task  6/25]  Current/Best:    4.11/  17.92 GFLOPS | Progress: (20/20) | 17.49 s Done.
+
    [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  7/25]  Current/Best:   13.00/  19.15 GFLOPS | Progress: (4/20) | 4.86 s
    [Task  7/25]  Current/Best:   17.98/  19.99 GFLOPS | Progress: (8/20) | 6.76 s
    [Task  7/25]  Current/Best:   12.03/  20.00 GFLOPS | Progress: (12/20) | 9.52 s
    [Task  7/25]  Current/Best:   14.03/  20.00 GFLOPS | Progress: (16/20) | 11.71 s
    [Task  7/25]  Current/Best:   12.42/  21.50 GFLOPS | Progress: (20/20) | 14.50 s Done.
+
    [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  8/25]  Current/Best:   11.73/  23.00 GFLOPS | Progress: (4/20) | 6.35 s
    [Task  8/25]  Current/Best:    2.87/  23.00 GFLOPS | Progress: (8/20) | 11.29 s
    [Task  8/25]  Current/Best:   12.01/  23.00 GFLOPS | Progress: (12/20) | 14.63 s
    [Task  8/25]  Current/Best:   14.75/  23.00 GFLOPS | Progress: (16/20) | 16.87 s
    [Task  8/25]  Current/Best:    2.84/  23.00 GFLOPS | Progress: (20/20) | 19.82 s Done.
+
    [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task  9/25]  Current/Best:   18.52/  18.52 GFLOPS | Progress: (4/20) | 9.99 s
    [Task  9/25]  Current/Best:   15.33/  18.52 GFLOPS | Progress: (8/20) | 11.84 s
    [Task  9/25]  Current/Best:   21.29/  21.29 GFLOPS | Progress: (12/20) | 13.98 s
    [Task  9/25]  Current/Best:   14.31/  21.29 GFLOPS | Progress: (16/20) | 15.70 s
    [Task  9/25]  Current/Best:   15.55/  21.29 GFLOPS | Progress: (20/20) | 19.62 s Done.
+
    [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 10/25]  Current/Best:   14.56/  16.98 GFLOPS | Progress: (4/20) | 4.68 s
    [Task 10/25]  Current/Best:   17.96/  18.97 GFLOPS | Progress: (8/20) | 6.32 s
    [Task 10/25]  Current/Best:   19.52/  19.52 GFLOPS | Progress: (12/20) | 8.24 s
    [Task 10/25]  Current/Best:   12.86/  19.52 GFLOPS | Progress: (16/20) | 10.29 s
    [Task 10/25]  Current/Best:   16.13/  19.52 GFLOPS | Progress: (20/20) | 11.99 s Done.
+
    [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 11/25]  Current/Best:   12.21/  23.96 GFLOPS | Progress: (4/20) | 4.52 s
    [Task 11/25]  Current/Best:    6.89/  23.96 GFLOPS | Progress: (8/20) | 8.44 s
    [Task 11/25]  Current/Best:   22.15/  23.96 GFLOPS | Progress: (12/20) | 10.40 s
    [Task 11/25]  Current/Best:   19.35/  23.96 GFLOPS | Progress: (16/20) | 12.69 s
    [Task 11/25]  Current/Best:   13.07/  23.96 GFLOPS | Progress: (20/20) | 16.40 s Done.
+
    [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 12/25]  Current/Best:   21.71/  23.86 GFLOPS | Progress: (4/20) | 4.25 s
    [Task 12/25]  Current/Best:   18.83/  23.86 GFLOPS | Progress: (8/20) | 7.68 s
    [Task 12/25]  Current/Best:   16.70/  23.86 GFLOPS | Progress: (12/20) | 9.90 s
    [Task 12/25]  Current/Best:    3.83/  23.86 GFLOPS | Progress: (16/20) | 13.12 s
    [Task 12/25]  Current/Best:   14.11/  23.86 GFLOPS | Progress: (20/20) | 15.24 s Done.
+
    [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 13/25]  Current/Best:   17.07/  19.07 GFLOPS | Progress: (4/20) | 4.65 s
    [Task 13/25]  Current/Best:   11.81/  19.07 GFLOPS | Progress: (8/20) | 8.47 s
    [Task 13/25]  Current/Best:   19.27/  19.27 GFLOPS | Progress: (12/20) | 11.05 s
    [Task 13/25]  Current/Best:    9.94/  19.66 GFLOPS | Progress: (16/20) | 13.29 s
    [Task 13/25]  Current/Best:   19.26/  19.66 GFLOPS | Progress: (20/20) | 16.11 s Done.
+
    [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 14/25]  Current/Best:   10.38/  14.50 GFLOPS | Progress: (4/20) | 6.65 s
    [Task 14/25]  Current/Best:   15.77/  18.66 GFLOPS | Progress: (8/20) | 11.46 s
    [Task 14/25]  Current/Best:   11.14/  18.67 GFLOPS | Progress: (12/20) | 13.91 s
    [Task 14/25]  Current/Best:   17.32/  18.67 GFLOPS | Progress: (16/20) | 16.98 s
    [Task 14/25]  Current/Best:    6.60/  18.67 GFLOPS | Progress: (20/20) | 27.89 s Done.
+
    [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 15/25]  Current/Best:   14.31/  14.31 GFLOPS | Progress: (4/20) | 4.66 s
    [Task 15/25]  Current/Best:   21.11/  21.11 GFLOPS | Progress: (8/20) | 11.85 s
    [Task 15/25]  Current/Best:    3.19/  21.11 GFLOPS | Progress: (12/20) | 22.42 s
    [Task 15/25]  Current/Best:   12.34/  21.11 GFLOPS | Progress: (16/20) | 26.79 s
    [Task 15/25]  Current/Best:    7.87/  21.11 GFLOPS | Progress: (20/20) | 33.54 s Done.
+
    [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 16/25]  Current/Best:    9.54/  19.72 GFLOPS | Progress: (4/20) | 4.47 s
    [Task 16/25]  Current/Best:    7.25/  19.72 GFLOPS | Progress: (8/20) | 6.52 s
    [Task 16/25]  Current/Best:    6.68/  19.72 GFLOPS | Progress: (12/20) | 8.61 s
    [Task 16/25]  Current/Best:   18.93/  19.72 GFLOPS | Progress: (16/20) | 10.54 s
    [Task 16/25]  Current/Best:    8.03/  19.72 GFLOPS | Progress: (20/20) | 12.29 s Done.
+
    [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 17/25]  Current/Best:   18.04/  18.04 GFLOPS | Progress: (4/20) | 6.20 s
    [Task 17/25]  Current/Best:   19.45/  19.45 GFLOPS | Progress: (8/20) | 8.48 s
    [Task 17/25]  Current/Best:    6.98/  21.61 GFLOPS | Progress: (12/20) | 11.64 s
    [Task 17/25]  Current/Best:    6.06/  22.68 GFLOPS | Progress: (16/20) | 14.39 s
    [Task 17/25]  Current/Best:   20.80/  22.68 GFLOPS | Progress: (20/20) | 17.31 s Done.
+
    [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 18/25]  Current/Best:    7.81/  18.57 GFLOPS | Progress: (4/20) | 4.91 s
    [Task 18/25]  Current/Best:   18.78/  22.11 GFLOPS | Progress: (8/20) | 6.98 s
    [Task 18/25]  Current/Best:    5.96/  22.11 GFLOPS | Progress: (12/20) | 10.83 s
    [Task 18/25]  Current/Best:    5.07/  22.11 GFLOPS | Progress: (16/20) | 13.31 s
    [Task 18/25]  Current/Best:   14.80/  22.11 GFLOPS | Progress: (20/20) | 17.74 s Done.
+
    [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 19/25]  Current/Best:    5.45/  10.68 GFLOPS | Progress: (4/20) | 6.41 s
    [Task 19/25]  Current/Best:   21.02/  21.50 GFLOPS | Progress: (8/20) | 9.75 s
    [Task 19/25]  Current/Best:   10.49/  21.50 GFLOPS | Progress: (12/20) | 13.11 s
    [Task 19/25]  Current/Best:   13.21/  21.50 GFLOPS | Progress: (16/20) | 19.00 s
    [Task 19/25]  Current/Best:   12.24/  21.50 GFLOPS | Progress: (20/20) | 23.80 s Done.
+
    [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 20/25]  Current/Best:    9.32/  17.72 GFLOPS | Progress: (4/20) | 15.16 s
    [Task 20/25]  Current/Best:   18.05/  18.08 GFLOPS | Progress: (8/20) | 24.87 s
    [Task 20/25]  Current/Best:    8.02/  18.08 GFLOPS | Progress: (12/20) | 27.83 s
    [Task 20/25]  Current/Best:   15.09/  18.08 GFLOPS | Progress: (16/20) | 30.19 s
    [Task 20/25]  Current/Best:    3.80/  19.86 GFLOPS | Progress: (20/20) | 36.28 s
    [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 21/25]  Current/Best:   10.68/  14.34 GFLOPS | Progress: (4/20) | 5.69 s
    [Task 21/25]  Current/Best:    6.70/  14.34 GFLOPS | Progress: (8/20) | 8.95 s
    [Task 21/25]  Current/Best:   21.09/  21.09 GFLOPS | Progress: (12/20) | 11.54 s
    [Task 21/25]  Current/Best:   13.63/  21.09 GFLOPS | Progress: (16/20) | 13.88 s
    [Task 21/25]  Current/Best:   16.77/  21.09 GFLOPS | Progress: (20/
 20) | 16.08 s Done.
+
    [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 22/25]  Current/Best:   15.21/  19.50 GFLOPS | Progress: (4/20) | 4.04 s
    [Task 22/25]  Current/Best:   19.48/  19.50 GFLOPS | Progress: (8/20) | 5.82 s
    [Task 22/25]  Current/Best:   17.73/  19.50 GFLOPS | Progress: (12/20) | 7.87 s
    [Task 22/25]  Current/Best:    1.58/  19.50 GFLOPS | Progress: (16/20) | 10.36 s
    [Task 22/25]  Current/Best:    9.19/  19.50 GFLOPS | Progress: (20/20) | 12.10 s Done.
+
    [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 23/25]  Current/Best:    9.29/  16.46 GFLOPS | Progress: (4/20) | 7.02 s
    [Task 23/25]  Current/Best:   21.01/  21.01 GFLOPS | Progress: (8/20) | 10.95 s
    [Task 23/25]  Current/Best:   20.55/  21.01 GFLOPS | Progress: (12/20) | 13.51 s
    [Task 23/25]  Current/Best:   12.11/  21.01 GFLOPS | Progress: (16/20) | 16.64 s
    [Task 23/25]  Current/Best:    9.97/  21.01 GFLOPS | Progress: (20/20) | 20.01 s Done.
+
    [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 24/25]  Current/Best:    1.42/   6.94 GFLOPS | Progress: (4/20) | 7.39 s
    [Task 24/25]  Current/Best:    2.91/   6.94 GFLOPS | Progress: (8/20) | 18.40 s
    [Task 24/25]  Current/Best:    9.16/   9.16 GFLOPS | Progress: (12/20) | 29.39 s Done.
+
    [Task 24/25]  Current/Best:    2.41/   9.16 GFLOPS | Progress: (16/20) | 36.83 s
    [Task 24/25]  Current/Best:    0.98/   9.16 GFLOPS | Progress: (20/20) | 47.89 s
    [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
    [Task 25/25]  Current/Best:    1.52/   5.64 GFLOPS | Progress: (4/20) | 13.50 s
    [Task 25/25]  Current/Best:    3.00/   9.16 GFLOPS | Progress: (8/20) | 16.73 s
    [Task 25/25]  Current/Best:    1.56/   9.27 GFLOPS | Progress: (12/20) | 23.68 s
    [Task 25/25]  Current/Best:    1.56/   9.27 GFLOPS | Progress: (16/20) | 25.75 s
    [Task 25/25]  Current/Best:    6.60/   9.27 GFLOPS | Progress: (20/20) | 29.00 s
 
 
 
@@ -675,6 +674,7 @@ model using optimized operators to speed up our computations.
  .. code-block:: none
 
      Done.
+     Done.
 
 
 
@@ -708,7 +708,7 @@ Verify that the optimized model runs and produces the same results:
 
  .. code-block:: none
 
-    class='n02123045 tabby, tabby cat' with probability=0.621104
+    class='n02123045 tabby, tabby cat' with probability=0.621105
     class='n02123159 tiger cat' with probability=0.356378
     class='n02124075 Egyptian cat' with probability=0.019712
     class='n02129604 tiger, Panthera tigris' with probability=0.001215
@@ -766,8 +766,8 @@ improvement in comparing the optimized model to the unoptimized model.
 
