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Posted to commits@tvm.apache.org by tq...@apache.org on 2024/03/20 19:37:35 UTC

(tvm-site) branch asf-site updated: deploying docs (apache/tvm@0f38ef2d6e6ecb7d1b8e164582f417b15b8f4e9a)

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 2cd03e077f deploying docs (apache/tvm@0f38ef2d6e6ecb7d1b8e164582f417b15b8f4e9a)
2cd03e077f is described below

commit 2cd03e077f9dd34fab8172cd4cabd784f1ac5549
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Wed Mar 20 19:37:29 2024 +0000

    deploying docs (apache/tvm@0f38ef2d6e6ecb7d1b8e164582f417b15b8f4e9a)
---
 .../how_to/compile_models/from_darknet.rst.txt     |   2 +-
 .../how_to/compile_models/from_oneflow.rst.txt     |   2 +-
 .../how_to/compile_models/from_paddle.rst.txt      |   5 +
 .../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      |  20 +-
 .../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 +-
 .../deploy_models/sg_execution_times.rst.txt       |  18 +-
 .../how_to/extend_tvm/sg_execution_times.rst.txt   |   6 +-
 .../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   |   6 +-
 .../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/frontend/deploy_detection.rst.txt    |   7 +-
 .../tutorials/frontend/sg_execution_times.rst.txt  |   4 +-
 .../tutorials/optimize/sg_execution_times.rst.txt  |   6 +-
 .../topic/vta/tutorials/sg_execution_times.rst.txt |   6 +-
 .../tutorial/auto_scheduler_matmul_x86.rst.txt     |   6 +-
 docs/_sources/tutorial/autotvm_matmul_x86.rst.txt  |  20 +-
 docs/_sources/tutorial/autotvm_relay_x86.rst.txt   |  56 ++---
 .../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       |  49 ++--
 docs/commit_hash                                   |   2 +-
 docs/how_to/compile_models/from_darknet.html       |   2 +-
 docs/how_to/compile_models/from_oneflow.html       |  16 +-
 docs/how_to/compile_models/from_paddle.html        |   1 +
 docs/how_to/compile_models/from_pytorch.html       |  15 +-
 docs/how_to/compile_models/from_tensorflow.html    |   2 +-
 docs/how_to/compile_models/sg_execution_times.html |  20 +-
 .../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           |  58 +++--
 docs/how_to/deploy_models/deploy_prequantized.html |   8 +-
 .../deploy_models/deploy_prequantized_tflite.html  |   2 +-
 docs/how_to/deploy_models/sg_execution_times.html  |  18 +-
 docs/how_to/extend_tvm/sg_execution_times.html     |   6 +-
 docs/how_to/extend_tvm/use_pass_instrument.html    |  16 +-
 docs/how_to/optimize_operators/opt_conv_cuda.html  |   2 +-
 .../optimize_operators/opt_conv_tensorcore.html    |   2 +-
 docs/how_to/optimize_operators/opt_gemm.html       |  16 +-
 .../optimize_operators/sg_execution_times.html     |   8 +-
 .../sg_execution_times.html                        |  14 +-
 .../tune_conv2d_layer_cuda.html                    |   2 +-
 .../tune_with_autoscheduler/tune_network_cuda.html |   4 +-
 .../tune_with_autoscheduler/tune_network_x86.html  |   4 +-
 .../tune_with_autotvm/sg_execution_times.html      |   6 +-
 .../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         |  12 +-
 docs/reference/api/typedoc/classes/DLDataType.html |  14 +-
 docs/reference/api/typedoc/classes/DLDevice.html   |  12 +-
 docs/reference/api/typedoc/classes/Instance.html   | 114 ++++-----
 .../classes/LinearCongruentialGenerator.html       |  16 +-
 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_.AsyncifyHandler.html        |  12 +-
 .../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 |  56 ++---
 .../api/typedoc/classes/_internal_.TVMString.html  |  14 +-
 .../typedoc/classes/_internal_.WebGPUContext.html  |  28 +--
 .../enums/_internal_.AsyncifyStateKind.html        |   8 +-
 .../typedoc/enums/_internal_.RPCServerState.html   |  14 +-
 docs/reference/api/typedoc/functions/assert.html   |   2 +-
 .../api/typedoc/functions/createPolyfillWASI.html  |   2 +-
 .../api/typedoc/functions/deleteNDArrayCache.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 +-
 .../_internal_.ArtifactCacheTemplate.html          |  10 +-
 .../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 +-
 .../typedoc/types/_internal_.AsyncPackedFunc.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/frontend/deploy_detection.html   |   3 +-
 .../vta/tutorials/frontend/sg_execution_times.html |   4 +-
 .../vta/tutorials/optimize/sg_execution_times.html |   6 +-
 docs/topic/vta/tutorials/sg_execution_times.html   |   6 +-
 docs/tutorial/auto_scheduler_matmul_x86.html       |   5 +-
 docs/tutorial/autotvm_matmul_x86.html              |  20 +-
 docs/tutorial/autotvm_relay_x86.html               | 273 ++++++++++-----------
 docs/tutorial/cross_compilation_and_rpc.html       |   2 +-
 docs/tutorial/intro_topi.html                      |   2 +-
 docs/tutorial/sg_execution_times.html              |  26 +-
 docs/tutorial/tensor_expr_get_started.html         |  45 ++--
 137 files changed, 895 insertions(+), 883 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 1f2dac35d5..ebe84c7ee4 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  31.046 seconds)
+   **Total running time of the script:** ( 1 minutes  35.180 seconds)
 
 
 .. _sphx_glr_download_how_to_compile_models_from_darknet.py:
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 3a54b1ab45..b3c9fbe59e 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]       3%|2         | 1.20M/41.5M [00:00<00:03, 12.5MB/s]      17%|#6        | 6.86M/41.5M [00:00<00:00, 40.1MB/s]      26%|##5       | 10.7M/41.5M [00:00<00:00, 39.8MB/s]      39%|###8      | 16.0M/41.5M [00:00<00:00, 34.9MB/s]      54%|#####3    | 22.3M/41.5M [00:00<00:00, 41.4MB/s]      64%|######3   | 26.4M/41.5M [00:00<00:00, 38.6MB/s]      77%|#######7  | 32.0M/41.5M [00:00<00:00, 40.8MB/s]      92%|#########2| 38.3M/41.5M [00:01<00:00, 41.3MB/s]     100%|##########| 41.5M/41.5M [00:01<00:00, 40.2MB/s]
+       0%|          | 0.00/41.5M [00:00<?, ?B/s]      15%|#5        | 6.33M/41.5M [00:00<00:02, 16.8MB/s]      35%|###4      | 14.3M/41.5M [00:00<00:01, 24.4MB/s]      41%|####      | 16.8M/41.5M [00:00<00:01, 24.0MB/s]      58%|#####7    | 24.0M/41.5M [00:00<00:00, 28.3MB/s]      84%|########4 | 35.0M/41.5M [00:01<00:00, 46.0MB/s]      98%|#########8| 40.7M/41.5M [00:01<00:00, 36.7MB/s]     100%|##########| 41.5M/41.5M [00:01<00:00, 32.6MB/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 8df75c9e33..5ce8aea381 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -207,6 +207,11 @@ Look up prediction top 1 index in 1000 class synset.
 
 
 
+.. rst-class:: sphx-glr-timing
+
+   **Total running time of the script:** ( 1 minutes  2.114 seconds)
+
+
 .. _sphx_glr_download_how_to_compile_models_from_paddle.py:
 
 .. only:: html
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 376cefcb9f..b55eab44e2 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
-       0%|          | 0.00/44.7M [00:00<?, ?B/s]      18%|#7        | 7.99M/44.7M [00:00<00:00, 43.6MB/s]      36%|###5      | 16.0M/44.7M [00:00<00:00, 58.2MB/s]      54%|#####3    | 24.0M/44.7M [00:00<00:00, 63.0MB/s]      68%|######7   | 30.3M/44.7M [00:00<00:00, 58.9MB/s]      81%|########  | 36.1M/44.7M [00:00<00:00, 57.2MB/s]      93%|#########3| 41.6M/44.7M [00:00<00:00, 47.4MB/s]     100%|##########| 44.7M/44.7M [00:00<00:00, 55.6MB/s]
+       0%|          | 0.00/44.7M [00:00<?, ?B/s]      18%|#7        | 7.99M/44.7M [00:00<00:00, 43.5MB/s]      32%|###2      | 14.3M/44.7M [00:00<00:00, 34.8MB/s]      40%|###9      | 17.7M/44.7M [00:00<00:00, 33.0MB/s]      54%|#####3    | 24.0M/44.7M [00:00<00:00, 35.7MB/s]      72%|#######1  | 32.0M/44.7M [00:00<00:00, 40.5MB/s]      86%|########5 | 38.3M/44.7M [00:01<00:00, 42.3MB/s]      96%|#########6| 43.1M/44.7M [00:01<00:00, 44.1MB/s]     100%|##########| 44.7M/44.7M [00:01<00:00, 41.7MB/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 20579d23bf..745e02d4d7 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  28.321 seconds)
+   **Total running time of the script:** ( 1 minutes  31.592 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 3ca294e7a9..aa6d8872ff 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
@@ -5,24 +5,24 @@
 
 Computation times
 =================
-**06:26.266** total execution time for **how_to_compile_models** files:
+**06:42.208** total execution time for **how_to_compile_models** files:
 
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:31.046 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:35.180 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:28.321 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:31.592 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 00:59.852 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 01:02.114 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:42.080 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:43.672 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:37.067 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:38.503 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:27.673 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:28.923 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:25.892 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:27.167 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:11.565 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:12.147 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.769 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.909 | 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 4ba82e3774..d6dd50db28 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)  
-     3994.3996    3994.8751    4000.6321    3989.2283      3.2530                  
+     4122.0512    4122.1482    4125.6389    4118.9306      2.3064                  
 
 
 