  .. code-block:: none
 
-    optimized: {'mean': 392.10471162999966, 'median': 392.5059785999565, 'std': 1.7312932702501085}
-    unoptimized: {'mean': 472.78118281999923, 'median': 472.4927659500054, 'std': 1.7815587371850354}
+    optimized: {'mean': 404.171723390009, 'median': 403.35173505000057, 'std': 2.4715070031973183}
+    unoptimized: {'mean': 488.96065589000045, 'median': 489.13092864997907, 'std': 2.8590050185786398}
 
 
 
@@ -790,7 +790,7 @@ profiling/benchmarking.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 12 minutes  52.917 seconds)
+   **Total running time of the script:** ( 12 minutes  41.331 seconds)
 
 
 .. _sphx_glr_download_tutorial_autotvm_relay_x86.py:
diff --git a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
index 434fd0d4ae..a91f54b64e 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
 
-    1.186e-07 secs/op
+    1.22e-07 secs/op
 
 
 
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index 55ee4c35ed..e2c7c5077c 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, 0x26c7a590)), stage(b, placeholder(b, 0x28e07900)), 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, 0x12e62ac0)), stage(b, placeholder(b, 0x131cde30)), 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 fe67e94815..e88e14ab9e 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,24 +5,24 @@
 
 Computation times
 =================
-**16:28.118** total execution time for **tutorial** files:
+**16:08.995** total execution time for **tutorial** files:
 
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 12:52.917 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 12:41.331 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:33.025 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:29.500 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 00:57.773 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 00:58.615 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:41.652 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:42.937 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:20.800 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:14.607 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.928 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.949 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:00.837 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:00.858 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.186 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.198 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_uma.py` (``uma.py``)                                             | 00:00.000 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
@@ -30,7 +30,7 @@ Computation times
 +------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)                             | 00:00.000 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_install.py` (``install.py``)                                     | 00:00.000 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
 | :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 a5e1041211..049675e60a 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -389,7 +389,7 @@ compile and run this new schedule with the parallel operation applied:
 
  .. code-block:: none
 
-    parallel: 0.000006
+    parallel: 0.000007
 
 
 
@@ -444,7 +444,7 @@ factor to be the number of threads on your CPU.
 
  .. code-block:: none
 
-    vector: 0.000038
+    vector: 0.000041
     # 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    6.854769999335986e-06                    1.0
-                   naive              7.7089e-06      1.1246037431958698
-                parallel    6.305800000000001e-06     0.9199141620522405
-                  vector             3.80685e-05       5.553578019931764
+                   numpy    7.053879999148194e-06                    1.0
+                   naive              7.7898e-06      1.1043283981214131
+                parallel              6.8526e-06      0.9714653496837911
+                  vector             4.11998e-05       5.840728791101517
 
 
 
@@ -922,7 +922,7 @@ matrix multiplication.
 
  .. code-block:: none
 
-    Numpy running time: 0.016611
+    Numpy running time: 0.017873
 
 
 
@@ -980,7 +980,7 @@ optimizations.
 
  .. code-block:: none
 
-    none: 3.274869
+    none: 3.295010
 
 
 
@@ -1080,7 +1080,7 @@ schedule.
 
  .. code-block:: none
 
-    blocking: 0.299654
+    blocking: 0.302306
 
 
 
@@ -1164,7 +1164,7 @@ already cache friendly from our previous optimizations.
 
  .. code-block:: none
 
-    vectorization: 0.270210
+    vectorization: 0.278870
     # 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: 0.112230
+    loop permutation: 0.116149
     # 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: 0.103772
+    array packing: 0.104551
     # 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: 0.100726
+    block caching: 0.108966
     # 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: 0.119668
+    parallelization: 0.129152
     # 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      3.2748691253000004                     1.0
-                blocking            0.2996541992     0.09150112194866708
-           vectorization     0.27021035849999997     0.08251027694892903
-        loop permutation            0.1122299761     0.03427006448378879
-           array packing            0.1037720111     0.03168737654225916
-           block caching            0.1007260496     0.03075727479362181
-         parallelization     0.11966844299999999     0.03654144285507518
+                    none             3.295010456                     1.0
+                blocking            0.3023064685     0.09174674027195256
+           vectorization            0.2788703474     0.08463413124902083
+        loop permutation            0.1161490822    0.035249988960884805
+           array packing     0.10455061780000001    0.031729980586137484
+           block caching     0.10896627650000001     0.03307008519550507
+         parallelization            0.1291516268     0.03919612047507263
 
 
 
diff --git a/docs/commit_hash b/docs/commit_hash
index da4dfb3763..e1c23ce5e2 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-5092c003de6424332d9179ddd405540092b96742
+ff9ebadf6ae6bdf2fbfe5eb220d770b0ed9550cd
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index 137326cda5..1a9956110a 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -605,7 +605,7 @@ class:[&#39;truck 0.9266&#39;] left:471 top:83 right:689 bottom:169
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 </pre></div>
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  36.143 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-darknet-py">
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diff --git a/docs/how_to/compile_models/from_mxnet.html b/docs/how_to/compile_models/from_mxnet.html
index 3a30873cdd..fc1c8058d8 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">&quot;x&quot;</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>
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+<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.zip81703467-a908-4e79-bdf5-9b978b7dec49 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
 x (1, 3, 224, 224)
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 </div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index e364fa00ff..e818a024c5 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -469,14 +469,13 @@ 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: &quot;https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip&quot; to /workspace/.oneflow/flowvision_cache/resnet18.zip
 
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+ 96%|#########6| 40.0M/41.5M [00:00&lt;00:00, 52.1MB/s]
+100%|##########| 41.5M/41.5M [00:00&lt;00:00, 50.3MB/s]
 </pre></div>
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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 f60e58cbe9..9701034e30 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&gt;=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: &#39;tiger cat&#39;,
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  1.305 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  2.038 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 6b5e54916d..7b38d2679d 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -452,14 +452,16 @@ be unstable.</p>
 Downloading: &quot;https://download.pytorch.org/models/resnet18-f37072fd.pth&quot; to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
 
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+ 86%|########5 | 38.3M/44.7M [00:01&lt;00:00, 37.8MB/s]
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 </pre></div>
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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 36f38d4935..04dfdd106e 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  30.490 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  32.488 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 a026000f33..c52cd183c0 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>07:07.307</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>07:18.067</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 @@
 </colgroup>
 <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>
-<td><p>01:32.012</p></td>
+<td><p>01:36.143</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>
-<td><p>01:30.490</p></td>
+<td><p>01:32.488</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="from_paddle.html#sphx-glr-how-to-compile-models-from-paddle-py"><span class="std std-ref">Compile PaddlePaddle Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_paddle.py</span></code>)</p></td>
-<td><p>01:01.305</p></td>
+<td><p>01:02.038</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="from_oneflow.html#sphx-glr-how-to-compile-models-from-oneflow-py"><span class="std std-ref">Compile OneFlow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_oneflow.py</span></code>)</p></td>
-<td><p>00:41.990</p></td>
+<td><p>00:42.880</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <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>00:37.824</p></td>
+<td><p>00:39.513</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <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>
-<td><p>00:33.929</p></td>
+<td><p>00:34.130</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="from_pytorch.html#sphx-glr-how-to-compile-models-from-pytorch-py"><span class="std std-ref">Compile PyTorch Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_pytorch.py</span></code>)</p></td>
-<td><p>00:28.689</p></td>
+<td><p>00:29.481</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="from_keras.html#sphx-glr-how-to-compile-models-from-keras-py"><span class="std std-ref">Compile Keras Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_keras.py</span></code>)</p></td>
-<td><p>00:26.587</p></td>
+<td><p>00:26.645</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="from_tflite.html#sphx-glr-how-to-compile-models-from-tflite-py"><span class="std std-ref">Compile TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tflite.py</span></code>)</p></td>
-<td><p>00:11.674</p></td>
+<td><p>00:11.905</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>00:02.807</p></td>
+<td><p>00:02.844</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno.html b/docs/how_to/deploy_models/deploy_model_on_adreno.html
index 3b8f75f9f5..7ff290a782 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)
- 3994.9549    3993.3806    4005.8477    3991.9933      3.9112
+ 4060.6587    4060.0478    4068.1229    4057.3194      3.0713
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  17.463 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  19.156 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">
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 <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 1188f293c5..474b23d1b4 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
@@ -458,26 +458,31 @@ 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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+ 98910208/102967424 [===========================&gt;..] - ETA: 0s
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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 1ec503fea0..58840db2dc 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)
-  14.8813      14.7918      15.7025      14.4293       0.3654
+  15.3189      15.0604      16.8794      14.7576       0.6523
 </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 12714fc5f3..4c0b54bd7e 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -474,32 +474,37 @@ be unstable.</p>
 Downloading: &quot;https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth&quot; 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).
@@ -590,7 +595,7 @@ 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  34.732 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  35.111 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 91f6b140e2..39afe9645e 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -515,8 +515,8 @@ training. Other models require a full post training calibration.</p>
 Downloading: &quot;https://download.pytorch.org/models/mobilenet_v2-b0353104.pth&quot; to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
 
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 </pre></div>
 </div>
 </div>
@@ -607,7 +607,7 @@ 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)
-  86.3076      86.2584      88.7853      85.8978       0.3716
+  87.6607      87.5686      91.7020      87.3378       0.4483
 </pre></div>
 </div>
 <div class="admonition note">
@@ -646,7 +646,7 @@ 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  28.708 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  29.509 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 5c50fae24c..0084a1fa9d 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)
-  108.0301     107.8679     118.8993     107.4367      1.1204
+  111.0633     110.9595     114.5839     110.2779      0.5693
 </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 41fe1b4d8e..1a57b64857 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  52.534 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  56.862 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 83d173c1cf..e65d4178c1 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>11:44.222</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>11:49.775</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>03:34.732</p></td>
+<td><p>03:35.111</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>01:52.534</p></td>
+<td><p>01:56.862</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>01:28.708</p></td>
+<td><p>01:29.509</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>01:17.463</p></td>
+<td><p>01:19.156</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_android.html#sphx-glr-how-to-deploy-models-deploy-model-on-android-py"><span class="std std-ref">Deploy the Pretrained Model on Android</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_android.py</span></code>)</p></td>
-<td><p>00:51.622</p></td>
+<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>00:52.505</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-even"><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>00:51.102</p></td>
+<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>00:50.434</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>00:47.474</p></td>
+<td><p>00:45.887</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>00:30.598</p></td>
+<td><p>00:30.343</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>00:29.983</p></td>
+<td><p>00:29.963</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 ced0141db0..40d8da6d5a 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.zipae9fb4fd-6ff9-4157-98f3-3ee21179283e 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.zip93db1147-ecd7-4326-8589-9950387d19e7 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 51ab208cf5..7cbc34cbc2 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>00:57.757</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:59.467</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 84%" />
@@ -369,19 +369,19 @@
 </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>00:53.794</p></td>
+<td><p>00:55.257</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>00:02.790</p></td>
+<td><p>00:02.962</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>00:01.166</p></td>
+<td><p>00:01.241</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>
-<td><p>00:00.007</p></td>
+<td><p>00:00.008</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index c58717183e..ebb7bbbdcf 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: 24980us [24980us] (48.76%; 48.76%)
-FoldScaleAxis: 26248us [8us] (51.24%; 51.24%)
-        FoldConstant: 26240us [1832us] (51.22%; 99.97%)
-                InferType: 24408us [24408us] (47.65%; 93.02%)
+InferType: 25338us [25338us] (48.29%; 48.29%)
+FoldScaleAxis: 27130us [9us] (51.71%; 51.71%)
+        FoldConstant: 27121us [1908us] (51.69%; 99.97%)
+                InferType: 25213us [25213us] (48.05%; 92.96%)
 </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: 24398us [24398us] (48.23%; 48.23%)
-FoldScaleAxis: 26190us [8us] (51.77%; 51.77%)
-        FoldConstant: 26183us [1887us] (51.76%; 99.97%)
-                InferType: 24295us [24295us] (48.03%; 92.79%)
+InferType: 25309us [25309us] (48.30%; 48.30%)
+FoldScaleAxis: 27094us [10us] (51.70%; 51.70%)
+        FoldConstant: 27084us [1933us] (51.68%; 99.96%)
+                InferType: 25151us [25151us] (48.00%; 92.86%)
 </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 c0da8085de..1913364a22 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">&quot;Convolution: </span><span class="si">%f</span><span class="s2"> ms&quot;</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: 40.226814 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 41.797313 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 382e922abe..7562bd58fd 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">&quot;conv2d with tensor core: </span><span class="si">%f</span><span class="s2"> ms&quot;</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: 12.267565 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.267660 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 952b657139..5f5662430c 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">&quot;Baseline: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.017383
-Baseline: 3.271250
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.018671
+Baseline: 3.308058
 </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">&quot;Opt1: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.310946
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.304783
 </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">&quot;Opt2: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.313008
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.295418
 </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">&quot;Opt3: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.114952
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.116884
 </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">&quot;Opt4: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.102377
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.105651
 </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">&quot;Opt5: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.100968
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.110050
 </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">&quot;Opt6: </span><span class="si">%f</span><span class="s2">&quot;</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: 0.120452
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.131391
 </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 56c938ef5a..680cf7e5a1 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>00:33.080</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:33.787</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>00:30.081</p></td>
+<td><p>00:30.766</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>00:01.857</p></td>
+<td><p>00:01.869</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>00:01.141</p></td>
+<td><p>00:01.152</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 407bcd166d..7a06cafcca 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>03:34.687</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>03:38.586</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>01:33.518</p></td>
+<td><p>01:34.005</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>01:12.030</p></td>
+<td><p>01:13.720</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>00:17.513</p></td>
+<td><p>00:18.380</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>00:15.981</p></td>
+<tr class="row-even"><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>00:16.362</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>00:15.544</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
+<td><p>00:16.017</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>00:00.101</p></td>
+<td><p>00:00.102</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 742afe8535..0dba98e633 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: 0.354 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.353 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 257b4f9a46..068a62679c 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)
-   3.3096       3.3085       3.3152       3.3050       0.0043
+   3.2771       3.2685       3.2947       3.2682       0.0124
 </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  12.030 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  13.720 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 c0bf0f6e3f..a4860d6e32 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)
-  725.6079     726.1941     726.2311     724.3986      0.8553
+  744.6371     744.5805     748.4943     740.8363      3.1266
 </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>
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 <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>
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 ,None
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+tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.966     0.322    (1, 1, 10, 10, 3)  1       1        [0.966]
+Total_time                                    -                                             300.025   -        -                  -       -        -
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 <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)
 ---------                                     ---                                           --------  -------  -----              ------  -------  ----------------
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-tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.846     0.622    (1, 3, 10, 10, 1)  1       1        [0.846]
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+tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  102.6     97.442   (1, 6, 10, 10, 1)  2       1        [102.6]
+tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.753     1.665    (1, 6, 10, 10)     1       1        [1.753]
+tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.94      0.892    (1, 1, 10, 10, 3)  1       1        [0.94]
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diff --git a/docs/how_to/work_with_microtvm/micro_pytorch.html b/docs/how_to/work_with_microtvm/micro_pytorch.html
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--- a/docs/how_to/work_with_microtvm/micro_pytorch.html
+++ 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: &quot;https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth&quot; to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
 
   0%|          | 0.00/3.42M [00:00&lt;?, ?B/s]
- 61%|######    | 2.09M/3.42M [00:00&lt;00:00, 13.4MB/s]
-100%|##########| 3.42M/3.42M [00:00&lt;00:00, 20.7MB/s]
+ 61%|######    | 2.09M/3.42M [00:00&lt;00:00, 13.0MB/s]
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   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
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 </pre></div>
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--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
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@@ -603,8 +603,8 @@ objects to other stuff? We can display some examples from our datasets using <co
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-328/328 - 35s - loss: 0.0960 - accuracy: 0.9653 - val_loss: 0.1039 - val_accuracy: 0.9619 - 35s/epoch - 105ms/step
+328/328 - 35s - loss: 0.1001 - accuracy: 0.9630 - val_loss: 0.1408 - val_accuracy: 0.9498 - 35s/epoch - 108ms/step
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+328/328 - 35s - loss: 0.0670 - accuracy: 0.9752 - val_loss: 0.1027 - val_accuracy: 0.9690 - 35s/epoch - 107ms/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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 <span id="sphx-glr-how-to-work-with-microtvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
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 <tr class="row-odd"><td><p><a class="reference internal" href="micro_ethosu.html#sphx-glr-how-to-work-with-microtvm-micro-ethosu-py"><span class="std std-ref">7. Running TVM on bare metal Arm(R) Cortex(R)-M55 CPU and Ethos(TM)-U55 NPU with CMSIS-NN</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_ethosu.py</span></code>)</p></td>
diff --git a/docs/how_to/work_with_relay/sg_execution_times.html b/docs/how_to/work_with_relay/sg_execution_times.html
index f9219d8dad..f13e660ed3 100644
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+++ b/docs/how_to/work_with_relay/sg_execution_times.html
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 <span id="sphx-glr-how-to-work-with-relay-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:38.516</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:39.428</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
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@@ -369,15 +369,15 @@
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+<td><p>00:34.234</p></td>
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-<td><p>00:03.119</p></td>
+<td><p>00:03.154</p></td>
 <td><p>0.0 MB</p></td>
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 <tr class="row-odd"><td><p><a class="reference internal" href="build_gcn.html#sphx-glr-how-to-work-with-relay-build-gcn-py"><span class="std std-ref">Building a Graph Convolutional Network</span></a> (<code class="docutils literal notranslate"><span class="pre">build_gcn.py</span></code>)</p></td>
-<td><p>00:01.819</p></td>
+<td><p>00:02.033</p></td>
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diff --git a/docs/how_to/work_with_schedules/intrin_math.html b/docs/how_to/work_with_schedules/intrin_math.html
index d5168822ad..99ac26000c 100644
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-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;function my_cuda_math_rule at 0x7f458a08eee0&gt;
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 <p>Register the rule to TVM with override option to override existing rule.
diff --git a/docs/how_to/work_with_schedules/sg_execution_times.html b/docs/how_to/work_with_schedules/sg_execution_times.html
index d01c4196bc..6da7325fa9 100644
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 <span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:05.573</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:05.710</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
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 <tr class="row-even"><td><p><a class="reference internal" href="tensorize.html#sphx-glr-how-to-work-with-schedules-tensorize-py"><span class="std std-ref">Use Tensorize to Leverage Hardware Intrinsics</span></a> (<code class="docutils literal notranslate"><span class="pre">tensorize.py</span></code>)</p></td>
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 <td><p>0.0 MB</p></td>
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 <tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
-<td><p>00:00.717</p></td>
+<td><p>00:00.728</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="scan.html#sphx-glr-how-to-work-with-schedules-scan-py"><span class="std std-ref">Scan and Recurrent Kernel</span></a> (<code class="docutils literal notranslate"><span class="pre">scan.py</span></code>)</p></td>
-<td><p>00:00.704</p></td>
+<td><p>00:00.718</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="extern_op.html#sphx-glr-how-to-work-with-schedules-extern-op-py"><span class="std std-ref">External Tensor Functions</span></a> (<code class="docutils literal notranslate"><span class="pre">extern_op.py</span></code>)</p></td>
-<td><p>00:00.115</p></td>
+<td><p>00:00.120</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="schedule_primitives.html#sphx-glr-how-to-work-with-schedules-schedule-primitives-py"><span class="std std-ref">Schedule Primitives in TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">schedule_primitives.py</span></code>)</p></td>
-<td><p>00:00.069</p></td>
+<td><p>00:00.073</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="tedd.html#sphx-glr-how-to-work-with-schedules-tedd-py"><span class="std std-ref">Use Tensor Expression Debug Display (TEDD) for Visualization</span></a> (<code class="docutils literal notranslate"><span class="pre">tedd.py</span></code>)</p></td>
-<td><p>00:00.065</p></td>
+<td><p>00:00.067</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="tuple_inputs.html#sphx-glr-how-to-work-with-schedules-tuple-inputs-py"><span class="std std-ref">Compute and Reduce with Tuple Inputs</span></a> (<code class="docutils literal notranslate"><span class="pre">tuple_inputs.py</span></code>)</p></td>
-<td><p>00:00.031</p></td>
+<td><p>00:00.033</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
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diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index 11b13eee15..62df4395d3 100644
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 <dd><p>The search policy that searches in a hierarchical search space defined by sketches.
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@@ -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 [...]
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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="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/5092c003d/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/ff9ebadf6/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>
@@ -70,14 +70,14 @@
 <div class="tsd-comment tsd-typography"><p>The device index.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L342">runtime.ts:342</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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>
 <div class="tsd-comment tsd-typography"><p>The device type code of the device.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -89,7 +89,7 @@
 </div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -97,7 +97,7 @@
 <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/5092c003d/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/ff9ebadf6/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 5b057404c0..d752d9bbb6 100644
--- a/docs/reference/api/typedoc/classes/Instance.html
+++ b/docs/reference/api/typedoc/classes/Instance.html
@@ -40,7 +40,7 @@ are not tracked through JS native garbage collection mechanism.</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/5092c003d/web/src/runtime.ts#L1040">runtime.ts:1040</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1040">runtime.ts:1040</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">
@@ -139,24 +139,24 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <a href="Instance.html" class="tsd-signature-type tsd-kind-class">Instance</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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">&lt;</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">&gt;</span><span class="tsd-signature-symbol"> = {}</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1043">runtime.ts:1043</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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">&lt;</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">&gt;</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1042">runtime.ts:1042</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/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/ff9ebadf6/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>
@@ -183,7 +183,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">any</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -204,7 +204,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">any</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -221,7 +221,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -248,7 +248,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -258,7 +258,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -293,7 +293,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 <h5><span class="tsd-kind-parameter">repeat</span>: <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 1</span></h5></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -310,7 +310,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -320,7 +320,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -337,7 +337,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -355,7 +355,7 @@ a WASI object, or an object containing wasmLibraryProvider field.</p>
 <h4 class="tsd-returns-title">Returns <a href="VirtualMachine.html" class="tsd-signature-type tsd-kind-class">VirtualMachine</a></h4><p>The created virtual machime.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -381,7 +381,7 @@ so it won&#39;t be released via auto-release during endscope.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -403,7 +403,7 @@ so it won&#39;t be released via auto-release during endscope.</p>
 <h4 class="tsd-returns-title">Returns <a href="DLDevice.html" class="tsd-signature-type tsd-kind-class">DLDevice</a></h4><p>The created device.</p>
 <aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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 <p>Implementation of <a href="../interfaces/Disposable.html">Disposable</a>.<a href="../interfaces/Disposable.html#dispose">dispose</a></p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -442,7 +442,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -455,7 +455,7 @@ a value to parent scope.</p>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -481,7 +481,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -499,7 +499,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -520,7 +520,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -538,7 +538,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1409">runtime.ts:1409</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -573,7 +573,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1342">runtime.ts:1342</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -584,7 +584,7 @@ a value to parent scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1235">runtime.ts:1235</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -602,7 +602,7 @@ a value to parent scope.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1838">runtime.ts:1838</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -620,7 +620,7 @@ a value to parent scope.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1829">runtime.ts:1829</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -640,7 +640,7 @@ and needs to b explicitly disposed.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1817">runtime.ts:1817</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -665,7 +665,7 @@ alive when exit the current scope.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1205">runtime.ts:1205</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1205">runtime.ts:1205</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="ndarrayCacheClear" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>ndarray<wbr/>Cache<wbr/>Clear</span><a href="#ndarrayCacheClear" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -675,7 +675,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1449">runtime.ts:1449</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1449">runtime.ts:1449</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="ndarrayCacheGet" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>ndarray<wbr/>Cache<wbr/>Get</span><a href="#ndarrayCacheGet" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -693,7 +693,7 @@ alive when exit the current scope.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1422">runtime.ts:1422</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1422">runtime.ts:1422</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="ndarrayCacheRemove" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>ndarray<wbr/>Cache<wbr/>Remove</span><a href="#ndarrayCacheRemove" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -711,7 +711,7 @@ alive when exit the current scope.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L1431">runtime.ts:1431</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1431">runtime.ts:1431</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="ndarrayCacheUpdate" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>ndarray<wbr/>Cache<wbr/>Update</span><a href="#ndarrayCacheUpdate" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -734,7 +734,7 @@ alive when exit the current scope.</p>
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 <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/5092c003d/web/src/runtime.ts#L1440">runtime.ts:1440</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1440">runtime.ts:1440</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerAsyncServerFunc" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Async<wbr/>Server<wbr/>Func</span><a href="#registerAsyncServerFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -761,7 +761,7 @@ alive when exit the current scope.</p>
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 <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/5092c003d/web/src/runtime.ts#L1896">runtime.ts:1896</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1896">runtime.ts:1896</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerFunc" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Func</span><a href="#registerFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -784,7 +784,7 @@ alive when exit the current scope.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1274">runtime.ts:1274</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1636">runtime.ts:1636</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L2121">runtime.ts:2121</a></li></ul></aside></li></ul></section>
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@@ -931,7 +931,7 @@ Allocate new temporary space from the stack if necessary.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1782">runtime.ts:1782</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L1228">runtime.ts:1228</a></li></ul></aside></li></ul></section>
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@@ -961,7 +961,7 @@ 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/ff9ebadf6/web/src/runtime.ts#L1590">runtime.ts:1590</a></li></ul></aside></li></ul></section>
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@@ -979,7 +979,7 @@ 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/ff9ebadf6/web/src/runtime.ts#L1353">runtime.ts:1353</a></li></ul></aside></li></ul></section>
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@@ -997,7 +997,7 @@ 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/ff9ebadf6/web/src/runtime.ts#L1847">runtime.ts:1847</a></li></ul></aside></li></ul></section>
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@@ -1027,7 +1027,7 @@ 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/ff9ebadf6/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>
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@@ -1044,7 +1044,7 @@ 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/ff9ebadf6/web/src/runtime.ts#L1662">runtime.ts:1662</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 26147835cd..fdad82134b 100644
--- a/docs/reference/api/typedoc/classes/Module.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L686">runtime.ts:686</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L686">runtime.ts:686</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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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 <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>
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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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -110,7 +110,7 @@ only the first call will take effect.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L729">runtime.ts:729</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -128,7 +128,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L716">runtime.ts:716</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -145,7 +145,7 @@ 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/ff9ebadf6/web/src/runtime.ts#L763">runtime.ts:763</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/NDArray.html b/docs/reference/api/typedoc/classes/NDArray.html
index 4a06a13994..68e0f64caf 100644
--- a/docs/reference/api/typedoc/classes/NDArray.html
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L429">runtime.ts:429</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/web/src/runtime.ts#L449">runtime.ts:449</a></li></ul></aside></li></ul></section></section>
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 <section class="tsd-panel tsd-member"><a id="device" class="tsd-anchor"></a>
@@ -85,35 +85,35 @@
 <div class="tsd-comment tsd-typography"><p>Device of the array.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L439">runtime.ts:439</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L439">runtime.ts:439</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L435">runtime.ts:435</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/5092c003d/web/src/runtime.ts#L441">runtime.ts:441</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L441">runtime.ts:441</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L433">runtime.ts:433</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L433">runtime.ts:433</a></li></ul></aside></section>
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 <h3 class="tsd-anchor-link"><span>shape</span><a href="#shape" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L437">runtime.ts:437</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="copyFrom" class="tsd-anchor"></a>
@@ -134,7 +134,7 @@ The number of elements must match.</p>
 <h4 class="tsd-returns-title">Returns <a href="NDArray.html" class="tsd-signature-type tsd-kind-class">NDArray</a></h4><p>this</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L549">runtime.ts:549</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -152,7 +152,7 @@ The number of elements must match.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -165,7 +165,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -176,7 +176,7 @@ only the first call will take effect.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -194,7 +194,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L515">runtime.ts:515</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -206,7 +206,7 @@ the dtype of the NDArray.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L659">runtime.ts:659</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -217,7 +217,7 @@ the dtype of the NDArray.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L628">runtime.ts:628</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -235,7 +235,7 @@ 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/ff9ebadf6/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
index d0c3b39887..19d8d9b3a6 100644
--- 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/5092c003d/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/ff9ebadf6/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li></ul></aside>
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 <h4 class="tsd-returns-title">Returns <a href="RPCServer.html" class="tsd-signature-type tsd-kind-class">RPCServer</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/web/src/rpc_server.ts#L100">rpc_server.ts:100</a></li></ul></aside></li></ul></section></section>
 <section class="tsd-panel-group tsd-member-group">
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 <section class="tsd-panel tsd-member"><a id="getImports" class="tsd-anchor"></a>
@@ -113,12 +113,12 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/rpc_server.ts#L83">rpc_server.ts:83</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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>
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 <div class="tsd-signature"><span class="tsd-kind-property">key</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">string</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="socket" class="tsd-anchor"></a>
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 <div class="tsd-signature"><span class="tsd-kind-property">socket</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type ">WebSocket</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="state" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/Scalar.html b/docs/reference/api/typedoc/classes/Scalar.html
index 71cd677c54..f8225f1a37 100644
--- a/docs/reference/api/typedoc/classes/Scalar.html
+++ b/docs/reference/api/typedoc/classes/Scalar.html
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 <li><span class="target">Scalar</span></li></ul></section><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L276">runtime.ts:276</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L276">runtime.ts:276</a></li></ul></aside>
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@@ -55,7 +55,7 @@ argument to PackedFunc calls.</p>
 <h5><span class="tsd-kind-parameter">dtype</span>: <span class="tsd-signature-type">string</span></h5></li></ul></div>
 <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/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L282">runtime.ts:282</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="dtype" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L280">runtime.ts:280</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L280">runtime.ts:280</a></li></ul></aside></section>
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 <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>
 <div class="tsd-comment tsd-typography"><p>The value.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L278">runtime.ts:278</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/TVMArray.html b/docs/reference/api/typedoc/classes/TVMArray.html
index 723e94045c..8420b0d962 100644
--- a/docs/reference/api/typedoc/classes/TVMArray.html
+++ b/docs/reference/api/typedoc/classes/TVMArray.html
@@ -25,7 +25,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L860">runtime.ts:860</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L860">runtime.ts:860</a></li></ul></aside>
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@@ -63,7 +63,7 @@
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 <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/5092c003d/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/ff9ebadf6/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>
@@ -78,7 +78,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -96,7 +96,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -115,7 +115,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -125,7 +125,7 @@ only the first call will take effect.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-is-inherited">
@@ -136,7 +136,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-is-inherited">
@@ -147,7 +147,7 @@ only the first call will take effect.</p>
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 <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/5092c003d/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/ff9ebadf6/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/TVMObject.html b/docs/reference/api/typedoc/classes/TVMObject.html