@@ -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  17.224 seconds)
+   **Total running time of the script:** ( 1 minutes  19.772 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 4314030a86..7c22b9b1c9 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
-          8192/102967424 [..............................] - ETA: 0s       6635520/102967424 [>.............................] - ETA: 1s       8380416/102967424 [=>............................] - ETA: 2s      15024128/102967424 [===>..........................] - ETA: 1s      16769024/102967424 [===>..........................] - ETA: 2s      23412736/102967424 [=====>........................] - ETA: 1s      25157632/102967424 [======>.......................] - ETA: 1s      25296896/102967424 [======>.......................] - ETA: 2s
       33546240/102967424 [========>.....................] - ETA: 1s      41934848/102967424 [===========>..................] - ETA: 1s      48783360/102967424 [=============>................] - ETA: 0s      50323456/102967424 [=============>................] - ETA: 0s      58712064/102967424 [================>.............] - ETA: 0s      67100672/102967424 [==================>...........] - ETA: 0s      73744384/102967424 [====================>.........] - ETA: 0s      75489280/102967424 [====================>.........] -
  ETA: 0s      82124800/102967424 [======================>.......] - ETA: 0s      83877888/102967424 [=======================>......] - ETA: 0s      92266496/102967424 [=========================>....] - ETA: 0s     100646912/102967424 [============================>.] - ETA: 0s     102850560/102967424 [============================>.] - ETA: 0s     102967424/102967424 [==============================] - 2s 0us/step
+          8192/102967424 [..............................] - ETA: 0s       6635520/102967424 [>.............................] - ETA: 0s       8380416/102967424 [=>............................] - ETA: 1s      16769024/102967424 [===>..........................] - ETA: 1s      25157632/102967424 [======>.......................] - ETA: 1s      33546240/102967424 [========>.....................] - ETA: 1s      40189952/102967424 [==========>...................] - ETA: 0s      43196416/102967424 [===========>..................] - ETA: 0s
       50323456/102967424 [=============>................] - ETA: 0s      56967168/102967424 [===============>..............] - ETA: 0s      58712064/102967424 [================>.............] - ETA: 0s      65355776/102967424 [==================>...........] - ETA: 0s      67239936/102967424 [==================>...........] - ETA: 0s      69296128/102967424 [===================>..........] - ETA: 0s      75489280/102967424 [====================>.........] - ETA: 0s      83877888/102967424 [=======================>......] -
  ETA: 0s      92266496/102967424 [=========================>....] - ETA: 0s     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 d9f8a94ad8..9cbd02129c 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)  
-      14.2251      14.2108      14.3957      14.1126       0.0912                  
+      14.8821      14.8402      15.5314      14.5001       0.2710                  
 
 
 
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 a6a4cfc13a..bb06abafe2 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
-       0%|          | 0.00/170M [00:00<?, ?B/s]       5%|4         | 7.99M/170M [00:00<00:03, 50.8MB/s]       9%|9         | 16.0M/170M [00:00<00:04, 38.9MB/s]      13%|#3        | 22.3M/170M [00:00<00:03, 42.2MB/s]      16%|#5        | 26.5M/170M [00:00<00:03, 40.6MB/s]      19%|#8        | 32.0M/170M [00:00<00:03, 39.4MB/s]      24%|##3       | 40.0M/170M [00:00<00:03, 44.6MB/s]      27%|##7       | 46.3M/170M [00:01<00:02, 49.2MB/s]      30%|###       | 51.1M/170M [00:01<00:03, 41.4MB/s]      33%|###2      | 56.0M/170M [00:01<00:02, 42.4MB/s]      37%|###6      | 62.3M/170M [00:01<00:02, 39.2MB/s]      39%|###8      | 66.2M/170M [00:01<00:03, 35.3MB/s]      42%|####2     | 72.0M/170M [00:01<00:02, 40.2MB/s]      46%|####6     | 78.3M/170M [00:02<00:02, 39.8MB/s]      48%|####8     | 82.3M/170M [00:02<00:02, 38.8MB/s]      52%|#####1    | 88.0M/170M [00:02<00:02, 30.7MB/s]      56%|#####5    | 94.3M/170M [00:02<00:02, 27.8MB/s]      57%|#####7    | 97.3M/170M [00:02<00:02, 28.0MB/
 s]      61%|######1   | 104M/170M [00:02<00:02, 30.9MB/s]       66%|######5   | 112M/170M [00:03<00:01, 40.7MB/s]      71%|#######   | 120M/170M [00:03<00:01, 40.3MB/s]      75%|#######5  | 128M/170M [00:03<00:01, 40.7MB/s]      80%|########  | 136M/170M [00:03<00:00, 41.9MB/s]      85%|########4 | 144M/170M [00:03<00:00, 42.6MB/s]      88%|########8 | 150M/170M [00:04<00:00, 41.4MB/s]      91%|######### | 154M/170M [00:04<00:00, 39.4MB/s]      93%|#########3| 158M/170M [00:04<00:00, 29.3MB/s]      95%|#########5| 161M/170M [00:04<00:00, 26.6MB/s]      99%|#########8| 168M/170M [00:04<00:00, 33.6MB/s]     100%|##########| 170M/170M [00:04<00:00, 37.6MB/s]
+       0%|          | 0.00/170M [00:00<?, ?B/s]       5%|5         | 9.04M/170M [00:00<00:01, 94.8MB/s]      11%|#         | 18.1M/170M [00:00<00:02, 65.7MB/s]      15%|#4        | 24.8M/170M [00:00<00:03, 50.5MB/s]      18%|#7        | 30.3M/170M [00:00<00:02, 51.4MB/s]      21%|##1       | 36.5M/170M [00:00<00:02, 55.3MB/s]      27%|##7       | 46.3M/170M [00:00<00:02, 60.8MB/s]      31%|###       | 52.2M/170M [00:00<00:02, 52.7MB/s]      35%|###4      | 59.0M/170M [00:01<00:02, 57.1MB/s]      38%|###8      | 64.7M/170M [00:01<00:02, 45.8MB/s]      43%|####3     | 73.6M/170M [00:01<00:01, 56.7MB/s]      47%|####6     | 79.7M/170M [00:01<00:01, 55.3MB/s]      50%|#####     | 85.4M/170M [00:01<00:01, 56.4MB/s]      54%|#####3    | 91.2M/170M [00:01<00:01, 43.6MB/s]      57%|#####6    | 96.5M/170M [00:01<00:01, 46.4MB/s]      61%|######1   | 104M/170M [00:02<00:01, 42.1MB/s]       66%|######5   | 112M/170M [00:02<00:01, 43.3MB/s]      71%|#######   | 120M/170M [00:02<00:01, 48.4MB/s]
       74%|#######4  | 126M/170M [00:02<00:01, 44.3MB/s]      77%|#######7  | 131M/170M [00:02<00:01, 40.1MB/s]      79%|#######9  | 135M/170M [00:02<00:01, 34.9MB/s]      82%|########2 | 140M/170M [00:03<00:00, 38.9MB/s]      85%|########4 | 144M/170M [00:03<00:00, 39.5MB/s]      88%|########8 | 150M/170M [00:03<00:00, 43.5MB/s]      91%|#########1| 155M/170M [00:03<00:00, 38.6MB/s]      94%|#########4| 160M/170M [00:03<00:00, 36.0MB/s]      98%|#########7| 166M/170M [00:03<00:00, 33.9MB/s]     100%|##########| 170M/170M [00:03<00:00, 45.3MB/s]
     /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  26.331 seconds)
+   **Total running time of the script:** ( 3 minutes  35.699 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 512f430430..54722f7012 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]      59%|#####8    | 7.99M/13.6M [00:00<00:00, 69.1MB/s]     100%|##########| 13.6M/13.6M [00:00<00:00, 47.8MB/s]
+       0%|          | 0.00/13.6M [00:00<?, ?B/s]      59%|#####8    | 7.99M/13.6M [00:00<00:00, 59.5MB/s]     100%|##########| 13.6M/13.6M [00:00<00:00, 56.3MB/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)  
-      86.0477      85.9436      87.6205      85.5688       0.3207                  
+      88.8394      88.8050      89.4554      88.5079       0.2201                  
 