index 587f85df0e..a782917813 100644
--- a/docs/reference/api/typedoc/classes/TVMObject.html
+++ b/docs/reference/api/typedoc/classes/TVMObject.html
@@ -30,7 +30,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L776">runtime.ts:776</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L776">runtime.ts:776</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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@@ -65,7 +65,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -80,7 +80,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -98,7 +98,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><p>The handle.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -108,7 +108,7 @@ only the first call will take effect.</p>
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 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -118,7 +118,7 @@ only the first call will take effect.</p>
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 <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/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L834">runtime.ts:834</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/VirtualMachine.html b/docs/reference/api/typedoc/classes/VirtualMachine.html
index 15e6e14746..5d5ea93e13 100644
--- a/docs/reference/api/typedoc/classes/VirtualMachine.html
+++ b/docs/reference/api/typedoc/classes/VirtualMachine.html
@@ -30,7 +30,7 @@
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 <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/5092c003d/web/src/runtime.ts#L915">runtime.ts:915</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L915">runtime.ts:915</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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@@ -68,7 +68,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -83,7 +83,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -101,7 +101,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></h4><p>The result function.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -111,7 +111,7 @@ only the first call will take effect.</p>
 </div>
 <h4 class="tsd-returns-title">Returns <a href="Module.html" class="tsd-signature-type tsd-kind-class">Module</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L950">runtime.ts:950</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
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diff --git a/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html b/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
index 36d8caf4ce..8bcdd74181 100644
--- a/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
+++ b/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
@@ -36,7 +36,7 @@ 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/5092c003d/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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">
@@ -86,7 +86,7 @@ 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/5092c003d/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/ff9ebadf6/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>
@@ -95,7 +95,7 @@ can still call into storeXX</li>
 <div class="tsd-comment tsd-typography"><p>List of temporay arguments that can be disposed during reset.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -115,7 +115,7 @@ can still call into storeXX</li>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><p>The allocated pointer array.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -134,7 +134,7 @@ can still call into storeXX</li>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -156,7 +156,7 @@ Allocate new temporary space for bytes.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -180,7 +180,7 @@ and will be filled when we commit the data.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -199,7 +199,7 @@ No further store function should be called.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -212,7 +212,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -230,7 +230,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -240,7 +240,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
 </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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -255,7 +255,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -270,7 +270,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -285,7 +285,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -300,7 +300,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -315,7 +315,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -330,7 +330,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -345,7 +345,7 @@ 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/5092c003d/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/ff9ebadf6/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 3265dd3aa5..83228e3160 100644
--- a/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
+++ b/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
@@ -29,7 +29,7 @@ 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/5092c003d/web/src/webgpu.ts#L158">webgpu.ts:158</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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">
@@ -61,7 +61,7 @@ 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/5092c003d/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/ff9ebadf6/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>
@@ -71,7 +71,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -84,7 +84,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -101,7 +101,7 @@ 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/5092c003d/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/ff9ebadf6/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 63686e5c9b..1e8969fb6f 100644
--- a/docs/reference/api/typedoc/classes/_internal_.Environment.html
+++ b/docs/reference/api/typedoc/classes/_internal_.Environment.html
@@ -28,7 +28,7 @@
 <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/5092c003d/web/src/environment.ts#L68">environment.ts:68</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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">
@@ -76,7 +76,7 @@
 <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/5092c003d/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/ff9ebadf6/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>
@@ -86,7 +86,7 @@
 </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/5092c003d/web/src/environment.ts#L70">environment.ts:70</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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"> =&gt; </span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">)</span></div>
@@ -104,7 +104,7 @@
 <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/5092c003d/web/src/environment.ts#L69">environment.ts:69</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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>
@@ -114,14 +114,14 @@ can call via TVMWasmPackedCFunc.</p>
 of functions that do not maps to the address space.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/environment.ts#L78">environment.ts:78</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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>
 <div class="tsd-comment tsd-typography"><p>Free table index that can be recycled.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -139,7 +139,7 @@ of functions that do not maps to the address space.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/web/src/environment.ts#L105">environment.ts:105</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_.FFILibrary.html b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
index 971bf223b4..cc1da1836e 100644
--- a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
+++ b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
@@ -28,7 +28,7 @@
 <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/5092c003d/web/src/runtime.ts#L43">runtime.ts:43</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L43">runtime.ts:43</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">
@@ -69,29 +69,29 @@
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 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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">&lt;</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">&gt;</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L46">runtime.ts:46</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/web/src/runtime.ts#L45">runtime.ts:45</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/web/src/runtime.ts#L44">runtime.ts:44</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/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/ff9ebadf6/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>
@@ -106,7 +106,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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 <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -127,7 +127,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -140,7 +140,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -148,7 +148,7 @@ 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/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L73">runtime.ts:73</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_.Memory.html b/docs/reference/api/typedoc/classes/_internal_.Memory.html
index fc3bf6d55a..e15d314e63 100644
--- a/docs/reference/api/typedoc/classes/_internal_.Memory.html
+++ b/docs/reference/api/typedoc/classes/_internal_.Memory.html
@@ -24,7 +24,7 @@
 <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/5092c003d/web/src/memory.ts#L31">memory.ts:31</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/memory.ts#L31">memory.ts:31</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 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/web/src/memory.ts#L32">memory.ts:32</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
@@ -101,7 +101,7 @@
 </div></li></ul></div>
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -114,7 +114,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -127,7 +127,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -140,7 +140,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -153,7 +153,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -166,7 +166,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -187,7 +187,7 @@
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Uint8Array</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -204,7 +204,7 @@
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Uint8Array</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -217,7 +217,7 @@
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 <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/5092c003d/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/ff9ebadf6/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>
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 <ul class="tsd-signatures">
@@ -230,7 +230,7 @@
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 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -243,7 +243,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -256,7 +256,7 @@
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -264,7 +264,7 @@
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 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -285,7 +285,7 @@
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 <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/5092c003d/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/ff9ebadf6/web/src/memory.ts#L175">memory.ts:175</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_.PackedFuncCell.html b/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html
index 100eee9906..3fd47b2326 100644
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+++ b/docs/reference/api/typedoc/classes/_internal_.PackedFuncCell.html
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 <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/5092c003d/web/src/runtime.ts#L291">runtime.ts:291</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L291">runtime.ts:291</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">
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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/5092c003d/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/ff9ebadf6/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>
@@ -74,7 +74,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -87,7 +87,7 @@ 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/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L309">runtime.ts:309</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_.RuntimeContext.html b/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html
index 8b6a8b0a60..3853a72591 100644
--- a/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html
+++ b/docs/reference/api/typedoc/classes/_internal_.RuntimeContext.html
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L165">runtime.ts:165</a></li></ul></aside></li></ul></section></section>
 <section class="tsd-panel-group tsd-member-group">
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 <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/5092c003d/web/src/runtime.ts#L160">runtime.ts:160</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L161">runtime.ts:161</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L161">runtime.ts:161</a></li></ul></aside></section>
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 <h3 class="tsd-anchor-link"><span>array<wbr/>Cache<wbr/>Clear</span><a href="#arrayCacheClear" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L153">runtime.ts:153</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/web/src/runtime.ts#L150">runtime.ts:150</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L152">runtime.ts:152</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L151">runtime.ts:151</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L151">runtime.ts:151</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L154">runtime.ts:154</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L154">runtime.ts:154</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L144">runtime.ts:144</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L144">runtime.ts:144</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L145">runtime.ts:145</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L146">runtime.ts:146</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L146">runtime.ts:146</a></li></ul></aside></section>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L148">runtime.ts:148</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L148">runtime.ts:148</a></li></ul></aside></section>
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 <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/5092c003d/web/src/runtime.ts#L149">runtime.ts:149</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L149">runtime.ts:149</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L157">runtime.ts:157</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L157">runtime.ts:157</a></li></ul></aside></section>
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 <h3 class="tsd-anchor-link"><span>ndarray<wbr/>Create<wbr/>View</span><a href="#ndarrayCreateView" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L158">runtime.ts:158</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L158">runtime.ts:158</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L155">runtime.ts:155</a></li></ul></aside></section>
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 <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">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L156">runtime.ts:156</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L156">runtime.ts:156</a></li></ul></aside></section>
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 <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">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
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 <h3 class="tsd-anchor-link"><span>string<wbr/>Make</span><a href="#stringMake" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L147">runtime.ts:147</a></li></ul></aside></section></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L234">runtime.ts:234</a></li></ul></aside></li></ul></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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>
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@@ -239,7 +239,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -252,7 +252,7 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -260,7 +260,7 @@ only the first call will take effect.</p>
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 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -278,7 +278,7 @@ 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/5092c003d/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/ff9ebadf6/web/src/runtime.ts#L243">runtime.ts:243</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/_internal_.TVMString.html b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
index 97fc3e42a3..6490ffa9d6 100644
--- a/docs/reference/api/typedoc/classes/_internal_.TVMString.html
+++ b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
@@ -26,7 +26,7 @@
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 <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/5092c003d/web/src/runtime.ts#L886">runtime.ts:886</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L886">runtime.ts:886</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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@@ -63,7 +63,7 @@
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 <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/5092c003d/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/ff9ebadf6/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>
@@ -78,7 +78,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-is-inherited">
@@ -97,7 +97,7 @@ only the first call will take effect.</p>
 <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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -107,7 +107,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><p>the size of the array.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-is-inherited">
@@ -118,7 +118,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-is-inherited">
@@ -129,7 +129,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><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/5092c003d/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/ff9ebadf6/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 06b48def2e..ba22631c48 100644
--- a/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
+++ b/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
@@ -25,7 +25,7 @@ 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/5092c003d/web/src/webgpu.ts#L335">webgpu.ts:335</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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">
@@ -69,19 +69,19 @@ 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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/web/src/webgpu.ts#L336">webgpu.ts:336</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></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/5092c003d/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/ff9ebadf6/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>
@@ -100,7 +100,7 @@ Manages all the webgpu resources here.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -110,7 +110,7 @@ Manages all the webgpu resources here.</p>
 </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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -139,7 +139,7 @@ Manages all the webgpu resources here.</p>
 </div></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/5092c003d/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/ff9ebadf6/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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -160,7 +160,7 @@ via createComputePipeline</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Function</span></h4><p>The shader</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/webgpu.ts#L456">webgpu.ts:456</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L456">webgpu.ts:456</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="createShaderAsync" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>create<wbr/>Shader<wbr/>Async</span><a href="#createShaderAsync" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -181,7 +181,7 @@ via createComputePipelineAsync</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type ">Function</span><span class="tsd-signature-symbol">&gt;</span></h4><p>The shader</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/webgpu.ts#L468">webgpu.ts:468</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L468">webgpu.ts:468</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 class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -191,7 +191,7 @@ via createComputePipelineAsync</p>
 </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/5092c003d/web/src/webgpu.ts#L368">webgpu.ts:368</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L368">webgpu.ts:368</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="drawImageFromBuffer" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L403">webgpu.ts:403</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L724">webgpu.ts:724</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L390">webgpu.ts:390</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L383">webgpu.ts:383</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L30">rpc_server.ts:30</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L33">rpc_server.ts:33</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L32">rpc_server.ts:32</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/rpc_server.ts#L31">rpc_server.ts:31</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/support.ts#L52">support.ts:52</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/compact.ts#L55">compact.ts:55</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/webgpu.ts#L36">webgpu.ts:36</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/web/src/runtime.ts#L2403">runtime.ts:2403</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/support.ts#L62">support.ts:62</a></li></ul></aside></li></ul></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/types.ts#L46">types.ts:46</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/web/src/runtime.ts#L977">runtime.ts:977</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L980">runtime.ts:980</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/5092c003d/web/src/runtime.ts#L978">runtime.ts:978</a></li></ul></aside></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/runtime.ts#L978">runtime.ts:978</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/web/src/types.ts#L34">types.ts:34</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/web/src/webgpu.ts#L326">webgpu.ts:326</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/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/ff9ebadf6/web/src/runtime.ts#L962">runtime.ts:962</a></li></ul></aside></section></section></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 0962d025ca..147fa22205 100644
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-<p><strong>00:35.290</strong> total execution time for <strong>topic_vta_tutorials_autotvm</strong> files:</p>
+<p><strong>00:35.440</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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index 104d0e29d9..22f28dd329 100644
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-resnet18_v1 inference graph built in 37.56s!
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diff --git a/docs/topic/vta/tutorials/frontend/deploy_detection.html b/docs/topic/vta/tutorials/frontend/deploy_detection.html
index 8fa22cc88d..d653c73ef9 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_detection.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_detection.html
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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)
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-yolov3-tiny inference graph built in 25.39s!
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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 dcd763793d..965a850136 100644
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@@ -360,7 +360,7 @@
             
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-<p><strong>01:56.070</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
+<p><strong>01:59.329</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
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index 54dc31c995..d1d3cb7278 100644
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@@ -360,7 +360,7 @@
             
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-<p><strong>00:03.238</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
+<p><strong>00:03.301</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
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 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="vta_get_started.html#sphx-glr-topic-vta-tutorials-vta-get-started-py"><span class="std std-ref">Get Started with VTA</span></a> (<code class="docutils literal notranslate"><span class="pre">vta_get_started.py</span></code>)</p></td>
-<td><p>00:00.391</p></td>
+<td><p>00:00.392</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/tutorial/auto_scheduler_matmul_x86.html b/docs/tutorial/auto_scheduler_matmul_x86.html
index 2a691a6748..05dfd092b8 100644
--- a/docs/tutorial/auto_scheduler_matmul_x86.html
+++ b/docs/tutorial/auto_scheduler_matmul_x86.html
@@ -512,9 +512,6 @@ trials, we can load the best schedule from the log file and apply it.</p>
 <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">sch</span></a><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">args</span></a> <span class="o">=</span> <a href="../reference/api/pyth [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>*E
-</pre></div>
-</div>
 </div>
 <div class="section" id="inspecting-the-optimized-schedule">
 <h2>Inspecting the Optimized Schedule<a class="headerlink" href="#inspecting-the-optimized-schedule" title="Permalink to this headline">¶</a></h2>
@@ -592,7 +589,7 @@ 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: 94.321 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 92.121 ms
 </pre></div>
 </div>
 </div>
@@ -654,6 +651,7 @@ resume the status and do more 5 trials.</p>
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Resume search:
+.T
 </pre></div>
 </div>
 </div>
@@ -664,7 +662,7 @@ automatically optimize a matrix multiplication, without the need to specify a
 search template.  It ends a series of examples that starts from the Tensor
 Expression (TE) language that demonstrates how TVM can optimize computational
 operations.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  33.025 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  29.500 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 1171fc89e2..eb7f766c7e 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: 2.17/2.17       result: MeasureResult(costs=(0.1238816818,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.230107069015503, timestamp=1706571339.625364) [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 1])],None,2
-No: 2   GFLOPS: 7.92/7.92       result: MeasureResult(costs=(0.0339051936,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8027594089508057, timestamp=1706571340.4259365)       [(&#39;tile_y&#39;, [-1, 512]), (&#39;tile_x&#39;, [-1, 16])],None,49
-No: 3   GFLOPS: 2.17/7.92       result: MeasureResult(costs=(0.1236930316,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.2226710319519043, timestamp=1706571342.6601648)       [(&#39;tile_y&#39;, [-1, 32]), (&#39;tile_x&#39;, [-1, 4])],None,25
-No: 4   GFLOPS: 11.61/11.61     result: MeasureResult(costs=(0.0231276226,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6599793434143066, timestamp=1706571343.29226) [(&#39;tile_y&#39;, [-1, 128]), (&#39;tile_x&#39;, [-1, 256])],None,87
-No: 5   GFLOPS: 2.09/11.61      result: MeasureResult(costs=(0.1287003534,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3154706954956055, timestamp=1706571345.760802)        [(&#39;tile_y&#39;, [-1, 64]), (&#39;tile_x&#39;, [-1, 4])],None,26
-No: 6   GFLOPS: 13.35/13.35     result: MeasureResult(costs=(0.020101387,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6268157958984375, timestamp=1706571346.3466408)        [(&#39;tile_y&#39;, [-1, 128]), (&#39;tile_x&#39;, [-1, 128])],None,77
-No: 7   GFLOPS: 3.00/13.35      result: MeasureResult(costs=(0.0896176782,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6861565113067627, timestamp=1706571348.037459)        [(&#39;tile_y&#39;, [-1, 16]), (&#39;tile_x&#39;, [-1, 2])],None,14
-No: 8   GFLOPS: 1.50/13.35      result: MeasureResult(costs=(0.1787965154,), error_no=MeasureErrorNo.NO_ERROR, all_cost=3.0967469215393066, timestamp=1706571351.1551347)       [(&#39;tile_y&#39;, [-1, 1]), (&#39;tile_x&#39;, [-1, 1])],None,0
-No: 9   GFLOPS: 11.80/13.35     result: MeasureResult(costs=(0.022750107600000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.584221601486206, timestamp=1706571351.849052) [(&#39;tile_y&#39;, [-1, 128]), (&#39;tile_x&#39;, [-1, 512])],None,97
-No: 10  GFLOPS: 11.49/13.35     result: MeasureResult(costs=(0.0233557672,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6027917861938477, timestamp=1706571352.4954147)       [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 512])],None,98
+No: 1   GFLOPS: 9.49/9.49       result: MeasureResult(costs=(0.028277249999999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8736984729766846, timestamp=1706583503.4926963)       [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 128])],None,73
+No: 2   GFLOPS: 9.61/9.61       result: MeasureResult(costs=(0.0279214988,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8893542289733887, timestamp=1706583504.203972)        [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 128])],None,71
+No: 3   GFLOPS: 7.58/9.61       result: MeasureResult(costs=(0.035415316999999995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.82696533203125, timestamp=1706583505.0347772) [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 4])],None,21
+No: 4   GFLOPS: 14.09/14.09     result: MeasureResult(costs=(0.0190562692,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6014492511749268, timestamp=1706583505.597567)        [(&#39;tile_y&#39;, [-1, 128]), (&#39;tile_x&#39;, [-1, 64])],None,67
+No: 5   GFLOPS: 11.76/14.09     result: MeasureResult(costs=(0.0228304454,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6438071727752686, timestamp=1706583506.4033966)       [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 256])],None,82
+No: 6   GFLOPS: 9.11/14.09      result: MeasureResult(costs=(0.029456308200000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7988314628601074, timestamp=1706583507.1352098)       [(&#39;tile_y&#39;, [-1, 512]), (&#39;tile_x&#39;, [-1, 64])],None,69
+No: 7   GFLOPS: 10.24/14.09     result: MeasureResult(costs=(0.026208645799999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6654329299926758, timestamp=1706583507.818901)        [(&#39;tile_y&#39;, [-1, 512]), (&#39;tile_x&#39;, [-1, 512])],None,99
+No: 8   GFLOPS: 11.19/14.09     result: MeasureResult(costs=(0.0239912734,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.696274995803833, timestamp=1706583508.4603906)        [(&#39;tile_y&#39;, [-1, 1]), (&#39;tile_x&#39;, [-1, 64])],None,60
+No: 9   GFLOPS: 9.20/14.09      result: MeasureResult(costs=(0.029177793400000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6892180442810059, timestamp=1706583509.2608345)       [(&#39;tile_y&#39;, [-1, 512]), (&#39;tile_x&#39;, [-1, 256])],None,89
+No: 10  GFLOPS: 2.06/14.09      result: MeasureResult(costs=(0.1303867132,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.308297872543335, timestamp=1706583511.6073163)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 4])],None,28
 </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 a9ab9d0a73..695bfb5745 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>{&#39;mean&#39;: 472.78118281999923, &#39;median&#39;: 472.4927659500054, &#39;std&#39;: 1.7815587371850354}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;mean&#39;: 488.96065589000045, &#39;median&#39;: 489.13092864997907, &#39;std&#39;: 2.8590050185786398}
 </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:    9.41/  24.05 GFLOPS | Progress: (4/20) | 7.08 s
-[Task  1/25]  Current/Best:    7.80/  24.05 GFLOPS | Progress: (8/20) | 9.90 s
-[Task  1/25]  Current/Best:    6.75/  24.05 GFLOPS | Progress: (12/20) | 13.12 s
-[Task  1/25]  Current/Best:   12.15/  24.05 GFLOPS | Progress: (16/20) | 15.78 s
-[Task  1/25]  Current/Best:    3.43/  24.05 GFLOPS | Progress: (20/20) | 18.48 s Done.
+[Task  1/25]  Current/Best:   11.97/  20.90 GFLOPS | Progress: (4/20) | 10.33 s
+[Task  1/25]  Current/Best:    8.73/  20.90 GFLOPS | Progress: (8/20) | 12.86 s
+[Task  1/25]  Current/Best:    7.55/  20.90 GFLOPS | Progress: (12/20) | 15.16 s
+[Task  1/25]  Current/Best:   17.20/  20.90 GFLOPS | Progress: (16/20) | 18.04 s
+[Task  1/25]  Current/Best:   11.02/  20.90 GFLOPS | Progress: (20/20) | 21.62 s Done.
 