 
 
@@ -457,7 +457,7 @@ TODO
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  26.199 seconds)
+   **Total running time of the script:** ( 1 minutes  29.713 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 39ab906789..fe08265a44 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)  
-      105.0875     104.9699     107.3328     103.4988      1.0124                  
+      109.6496     109.6988     113.3938     108.4932      0.7184                  
 
 
 
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 fac2c5aa1c..f0f60ce81b 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
@@ -5,24 +5,24 @@
 
 Computation times
 =================
-**09:33.158** total execution time for **how_to_deploy_models** files:
+**09:55.551** 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``) | 03:26.331 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:35.699 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:26.199 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:29.713 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:17.224 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:19.772 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:49.963 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:52.021 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:49.773 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:51.393 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:45.588 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:47.132 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:29.131 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:29.976 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:28.938 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:29.835 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)                                     | 00:00.010 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
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 ff10848120..53232af26b 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
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**00:03.928** total execution time for **how_to_extend_tvm** files:
+**00:04.131** total execution time for **how_to_extend_tvm** files:
 
 +-------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)     | 00:02.737 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)     | 00:02.855 | 0.0 MB |
 +-------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)               | 00:01.184 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)               | 00:01.269 | 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 |
 +-------------------------------------------------------------------------------------------+-----------+--------+
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 78ecf480be..09bb0b073a 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: 25914us [25914us] (49.38%; 49.38%)
-    FoldScaleAxis: 26567us [7us] (50.62%; 50.62%)
-            FoldConstant: 26560us [1831us] (50.61%; 99.97%)
-                    InferType: 24728us [24728us] (47.12%; 93.10%)
+    InferType: 25998us [25998us] (49.24%; 49.24%)
+    FoldScaleAxis: 26803us [8us] (50.76%; 50.76%)
+            FoldConstant: 26794us [1892us] (50.75%; 99.97%)
+                    InferType: 24902us [24902us] (47.16%; 92.94%)
 
 
 
@@ -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: 24506us [24506us] (48.76%; 48.76%)
-    FoldScaleAxis: 25754us [5us] (51.24%; 51.24%)
-            FoldConstant: 25749us [1662us] (51.23%; 99.98%)
-                    InferType: 24087us [24087us] (47.92%; 93.55%)
+    InferType: 24890us [24890us] (48.19%; 48.19%)
+    FoldScaleAxis: 26755us [8us] (51.81%; 51.81%)
+            FoldConstant: 26747us [1937us] (51.79%; 99.97%)
+                    InferType: 24810us [24810us] (48.04%; 92.76%)
 
 
 
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 f3eb1f58ef..0a4b9172b6 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_cuda.rst.txt
@@ -331,7 +331,7 @@ latency of convolution.
 
  .. code-block:: none
 
-    Convolution: 53.526622 ms
+    Convolution: 40.099166 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 ddd18fbeaa..070595c397 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: 11.137446 ms
+    conv2d with tensor core: 12.263565 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 940afd4c8d..a3ab35c7b7 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: 0.017209
-    Baseline: 3.249494
+    Numpy running time: 0.017778
+    Baseline: 3.122380
 
 
 
@@ -227,7 +227,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
 
  .. code-block:: none
 
-    Opt1: 0.281671
+    Opt1: 0.287623
 
 
 
@@ -318,7 +318,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
 
  .. code-block:: none
 
-    Opt2: 0.262739
+    Opt2: 0.270746
 
 
 
@@ -406,7 +406,7 @@ the access pattern for A matrix is more cache friendly.
 
  .. code-block:: none
 
-    Opt3: 0.111100
+    Opt3: 0.116796
 
 
 
@@ -523,7 +523,7 @@ flattening.
 
  .. code-block:: none
 
-    Opt4: 0.102508
+    Opt4: 0.108060
 
 
 
@@ -635,7 +635,7 @@ write to C when all the block results are ready.
 
  .. code-block:: none
 
-    Opt5: 0.110018
+    Opt5: 0.111517
 
 
 
@@ -748,7 +748,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
 
  .. code-block:: none
 
-    Opt6: 0.127944
+    Opt6: 0.132610
 
 
 
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 82aea93d53..4dbe0a4e45 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
 =================
-**00:32.431** total execution time for **how_to_optimize_operators** files:
+**00:33.274** total execution time for **how_to_optimize_operators** files:
 
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:29.489 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:30.300 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.776 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.832 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.167 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.142 | 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 8c53b0609d..1fd8a452fa 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
 =================
-**03:31.821** total execution time for **how_to_tune_with_autoscheduler** files:
+**03:40.359** 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``)             | 01:31.930 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)             | 01:36.236 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:11.148 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:13.618 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:17.243 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:17.940 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:16.010 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:16.639 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:15.393 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:15.825 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)               | 00:00.098 | 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 |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
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 fb06a4677d..ae11619806 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: 0.346 ms
+    Execution time of this operator: 0.341 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 da90cc3f6f..bc9a1af3d1 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
@@ -633,7 +633,7 @@ 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)  
-       3.2591       3.2560       3.2657       3.2555       0.0047                  
+       3.2167       3.2109       3.2293       3.2098       0.0089                  
 
 
 
@@ -660,7 +660,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  11.148 seconds)
+   **Total running time of the script:** ( 1 minutes  13.618 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 95552325ff..5125c30489 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
@@ -655,7 +655,7 @@ 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)  
-      730.7174     730.0098     732.2694     729.8730      1.0988                  
+      803.4541     803.7370     804.5003     802.1249      0.9902                  
 
 
 
@@ -682,7 +682,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  31.930 seconds)
+   **Total running time of the script:** ( 1 minutes  36.236 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 90d351ee7a..ecabcace02 100644
--- a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**00:23.949** total execution time for **how_to_tune_with_autotvm** files:
+**00:23.912** total execution time for **how_to_tune_with_autotvm** files:
 
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)           | 00:23.913 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)           | 00:23.875 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)               | 00:00.021 | 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``)             | 00:00.005 | 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 0191e852ae..4461b2a85d 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: 0.037173
+    Time cost of this operator: 0.037269
 
 
 
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 f3f629fa71..49c6e226f5 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  293.5     98.741   (1, 2, 10, 10, 3)  2       1        [293.5]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.818     0.948    (1, 6, 10, 10)     1       1        [2.818]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.924     0.311    (1, 1, 10, 10, 3)  1       1        [0.924]           
-    Total_time                                    -                                             297.243   -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  304.4     98.737   (1, 2, 10, 10, 3)  2       1        [304.4]           
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.919     0.947    (1, 6, 10, 10)     1       1        [2.919]           
+    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.976     0.317    (1, 1, 10, 10, 3)  1       1        [0.976]           
+    Total_time                                    -                                             308.295   -        -                  -       -        -                 
 
 
 
@@ -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  108.6     97.626   (1, 6, 10, 10, 1)  2       1        [108.6]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.716     1.543    (1, 6, 10, 10)     1       1        [1.716]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.924     0.831    (1, 1, 10, 10, 3)  1       1        [0.924]           
-    Total_time                                    -                                             111.24    -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  137.5     98.139   (1, 6, 10, 10, 1)  2       1        [137.5]           
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.763     1.258    (1, 6, 10, 10)     1       1        [1.763]           
+    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.845     0.603    (1, 3, 10, 10, 1)  1       1        [0.845]           
+    Total_time                                    -                                             140.108   -        -                  -       -        -                 
 
 
 
@@ -439,7 +439,7 @@ Timing the tuned program
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  25.008 seconds)
+   **Total running time of the script:** ( 1 minutes  26.088 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 333297ff43..e5a117ca7a 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, 11.6MB/s]     100%|##########| 3.42M/3.42M [00:00<00:00, 18.5MB/s]
+       0%|          | 0.00/3.42M [00:00<?, ?B/s]      61%|######    | 2.09M/3.42M [00:00<00:00, 14.7MB/s]     100%|##########| 3.42M/3.42M [00:00<00:00, 23.1MB/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  25.883 seconds)
+   **Total running time of the script:** ( 1 minutes  29.436 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 70d6bffe67..d96fa88ab6 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/tmp_4hzk1t9/images/random'
+    '/tmp/tmpuwfq9vao/images/random'
 