 [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  2/25]  Current/Best:   14.20/  22.23 GFLOPS | Progress: (4/20) | 3.85 s
-[Task  2/25]  Current/Best:   15.66/  22.23 GFLOPS | Progress: (8/20) | 5.21 s
-[Task  2/25]  Current/Best:   14.15/  22.23 GFLOPS | Progress: (12/20) | 6.63 s
-[Task  2/25]  Current/Best:   12.37/  22.23 GFLOPS | Progress: (16/20) | 9.14 s
-[Task  2/25]  Current/Best:   17.64/  22.23 GFLOPS | Progress: (20/20) | 10.72 s Done.
+[Task  2/25]  Current/Best:   13.62/  13.62 GFLOPS | Progress: (4/20) | 4.08 s
+[Task  2/25]  Current/Best:    7.51/  13.62 GFLOPS | Progress: (8/20) | 5.88 s
+[Task  2/25]  Current/Best:    6.59/  20.45 GFLOPS | Progress: (12/20) | 7.26 s
+[Task  2/25]  Current/Best:    9.07/  20.45 GFLOPS | Progress: (16/20) | 10.04 s
+[Task  2/25]  Current/Best:   12.25/  20.45 GFLOPS | Progress: (20/20) | 12.65 s Done.
 
 [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  3/25]  Current/Best:   10.57/  20.81 GFLOPS | Progress: (4/20) | 5.61 s
-[Task  3/25]  Current/Best:   24.49/  24.49 GFLOPS | Progress: (8/20) | 7.69 s
-[Task  3/25]  Current/Best:    5.44/  24.49 GFLOPS | Progress: (12/20) | 10.44 s
-[Task  3/25]  Current/Best:   10.80/  24.49 GFLOPS | Progress: (16/20) | 12.88 s
-[Task  3/25]  Current/Best:   14.27/  24.49 GFLOPS | Progress: (20/20) | 15.69 s Done.
+[Task  3/25]  Current/Best:   19.34/  22.77 GFLOPS | Progress: (4/20) | 5.01 s
+[Task  3/25]  Current/Best:   24.34/  24.34 GFLOPS | Progress: (8/20) | 6.96 s
+[Task  3/25]  Current/Best:   13.34/  24.34 GFLOPS | Progress: (12/20) | 9.22 s
+[Task  3/25]  Current/Best:   12.57/  24.34 GFLOPS | Progress: (16/20) | 12.00 s
+[Task  3/25]  Current/Best:   19.77/  24.34 GFLOPS | Progress: (20/20) | 14.70 s Done.
 
 [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  4/25]  Current/Best:   12.31/  17.40 GFLOPS | Progress: (4/20) | 4.92 s
-[Task  4/25]  Current/Best:   13.07/  18.37 GFLOPS | Progress: (8/20) | 7.20 s
-[Task  4/25]  Current/Best:   13.00/  20.36 GFLOPS | Progress: (12/20) | 8.78 s
-[Task  4/25]  Current/Best:   10.33/  20.36 GFLOPS | Progress: (16/20) | 11.96 s
-[Task  4/25]  Current/Best:   19.09/  20.36 GFLOPS | Progress: (20/20) | 16.11 s Done.
+[Task  4/25]  Current/Best:   11.06/  15.91 GFLOPS | Progress: (4/20) | 4.32 s
+[Task  4/25]  Current/Best:    7.50/  16.24 GFLOPS | Progress: (8/20) | 6.90 s
+[Task  4/25]  Current/Best:   20.21/  20.21 GFLOPS | Progress: (12/20) | 8.90 s
+[Task  4/25]  Current/Best:   10.42/  20.21 GFLOPS | Progress: (16/20) | 13.51 s
+[Task  4/25]  Current/Best:   11.16/  21.85 GFLOPS | Progress: (20/20) | 21.28 s Done.
 
 [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  5/25]  Current/Best:    5.54/  20.53 GFLOPS | Progress: (4/20) | 4.38 s
-[Task  5/25]  Current/Best:    8.31/  20.53 GFLOPS | Progress: (8/20) | 6.31 s
-[Task  5/25]  Current/Best:   11.58/  20.53 GFLOPS | Progress: (12/20) | 8.24 s
-[Task  5/25]  Current/Best:   17.85/  20.53 GFLOPS | Progress: (16/20) | 10.67 s
-[Task  5/25]  Current/Best:   14.35/  20.53 GFLOPS | Progress: (20/20) | 12.71 s Done.
+[Task  5/25]  Current/Best:   14.94/  16.75 GFLOPS | Progress: (4/20) | 4.53 s
+[Task  5/25]  Current/Best:   19.22/  19.22 GFLOPS | Progress: (8/20) | 6.53 s
+[Task  5/25]  Current/Best:   14.33/  19.22 GFLOPS | Progress: (12/20) | 8.53 s
+[Task  5/25]  Current/Best:   14.36/  19.22 GFLOPS | Progress: (16/20) | 10.65 s
+[Task  5/25]  Current/Best:   16.57/  19.22 GFLOPS | Progress: (20/20) | 12.94 s Done.
 
 [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  6/25]  Current/Best:   11.51/  23.74 GFLOPS | Progress: (4/20) | 5.96 s
-[Task  6/25]  Current/Best:   14.68/  23.74 GFLOPS | Progress: (8/20) | 9.01 s
-[Task  6/25]  Current/Best:   15.76/  23.74 GFLOPS | Progress: (12/20) | 11.49 s
-[Task  6/25]  Current/Best:    5.85/  23.74 GFLOPS | Progress: (16/20) | 14.02 s
-[Task  6/25]  Current/Best:   15.00/  23.74 GFLOPS | Progress: (20/20) | 17.00 s Done.
+[Task  6/25]  Current/Best:   17.13/  17.13 GFLOPS | Progress: (4/20) | 5.45 s
+[Task  6/25]  Current/Best:    6.82/  17.47 GFLOPS | Progress: (8/20) | 7.71 s
+[Task  6/25]  Current/Best:   14.40/  17.47 GFLOPS | Progress: (12/20) | 10.38 s
+[Task  6/25]  Current/Best:   11.57/  17.92 GFLOPS | Progress: (16/20) | 12.49 s
+[Task  6/25]  Current/Best:    4.11/  17.92 GFLOPS | Progress: (20/20) | 17.49 s Done.
 
 [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  7/25]  Current/Best:    9.28/  13.36 GFLOPS | Progress: (4/20) | 5.10 s
-[Task  7/25]  Current/Best:   13.00/  18.10 GFLOPS | Progress: (8/20) | 7.62 s
-[Task  7/25]  Current/Best:   20.16/  20.53 GFLOPS | Progress: (12/20) | 9.71 s
-[Task  7/25]  Current/Best:   16.35/  20.53 GFLOPS | Progress: (16/20) | 12.53 s
-[Task  7/25]  Current/Best:   19.57/  23.51 GFLOPS | Progress: (20/20) | 14.67 s Done.
+[Task  7/25]  Current/Best:   13.00/  19.15 GFLOPS | Progress: (4/20) | 4.86 s
+[Task  7/25]  Current/Best:   17.98/  19.99 GFLOPS | Progress: (8/20) | 6.76 s
+[Task  7/25]  Current/Best:   12.03/  20.00 GFLOPS | Progress: (12/20) | 9.52 s
+[Task  7/25]  Current/Best:   14.03/  20.00 GFLOPS | Progress: (16/20) | 11.71 s
+[Task  7/25]  Current/Best:   12.42/  21.50 GFLOPS | Progress: (20/20) | 14.50 s Done.
 
 [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  8/25]  Current/Best:    8.17/  16.66 GFLOPS | Progress: (4/20) | 5.07 s
-[Task  8/25]  Current/Best:   12.54/  16.66 GFLOPS | Progress: (8/20) | 7.42 s
-[Task  8/25]  Current/Best:    7.84/  16.66 GFLOPS | Progress: (12/20) | 13.39 s
-[Task  8/25]  Current/Best:   16.38/  16.66 GFLOPS | Progress: (16/20) | 18.11 s
-[Task  8/25]  Current/Best:   12.42/  16.66 GFLOPS | Progress: (20/20) | 23.07 s Done.
+[Task  8/25]  Current/Best:   11.73/  23.00 GFLOPS | Progress: (4/20) | 6.35 s
+[Task  8/25]  Current/Best:    2.87/  23.00 GFLOPS | Progress: (8/20) | 11.29 s
+[Task  8/25]  Current/Best:   12.01/  23.00 GFLOPS | Progress: (12/20) | 14.63 s
+[Task  8/25]  Current/Best:   14.75/  23.00 GFLOPS | Progress: (16/20) | 16.87 s
+[Task  8/25]  Current/Best:    2.84/  23.00 GFLOPS | Progress: (20/20) | 19.82 s Done.
 
 [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  9/25]  Current/Best:   22.31/  22.31 GFLOPS | Progress: (4/20) | 4.29 s
-[Task  9/25]  Current/Best:   17.14/  22.31 GFLOPS | Progress: (8/20) | 8.07 s
-[Task  9/25]  Current/Best:   13.72/  22.31 GFLOPS | Progress: (12/20) | 15.38 s
-[Task  9/25]  Current/Best:   11.18/  22.31 GFLOPS | Progress: (16/20) | 21.34 s
-[Task  9/25]  Current/Best:   11.39/  22.31 GFLOPS | Progress: (20/20) | 26.29 s Done.
+[Task  9/25]  Current/Best:   18.52/  18.52 GFLOPS | Progress: (4/20) | 9.99 s
+[Task  9/25]  Current/Best:   15.33/  18.52 GFLOPS | Progress: (8/20) | 11.84 s
+[Task  9/25]  Current/Best:   21.29/  21.29 GFLOPS | Progress: (12/20) | 13.98 s
+[Task  9/25]  Current/Best:   14.31/  21.29 GFLOPS | Progress: (16/20) | 15.70 s
+[Task  9/25]  Current/Best:   15.55/  21.29 GFLOPS | Progress: (20/20) | 19.62 s Done.
 
 [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 10/25]  Current/Best:   12.67/  19.11 GFLOPS | Progress: (4/20) | 5.52 s
-[Task 10/25]  Current/Best:   19.03/  19.11 GFLOPS | Progress: (8/20) | 9.46 s
-[Task 10/25]  Current/Best:   20.57/  20.57 GFLOPS | Progress: (12/20) | 11.61 s
-[Task 10/25]  Current/Best:    6.26/  20.57 GFLOPS | Progress: (16/20) | 13.67 s
-[Task 10/25]  Current/Best:   11.15/  21.29 GFLOPS | Progress: (20/20) | 16.61 s Done.
+[Task 10/25]  Current/Best:   14.56/  16.98 GFLOPS | Progress: (4/20) | 4.68 s
+[Task 10/25]  Current/Best:   17.96/  18.97 GFLOPS | Progress: (8/20) | 6.32 s
+[Task 10/25]  Current/Best:   19.52/  19.52 GFLOPS | Progress: (12/20) | 8.24 s
+[Task 10/25]  Current/Best:   12.86/  19.52 GFLOPS | Progress: (16/20) | 10.29 s
+[Task 10/25]  Current/Best:   16.13/  19.52 GFLOPS | Progress: (20/20) | 11.99 s Done.
 