 
 
@@ -317,8 +317,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
 
  .. code-block:: none
 
-    /tmp/tmp_4hzk1t9/images/target contains 8144 images
-    /tmp/tmp_4hzk1t9/images/random contains 5000 images
+    /tmp/tmpuwfq9vao/images/target contains 8144 images
+    /tmp/tmpuwfq9vao/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: 0.2221 - accuracy: 0.9256 - val_loss: 0.1455 - val_accuracy: 0.9471 - 39s/epoch - 119ms/step
+    328/328 - 39s - loss: 0.2173 - accuracy: 0.9259 - val_loss: 0.1433 - val_accuracy: 0.9517 - 39s/epoch - 119ms/step
     Epoch 2/3
-    328/328 - 34s - loss: 0.1035 - accuracy: 0.9620 - val_loss: 0.1032 - val_accuracy: 0.9619 - 34s/epoch - 104ms/step
+    328/328 - 35s - loss: 0.1003 - accuracy: 0.9622 - val_loss: 0.1236 - val_accuracy: 0.9562 - 35s/epoch - 108ms/step
     Epoch 3/3
-    328/328 - 35s - loss: 0.0671 - accuracy: 0.9753 - val_loss: 0.0889 - val_accuracy: 0.9705 - 35s/epoch - 105ms/step
+    328/328 - 35s - loss: 0.0617 - accuracy: 0.9773 - val_loss: 0.1019 - val_accuracy: 0.9656 - 35s/epoch - 108ms/step
 
-    <keras.callbacks.History object at 0x7fbd534f98b0>
+    <keras.callbacks.History object at 0x7fbd31f2f730>
 
 
 
@@ -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  49.621 seconds)
+   **Total running time of the script:** ( 4 minutes  34.657 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 78c9e4c537..07a753c911 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
 =================
-**08:08.144** total execution time for **how_to_work_with_microtvm** files:
+**07:58.351** total execution time for **how_to_work_with_microtvm** files:
 
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:49.621 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:34.657 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:25.883 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:29.436 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:25.008 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:26.088 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:11.695 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:12.045 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:08.658 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:08.874 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:07.278 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:07.250 | 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 3135b6209f..e2a0331d3c 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
 =================
-**00:37.356** total execution time for **how_to_work_with_relay** files:
+**00:38.154** total execution time for **how_to_work_with_relay** files:
 
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:32.413 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:33.186 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.066 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.141 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:01.871 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:01.820 | 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 ff561a6c0c..99f52c97a3 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 0x7fbf403949d0>
+    <function my_cuda_math_rule at 0x7fbf0a996820>
 
 
 
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 f7227d7e9e..d9a6534a24 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
 =================
-**00:05.171** total execution time for **how_to_work_with_schedules** files:
+**00:05.075** total execution time for **how_to_work_with_schedules** files:
 
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.456 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.433 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:01.031 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:00.958 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.699 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.701 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.696 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.690 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.121 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.123 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.068 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.070 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)                               | 00:00.068 | 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``)               | 00:00.032 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
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 884b4822e1..4ef56c799c 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 25.91s!
+    yolov3-tiny inference graph built in 27.20s!
 
 
 
@@ -445,6 +445,11 @@ Download test image
 
 
 
+.. rst-class:: sphx-glr-timing
+
+   **Total running time of the script:** ( 1 minutes  0.711 seconds)
+
+
 .. _sphx_glr_download_topic_vta_tutorials_frontend_deploy_detection.py:
 
 .. only:: html
diff --git a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
index ea60e77703..2119fb4cdb 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
@@ -5,8 +5,8 @@
 
 Computation times
 =================
-**00:58.587** total execution time for **topic_vta_tutorials_frontend** files:
+**01:00.711** total execution time for **topic_vta_tutorials_frontend** files:
 
 +--------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:58.587 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 01:00.711 | 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 d374855a02..e58c936620 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
 =================
-**00:03.203** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.221** total execution time for **topic_vta_tutorials_optimize** files:
 
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.721 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.753 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.482 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.468 | 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 e001ad33fa..dc80c39c7a 100644
--- a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
 
 Computation times
 =================
-**00:00.781** total execution time for **topic_vta_tutorials** files:
+**00:00.753** total execution time for **topic_vta_tutorials** files:
 
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.404 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.389 | 0.0 MB |
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.377 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.364 | 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 5f984af237..10c46d4a55 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -318,7 +318,7 @@ We build the binary and check its correctness and performance.
 