 [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 11/25]  Current/Best:   20.36/  20.36 GFLOPS | Progress: (4/20) | 4.45 s
-[Task 11/25]  Current/Best:   10.94/  22.90 GFLOPS | Progress: (8/20) | 6.71 s
-[Task 11/25]  Current/Best:    7.54/  22.90 GFLOPS | Progress: (12/20) | 9.29 s
-[Task 11/25]  Current/Best:   20.55/  24.10 GFLOPS | Progress: (16/20) | 11.58 s
-[Task 11/25]  Current/Best:   15.64/  24.10 GFLOPS | Progress: (20/20) | 13.92 s Done.
+[Task 11/25]  Current/Best:   12.21/  23.96 GFLOPS | Progress: (4/20) | 4.52 s
+[Task 11/25]  Current/Best:    6.89/  23.96 GFLOPS | Progress: (8/20) | 8.44 s
+[Task 11/25]  Current/Best:   22.15/  23.96 GFLOPS | Progress: (12/20) | 10.40 s
+[Task 11/25]  Current/Best:   19.35/  23.96 GFLOPS | Progress: (16/20) | 12.69 s
+[Task 11/25]  Current/Best:   13.07/  23.96 GFLOPS | Progress: (20/20) | 16.40 s Done.
 
 [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 12/25]  Current/Best:   12.33/  15.12 GFLOPS | Progress: (4/20) | 4.43 s
-[Task 12/25]  Current/Best:    9.00/  15.94 GFLOPS | Progress: (8/20) | 8.37 s
-[Task 12/25]  Current/Best:    9.49/  15.94 GFLOPS | Progress: (12/20) | 14.16 s
-[Task 12/25]  Current/Best:   17.99/  20.76 GFLOPS | Progress: (16/20) | 20.46 s
-[Task 12/25]  Current/Best:   19.57/  20.76 GFLOPS | Progress: (20/20) | 23.31 s Done.
+[Task 12/25]  Current/Best:   21.71/  23.86 GFLOPS | Progress: (4/20) | 4.25 s
+[Task 12/25]  Current/Best:   18.83/  23.86 GFLOPS | Progress: (8/20) | 7.68 s
+[Task 12/25]  Current/Best:   16.70/  23.86 GFLOPS | Progress: (12/20) | 9.90 s
+[Task 12/25]  Current/Best:    3.83/  23.86 GFLOPS | Progress: (16/20) | 13.12 s
+[Task 12/25]  Current/Best:   14.11/  23.86 GFLOPS | Progress: (20/20) | 15.24 s Done.
 
 [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 13/25]  Current/Best:    1.62/  19.58 GFLOPS | Progress: (4/20) | 6.02 s
-[Task 13/25]  Current/Best:   11.07/  19.58 GFLOPS | Progress: (8/20) | 8.70 s
-[Task 13/25]  Current/Best:   10.19/  21.24 GFLOPS | Progress: (12/20) | 12.42 s
-[Task 13/25]  Current/Best:    3.18/  21.24 GFLOPS | Progress: (16/20) | 16.18 s
-[Task 13/25]  Current/Best:   22.19/  22.19 GFLOPS | Progress: (20/20) | 19.01 s Done.
+[Task 13/25]  Current/Best:   17.07/  19.07 GFLOPS | Progress: (4/20) | 4.65 s
+[Task 13/25]  Current/Best:   11.81/  19.07 GFLOPS | Progress: (8/20) | 8.47 s
+[Task 13/25]  Current/Best:   19.27/  19.27 GFLOPS | Progress: (12/20) | 11.05 s
+[Task 13/25]  Current/Best:    9.94/  19.66 GFLOPS | Progress: (16/20) | 13.29 s
+[Task 13/25]  Current/Best:   19.26/  19.66 GFLOPS | Progress: (20/20) | 16.11 s Done.
 
 [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 14/25]  Current/Best:    7.39/  14.16 GFLOPS | Progress: (4/20) | 5.20 s
-[Task 14/25]  Current/Best:    9.95/  17.39 GFLOPS | Progress: (8/20) | 7.40 s
-[Task 14/25]  Current/Best:    6.97/  17.39 GFLOPS | Progress: (12/20) | 16.01 s
-[Task 14/25]  Current/Best:    5.70/  17.39 GFLOPS | Progress: (16/20) | 28.51 s
-[Task 14/25]  Current/Best:   11.15/  17.39 GFLOPS | Progress: (20/20) | 39.02 s Done.
+[Task 14/25]  Current/Best:   10.38/  14.50 GFLOPS | Progress: (4/20) | 6.65 s
+[Task 14/25]  Current/Best:   15.77/  18.66 GFLOPS | Progress: (8/20) | 11.46 s
+[Task 14/25]  Current/Best:   11.14/  18.67 GFLOPS | Progress: (12/20) | 13.91 s
+[Task 14/25]  Current/Best:   17.32/  18.67 GFLOPS | Progress: (16/20) | 16.98 s
+[Task 14/25]  Current/Best:    6.60/  18.67 GFLOPS | Progress: (20/20) | 27.89 s Done.
 
 [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 15/25]  Current/Best:   18.78/  20.92 GFLOPS | Progress: (4/20) | 8.32 s
-[Task 15/25]  Current/Best:    8.70/  20.92 GFLOPS | Progress: (8/20) | 17.07 s
-[Task 15/25]  Current/Best:    7.55/  20.92 GFLOPS | Progress: (12/20) | 18.67 s
-[Task 15/25]  Current/Best:   17.16/  20.92 GFLOPS | Progress: (16/20) | 20.33 s
-[Task 15/25]  Current/Best:   19.26/  20.92 GFLOPS | Progress: (20/20) | 26.97 s Done.
+[Task 15/25]  Current/Best:   14.31/  14.31 GFLOPS | Progress: (4/20) | 4.66 s
+[Task 15/25]  Current/Best:   21.11/  21.11 GFLOPS | Progress: (8/20) | 11.85 s
+[Task 15/25]  Current/Best:    3.19/  21.11 GFLOPS | Progress: (12/20) | 22.42 s
+[Task 15/25]  Current/Best:   12.34/  21.11 GFLOPS | Progress: (16/20) | 26.79 s
+[Task 15/25]  Current/Best:    7.87/  21.11 GFLOPS | Progress: (20/20) | 33.54 s Done.
 
 [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 16/25]  Current/Best:   16.64/  16.64 GFLOPS | Progress: (4/20) | 4.79 s
-[Task 16/25]  Current/Best:   19.98/  19.98 GFLOPS | Progress: (8/20) | 7.57 s
-[Task 16/25]  Current/Best:   13.40/  19.98 GFLOPS | Progress: (12/20) | 9.83 s
-[Task 16/25]  Current/Best:    3.99/  19.98 GFLOPS | Progress: (16/20) | 12.14 s
-[Task 16/25]  Current/Best:   20.30/  20.30 GFLOPS | Progress: (20/20) | 13.98 s Done.
+[Task 16/25]  Current/Best:    9.54/  19.72 GFLOPS | Progress: (4/20) | 4.47 s
+[Task 16/25]  Current/Best:    7.25/  19.72 GFLOPS | Progress: (8/20) | 6.52 s
+[Task 16/25]  Current/Best:    6.68/  19.72 GFLOPS | Progress: (12/20) | 8.61 s
+[Task 16/25]  Current/Best:   18.93/  19.72 GFLOPS | Progress: (16/20) | 10.54 s
+[Task 16/25]  Current/Best:    8.03/  19.72 GFLOPS | Progress: (20/20) | 12.29 s Done.
 
 [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 17/25]  Current/Best:   12.03/  19.70 GFLOPS | Progress: (4/20) | 4.50 s
-[Task 17/25]  Current/Best:   21.41/  22.35 GFLOPS | Progress: (8/20) | 6.39 s
-[Task 17/25]  Current/Best:   21.42/  22.35 GFLOPS | Progress: (12/20) | 8.65 s
-[Task 17/25]  Current/Best:   15.67/  22.35 GFLOPS | Progress: (16/20) | 11.23 s
-[Task 17/25]  Current/Best:   19.67/  24.13 GFLOPS | Progress: (20/20) | 13.54 s Done.
+[Task 17/25]  Current/Best:   18.04/  18.04 GFLOPS | Progress: (4/20) | 6.20 s
+[Task 17/25]  Current/Best:   19.45/  19.45 GFLOPS | Progress: (8/20) | 8.48 s
+[Task 17/25]  Current/Best:    6.98/  21.61 GFLOPS | Progress: (12/20) | 11.64 s
+[Task 17/25]  Current/Best:    6.06/  22.68 GFLOPS | Progress: (16/20) | 14.39 s
+[Task 17/25]  Current/Best:   20.80/  22.68 GFLOPS | Progress: (20/20) | 17.31 s Done.
 
 [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 18/25]  Current/Best:   18.98/  18.98 GFLOPS | Progress: (4/20) | 4.47 s
-[Task 18/25]  Current/Best:    6.43/  18.98 GFLOPS | Progress: (8/20) | 8.27 s
-[Task 18/25]  Current/Best:   15.06/  18.98 GFLOPS | Progress: (12/20) | 10.56 s
-[Task 18/25]  Current/Best:   14.08/  18.98 GFLOPS | Progress: (16/20) | 13.50 s
-[Task 18/25]  Current/Best:   16.04/  18.98 GFLOPS | Progress: (20/20) | 17.56 s Done.
+[Task 18/25]  Current/Best:    7.81/  18.57 GFLOPS | Progress: (4/20) | 4.91 s
+[Task 18/25]  Current/Best:   18.78/  22.11 GFLOPS | Progress: (8/20) | 6.98 s
+[Task 18/25]  Current/Best:    5.96/  22.11 GFLOPS | Progress: (12/20) | 10.83 s
+[Task 18/25]  Current/Best:    5.07/  22.11 GFLOPS | Progress: (16/20) | 13.31 s
+[Task 18/25]  Current/Best:   14.80/  22.11 GFLOPS | Progress: (20/20) | 17.74 s Done.
 
 [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 19/25]  Current/Best:    5.49/  18.83 GFLOPS | Progress: (4/20) | 6.29 s
-[Task 19/25]  Current/Best:   12.08/  18.83 GFLOPS | Progress: (8/20) | 9.71 s
-[Task 19/25]  Current/Best:    5.09/  18.83 GFLOPS | Progress: (12/20) | 13.58 s
-[Task 19/25]  Current/Best:   22.12/  22.12 GFLOPS | Progress: (16/20) | 16.87 s
-[Task 19/25]  Current/Best:   17.32/  22.12 GFLOPS | Progress: (20/20) | 20.22 s Done.
+[Task 19/25]  Current/Best:    5.45/  10.68 GFLOPS | Progress: (4/20) | 6.41 s
+[Task 19/25]  Current/Best:   21.02/  21.50 GFLOPS | Progress: (8/20) | 9.75 s
+[Task 19/25]  Current/Best:   10.49/  21.50 GFLOPS | Progress: (12/20) | 13.11 s
+[Task 19/25]  Current/Best:   13.21/  21.50 GFLOPS | Progress: (16/20) | 19.00 s
+[Task 19/25]  Current/Best:   12.24/  21.50 GFLOPS | Progress: (20/20) | 23.80 s Done.
 
 [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 20/25]  Current/Best:    8.61/  12.09 GFLOPS | Progress: (4/20) | 6.79 s
-[Task 20/25]  Current/Best:   18.14/  18.14 GFLOPS | Progress: (8/20) | 9.83 s
-[Task 20/25]  Current/Best:    8.52/  18.58 GFLOPS | Progress: (12/20) | 13.98 s
-[Task 20/25]  Current/Best:    3.18/  20.98 GFLOPS | Progress: (16/20) | 25.93 s
-[Task 20/25]  Current/Best:   12.37/  20.98 GFLOPS | Progress: (20/20) | 37.38 s
+[Task 20/25]  Current/Best:    9.32/  17.72 GFLOPS | Progress: (4/20) | 15.16 s
+[Task 20/25]  Current/Best:   18.05/  18.08 GFLOPS | Progress: (8/20) | 24.87 s
+[Task 20/25]  Current/Best:    8.02/  18.08 GFLOPS | Progress: (12/20) | 27.83 s
+[Task 20/25]  Current/Best:   15.09/  18.08 GFLOPS | Progress: (16/20) | 30.19 s
+[Task 20/25]  Current/Best:    3.80/  19.86 GFLOPS | Progress: (20/20) | 36.28 s
 [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 21/25]  Current/Best:    9.67/  21.38 GFLOPS | Progress: (4/20) | 13.61 s
-[Task 21/25]  Current/Best:    8.86/  21.38 GFLOPS | Progress: (8/20) | 20.48 s
-[Task 21/25]  Current/Best:   16.18/  21.38 GFLOPS | Progress: (12/20) | 31.79 s Done.
-
-[Task 21/25]  Current/Best:   19.02/  21.38 GFLOPS | Progress: (16/20) | 34.38 s
-[Task 21/25]  Current/Best:   15.22/  21.38 GFLOPS | Progress: (20/20) | 36.27 s Done.
+[Task 21/25]  Current/Best:   10.68/  14.34 GFLOPS | Progress: (4/20) | 5.69 s
+[Task 21/25]  Current/Best:    6.70/  14.34 GFLOPS | Progress: (8/20) | 8.95 s
+[Task 21/25]  Current/Best:   21.09/  21.09 GFLOPS | Progress: (12/20) | 11.54 s
+[Task 21/25]  Current/Best:   13.63/  21.09 GFLOPS | Progress: (16/20) | 13.88 s
+[Task 21/25]  Current/Best:   16.77/  21.09 GFLOPS | Progress: (20/20) | 16.08 s Done.
 