  .. code-block:: none
 
-    Execution time of this operator: 93.558 ms
+    Execution time of this operator: 95.753 ms
 
 
 
@@ -416,7 +416,7 @@ resume the status and do more 5 trials.
  .. code-block:: none
 
     Resume search:
-
+    *E
 
 
 
@@ -434,7 +434,7 @@ operations.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  25.286 seconds)
+   **Total running time of the script:** ( 1 minutes  41.544 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 caca3504fc..0f5f41fef5 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: 11.65/11.65     result: MeasureResult(costs=(0.0230376522,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6356058120727539, timestamp=1710952624.9378529)       [('tile_y', [-1, 4]), ('tile_x', [-1, 512])],None,92
-    No: 2   GFLOPS: 8.25/11.65      result: MeasureResult(costs=(0.0325505864,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7752537727355957, timestamp=1710952625.7134717)       [('tile_y', [-1, 1]), ('tile_x', [-1, 8])],None,30
-    No: 3   GFLOPS: 8.54/11.65      result: MeasureResult(costs=(0.031416386799999994,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7668333053588867, timestamp=1710952626.4709394)       [('tile_y', [-1, 16]), ('tile_x', [-1, 8])],None,34
-    No: 4   GFLOPS: 2.14/11.65      result: MeasureResult(costs=(0.12564527060000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.257471799850464, timestamp=1710952628.7345502) [('tile_y', [-1, 32]), ('tile_x', [-1, 4])],None,25
-    No: 5   GFLOPS: 8.91/11.65      result: MeasureResult(costs=(0.030138117799999996,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7545211315155029, timestamp=1710952629.6838677)       [('tile_y', [-1, 8]), ('tile_x', [-1, 8])],None,33
-    No: 6   GFLOPS: 6.34/11.65      result: MeasureResult(costs=(0.0423325792,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.945284366607666, timestamp=1710952630.617679) [('tile_y', [-1, 16]), ('tile_x', [-1, 4])],None,24
-    No: 7   GFLOPS: 12.70/12.70     result: MeasureResult(costs=(0.021133044799999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6931145191192627, timestamp=1710952631.215719)        [('tile_y', [-1, 256]), ('tile_x', [-1, 128])],None,78
-    No: 8   GFLOPS: 8.94/12.70      result: MeasureResult(costs=(0.0300193318,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7496693134307861, timestamp=1710952631.9548552)       [('tile_y', [-1, 2]), ('tile_x', [-1, 64])],None,61
-    No: 9   GFLOPS: 0.52/12.70      result: MeasureResult(costs=(0.5165772869999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.509665966033936, timestamp=1710952640.574059)   [('tile_y', [-1, 64]), ('tile_x', [-1, 1])],None,6
-    No: 10  GFLOPS: 1.96/12.70      result: MeasureResult(costs=(0.1367587458,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4044830799102783, timestamp=1710952643.0227075)       [('tile_y', [-1, 1]), ('tile_x', [-1, 2])],None,10
+    No: 1   GFLOPS: 10.52/10.52     result: MeasureResult(costs=(0.0255119836,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7534909248352051, timestamp=1710958532.3695402)       [('tile_y', [-1, 8]), ('tile_x', [-1, 64])],None,63
+    No: 2   GFLOPS: 10.31/10.52     result: MeasureResult(costs=(0.026043288999999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6888840198516846, timestamp=1710958533.0425768)       [('tile_y', [-1, 2]), ('tile_x', [-1, 64])],None,61
+    No: 3   GFLOPS: 13.37/13.37     result: MeasureResult(costs=(0.0200773646,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5822114944458008, timestamp=1710958533.6184666)       [('tile_y', [-1, 256]), ('tile_x', [-1, 64])],None,68
+    No: 4   GFLOPS: 3.65/13.37      result: MeasureResult(costs=(0.07347294480000001,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4587929248809814, timestamp=1710958535.0518515)        [('tile_y', [-1, 64]), ('tile_x', [-1, 8])],None,36
+    No: 5   GFLOPS: 1.94/13.37      result: MeasureResult(costs=(0.13806226959999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4694745540618896, timestamp=1710958537.653597) [('tile_y', [-1, 8]), ('tile_x', [-1, 1])],None,3
+    No: 6   GFLOPS: 3.46/13.37      result: MeasureResult(costs=(0.0775120986,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.516719102859497, timestamp=1710958539.1676307)        [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
+    No: 7   GFLOPS: 10.55/13.37     result: MeasureResult(costs=(0.0254555586,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6843729019165039, timestamp=1710958539.8332918)       [('tile_y', [-1, 4]), ('tile_x', [-1, 32])],None,52
+    No: 8   GFLOPS: 0.99/13.37      result: MeasureResult(costs=(0.2720029142,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.609287977218628, timestamp=1710958544.4492793)        [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
+    No: 9   GFLOPS: 8.21/13.37      result: MeasureResult(costs=(0.0327070768,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7589902877807617, timestamp=1710958545.3176453)       [('tile_y', [-1, 16]), ('tile_x', [-1, 8])],None,34
+    No: 10  GFLOPS: 3.63/13.37      result: MeasureResult(costs=(0.0740125118,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.410879135131836, timestamp=1710958546.7573817)        [('tile_y', [-1, 256]), ('tile_x', [-1, 8])],None,38
 
 
 
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index be53cae255..8488e336ae 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': 472.81652373001634, 'median': 473.12350920001336, 'std': 2.307640356318348}
+    {'mean': 491.0514597600195, 'median': 490.92375170002924, 'std': 1.5121823348393049}
 
 
 
@@ -582,31 +582,31 @@ the tuning data to.
 