 [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 22/25]  Current/Best:   16.64/  22.37 GFLOPS | Progress: (4/20) | 3.94 s
-[Task 22/25]  Current/Best:   11.51/  22.37 GFLOPS | Progress: (8/20) | 7.44 s
-[Task 22/25]  Current/Best:   16.70/  22.37 GFLOPS | Progress: (12/20) | 9.12 s
-[Task 22/25]  Current/Best:    2.83/  22.37 GFLOPS | Progress: (16/20) | 11.01 s
-[Task 22/25]  Current/Best:   14.16/  22.37 GFLOPS | Progress: (20/20) | 12.79 s Done.
+[Task 22/25]  Current/Best:   15.21/  19.50 GFLOPS | Progress: (4/20) | 4.04 s
+[Task 22/25]  Current/Best:   19.48/  19.50 GFLOPS | Progress: (8/20) | 5.82 s
+[Task 22/25]  Current/Best:   17.73/  19.50 GFLOPS | Progress: (12/20) | 7.87 s
+[Task 22/25]  Current/Best:    1.58/  19.50 GFLOPS | Progress: (16/20) | 10.36 s
+[Task 22/25]  Current/Best:    9.19/  19.50 GFLOPS | Progress: (20/20) | 12.10 s Done.
 
 [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 23/25]  Current/Best:   12.29/  19.38 GFLOPS | Progress: (4/20) | 5.68 s
-[Task 23/25]  Current/Best:   18.27/  20.24 GFLOPS | Progress: (8/20) | 9.25 s
-[Task 23/25]  Current/Best:   22.35/  22.35 GFLOPS | Progress: (12/20) | 12.82 s
-[Task 23/25]  Current/Best:   11.33/  22.35 GFLOPS | Progress: (16/20) | 17.50 s
-[Task 23/25]  Current/Best:   12.41/  22.35 GFLOPS | Progress: (20/20) | 19.87 s Done.
+[Task 23/25]  Current/Best:    9.29/  16.46 GFLOPS | Progress: (4/20) | 7.02 s
+[Task 23/25]  Current/Best:   21.01/  21.01 GFLOPS | Progress: (8/20) | 10.95 s
+[Task 23/25]  Current/Best:   20.55/  21.01 GFLOPS | Progress: (12/20) | 13.51 s
+[Task 23/25]  Current/Best:   12.11/  21.01 GFLOPS | Progress: (16/20) | 16.64 s
+[Task 23/25]  Current/Best:    9.97/  21.01 GFLOPS | Progress: (20/20) | 20.01 s Done.
 
 [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 24/25]  Current/Best:    2.20/  10.19 GFLOPS | Progress: (4/20) | 11.42 s
-[Task 24/25]  Current/Best:    3.63/  10.19 GFLOPS | Progress: (8/20) | 22.35 s
-[Task 24/25]  Current/Best:    9.85/  10.19 GFLOPS | Progress: (12/20) | 34.16 s
-[Task 24/25]  Current/Best:    3.94/  10.19 GFLOPS | Progress: (16/20) | 46.27 s
-[Task 24/25]  Current/Best:    4.99/  10.19 GFLOPS | Progress: (20/20) | 48.85 s
+[Task 24/25]  Current/Best:    1.42/   6.94 GFLOPS | Progress: (4/20) | 7.39 s
+[Task 24/25]  Current/Best:    2.91/   6.94 GFLOPS | Progress: (8/20) | 18.40 s
+[Task 24/25]  Current/Best:    9.16/   9.16 GFLOPS | Progress: (12/20) | 29.39 s Done.
+
+[Task 24/25]  Current/Best:    2.41/   9.16 GFLOPS | Progress: (16/20) | 36.83 s
+[Task 24/25]  Current/Best:    0.98/   9.16 GFLOPS | Progress: (20/20) | 47.89 s
 [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 25/25]  Current/Best:    7.98/   7.98 GFLOPS | Progress: (4/20) | 7.53 s
-[Task 25/25]  Current/Best:    3.09/   9.96 GFLOPS | Progress: (8/20) | 9.13 s
-[Task 25/25]  Current/Best:    9.80/   9.96 GFLOPS | Progress: (12/20) | 11.51 s
-[Task 25/25]  Current/Best:    3.10/   9.96 GFLOPS | Progress: (16/20) | 13.54 s
-[Task 25/25]  Current/Best:    8.05/   9.96 GFLOPS | Progress: (20/20) | 14.89 s Done.
+[Task 25/25]  Current/Best:    1.52/   5.64 GFLOPS | Progress: (4/20) | 13.50 s
+[Task 25/25]  Current/Best:    3.00/   9.16 GFLOPS | Progress: (8/20) | 16.73 s
+[Task 25/25]  Current/Best:    1.56/   9.27 GFLOPS | Progress: (12/20) | 23.68 s
+[Task 25/25]  Current/Best:    1.56/   9.27 GFLOPS | Progress: (16/20) | 25.75 s
+[Task 25/25]  Current/Best:    6.60/   9.27 GFLOPS | Progress: (20/20) | 29.00 s
 </pre></div>
 </div>
 <p>The output from this tuning process will look something like this:</p>
@@ -986,6 +986,7 @@ model using optimized operators to speed up our computations.</p>
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Done.
+Done.
 </pre></div>
 </div>
 <p>Verify that the optimized model runs and produces the same results:</p>
@@ -1002,7 +1003,7 @@ model using optimized operators to speed up our computations.</p>
     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;class=&#39;</span><span class="si">%s</span><span class="s2">&#39; with probability=</span><span class="si">%f</span><span class="s2">&quot;</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=&#39;n02123045 tabby, tabby cat&#39; with probability=0.621104
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>class=&#39;n02123045 tabby, tabby cat&#39; with probability=0.621105
 class=&#39;n02123159 tiger cat&#39; with probability=0.356378
 class=&#39;n02124075 Egyptian cat&#39; with probability=0.019712
 class=&#39;n02129604 tiger, Panthera tigris&#39; with probability=0.001215
@@ -1040,8 +1041,8 @@ improvement in comparing the optimized model to the unoptimized model.</p>
 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;unoptimized: </span><span class="si">%s</span><span class="s2">&quot;</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: {&#39;mean&#39;: 392.10471162999966, &#39;median&#39;: 392.5059785999565, &#39;std&#39;: 1.7312932702501085}
-unoptimized: {&#39;mean&#39;: 472.78118281999923, &#39;median&#39;: 472.4927659500054, &#39;std&#39;: 1.7815587371850354}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {&#39;mean&#39;: 404.171723390009, &#39;median&#39;: 403.35173505000057, &#39;std&#39;: 2.4715070031973183}
+unoptimized: {&#39;mean&#39;: 488.96065589000045, &#39;median&#39;: 489.13092864997907, &#39;std&#39;: 2.8590050185786398}
 </pre></div>
 </div>
 </div>
@@ -1055,7 +1056,7 @@ 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  52.917 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 12 minutes  41.331 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 0228a07693..836e3a4e5c 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">&quot;</span><span class="si">%g</span><span class="s2"> secs/op&quot;</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>1.186e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.22e-07 secs/op
 </pre></div>
 </div>
 </div>
diff --git a/docs/tutorial/intro_topi.html b/docs/tutorial/intro_topi.html
index 7f23a8cb01..5e93ecec86 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, 0x26c7a590)), stage(b, placeholder(b, 0x28e07900)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), &quot;DataPar&quot;, &quot;&quot;), T.iter_var(ax1, T.Range(0, 10), &quot;DataPar&quot;, &quot;&quot;), T.iter_var(ax2, T.Range(0, 10), &quot;DataPar&quot;, &quot;&quot;)], reduce_axis=[], tag=broadcast, attr [...]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[stage(a, placeholder(a, 0x12e62ac0)), stage(b, placeholder(b, 0x131cde30)), stage(T_add, compute(T_add, body=[a[ax0, ax1, ax2] + b[ax1, ax2]], axis=[T.iter_var(ax0, T.Range(0, 100), &quot;DataPar&quot;, &quot;&quot;), T.iter_var(ax1, T.Range(0, 10), &quot;DataPar&quot;, &quot;&quot;), T.iter_var(ax2, T.Range(0, 10), &quot;DataPar&quot;, &quot;&quot;)], 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 89ed476c21..3fdb0647aa 100644
--- a/docs/tutorial/sg_execution_times.html
+++ b/docs/tutorial/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-tutorial-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>16:28.118</strong> total execution time for <strong>tutorial</strong> files:</p>
+<p><strong>16:08.995</strong> total execution time for <strong>tutorial</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
@@ -369,35 +369,35 @@
 </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>12:52.917</p></td>
+<td><p>12:41.331</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>01:33.025</p></td>
+<td><p>01:29.500</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>00:57.773</p></td>
+<td><p>00:58.615</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>00:41.652</p></td>
+<td><p>00:42.937</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>00:20.800</p></td>
+<td><p>00:14.607</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>00:00.928</p></td>
+<td><p>00:00.949</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>00:00.837</p></td>
+<td><p>00:00.858</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>00:00.186</p></td>
+<td><p>00:00.198</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>
@@ -412,11 +412,11 @@
 <td><p>00:00.000</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="install.html#sphx-glr-tutorial-install-py"><span class="std std-ref">Installing TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">install.py</span></code>)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="introduction.html#sphx-glr-tutorial-introduction-py"><span class="std std-ref">Introduction</span></a> (<code class="docutils literal notranslate"><span class="pre">introduction.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="introduction.html#sphx-glr-tutorial-introduction-py"><span class="std std-ref">Introduction</span></a> (<code class="docutils literal notranslate"><span class="pre">introduction.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="install.html#sphx-glr-tutorial-install-py"><span class="std std-ref">Installing TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">install.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
diff --git a/docs/tutorial/tensor_expr_get_started.html b/docs/tutorial/tensor_expr_get_started.html
index e92f18b18f..58f5f5b33b 100644
--- a/docs/tutorial/tensor_expr_get_started.html
+++ b/docs/tutorial/tensor_expr_get_started.html
@@ -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">&quot;parallel&quot;</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: 0.000007
 </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: 0.000038
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector: 0.000041
 # 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    6.854769999335986e-06                    1.0
-   naive              7.7089e-06      1.1246037431958698
-parallel    6.305800000000001e-06     0.9199141620522405
-  vector             3.80685e-05       5.553578019931764
+   numpy    7.053879999148194e-06                    1.0
+   naive              7.7898e-06      1.1043283981214131
+parallel              6.8526e-06      0.9714653496837911
+  vector             4.11998e-05       5.840728791101517
 </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: 0.016611
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.017873
 </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: 3.274869
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>none: 3.295010
 </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: 0.299654
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>blocking: 0.302306
 </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: 0.270210
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vectorization: 0.278870
 # 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: 0.112230
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>loop permutation: 0.116149
 # 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: 0.103772
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array packing: 0.104551
 # 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: 0.100726
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>block caching: 0.108966
 # 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: 0.119668
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallelization: 0.129152
 # 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      3.2748691253000004                     1.0
-        blocking            0.2996541992     0.09150112194866708
-   vectorization     0.27021035849999997     0.08251027694892903
-loop permutation            0.1122299761     0.03427006448378879
-   array packing            0.1037720111     0.03168737654225916
-   block caching            0.1007260496     0.03075727479362181
- parallelization     0.11966844299999999     0.03654144285507518
+            none             3.295010456                     1.0
+        blocking            0.3023064685     0.09174674027195256
+   vectorization            0.2788703474     0.08463413124902083
+loop permutation            0.1161490822    0.035249988960884805
+   array packing     0.10455061780000001    0.031729980586137484
+   block caching     0.10896627650000001     0.03307008519550507
+ parallelization            0.1291516268     0.03919612047507263
 </pre></div>
 </div>
 <p>Note that the outputs on the web page reflect the running times on a