  .. code-block:: none
 
-     [Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  1/25]  Current/Best:   15.60/  20.89 GFLOPS | Progress: (4/20) | 8.00 s     [Task  1/25]  Current/Best:   19.16/  20.89 GFLOPS | Progress: (8/20) | 10.54 s     [Task  1/25]  Current/Best:    5.68/  20.89 GFLOPS | Progress: (12/20) | 14.31 s     [Task  1/25]  Current/Best:   20.90/  20.90 GFLOPS | Progress: (16/20) | 16.44 s     [Task  1/25]  Current/Best:   10.59/  20.90 GFLOPS | Progress: (20/20) | 18.77 s Done.
-     [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  2/25]  Current/Best:    5.81/  23.49 GFLOPS | Progress: (4/20) | 4.08 s     [Task  2/25]  Current/Best:   13.81/  23.49 GFLOPS | Progress: (8/20) | 5.65 s     [Task  2/25]  Current/Best:   11.19/  23.49 GFLOPS | Progress: (12/20) | 7.12 s     [Task  2/25]  Current/Best:   19.84/  23.49 GFLOPS | Progress: (16/20) | 8.79 s     [Task  2/25]  Current/Best:   17.10/  23.49 GFLOPS | Progress: (20/20) | 10.38 s Done.
-     [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  3/25]  Current/Best:   22.97/  22.97 GFLOPS | Progress: (4/20) | 4.72 s     [Task  3/25]  Current/Best:   12.90/  22.97 GFLOPS | Progress: (8/20) | 8.80 s     [Task  3/25]  Current/Best:   23.40/  23.40 GFLOPS | Progress: (12/20) | 11.11 s     [Task  3/25]  Current/Best:   15.52/  23.40 GFLOPS | Progress: (16/20) | 14.33 s     [Task  3/25]  Current/Best:   21.75/  23.76 GFLOPS | Progress: (20/20) | 16.04 s Done.
-     [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  4/25]  Current/Best:    3.50/  21.87 GFLOPS | Progress: (4/20) | 7.69 s     [Task  4/25]  Current/Best:   10.55/  21.87 GFLOPS | Progress: (8/20) | 9.92 s     [Task  4/25]  Current/Best:   15.13/  21.87 GFLOPS | Progress: (12/20) | 17.32 s     [Task  4/25]  Current/Best:   11.17/  21.87 GFLOPS | Progress: (16/20) | 19.40 s     [Task  4/25]  Current/Best:   12.55/  21.87 GFLOPS | Progress: (20/20) | 21.50 s Done.
-     [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  5/25]  Current/Best:    5.84/  15.89 GFLOPS | Progress: (4/20) | 4.64 s     [Task  5/25]  Current/Best:    9.05/  15.89 GFLOPS | Progress: (8/20) | 6.54 s     [Task  5/25]  Current/Best:    5.38/  21.32 GFLOPS | Progress: (12/20) | 8.52 s     [Task  5/25]  Current/Best:   19.69/  21.32 GFLOPS | Progress: (16/20) | 10.98 s     [Task  5/25]  Current/Best:   11.11/  21.32 GFLOPS | Progress: (20/20) | 13.19 s Done.
-     [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  6/25]  Current/Best:   15.50/  15.50 GFLOPS | Progress: (4/20) | 5.72 s     [Task  6/25]  Current/Best:   13.81/  23.42 GFLOPS | Progress: (8/20) | 8.52 s     [Task  6/25]  Current/Best:    4.88/  23.42 GFLOPS | Progress: (12/20) | 10.83 s     [Task  6/25]  Current/Best:   13.85/  23.42 GFLOPS | Progress: (16/20) | 14.21 s     [Task  6/25]  Current/Best:   13.91/  23.42 GFLOPS | Progress: (20/20) | 16.69 s Done.
-     [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  7/25]  Current/Best:   17.30/  18.84 GFLOPS | Progress: (4/20) | 4.68 s     [Task  7/25]  Current/Best:   12.22/  20.44 GFLOPS | Progress: (8/20) | 7.39 s     [Task  7/25]  Current/Best:   18.39/  20.44 GFLOPS | Progress: (12/20) | 9.49 s     [Task  7/25]  Current/Best:    5.37/  20.44 GFLOPS | Progress: (16/20) | 12.72 s     [Task  7/25]  Current/Best:   10.28/  20.44 GFLOPS | Progress: (20/20) | 15.74 s Done.
-     [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  8/25]  Current/Best:    3.95/  18.06 GFLOPS | Progress: (4/20) | 5.70 s     [Task  8/25]  Current/Best:    6.13/  18.06 GFLOPS | Progress: (8/20) | 17.32 s     [Task  8/25]  Current/Best:   16.64/  18.06 GFLOPS | Progress: (12/20) | 20.86 s     [Task  8/25]  Current/Best:   13.80/  18.06 GFLOPS | Progress: (16/20) | 23.57 s     [Task  8/25]  Current/Best:   21.90/  21.90 GFLOPS | Progress: (20/20) | 26.38 s     [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  9/25]  Current/Best:   17.69/  17.69 GFLOPS | Progress: (4/20) | 5.81 s     [Task  9/25]  Current/Best:   19.84/  19.84 GFLOPS | Progress: (8/20) | 15.98 s     [Task  9/25]  Current/Best:   11.88/  21.77 GFLOPS | Progress: (12/20) | 22.97 s     [Task  9/25]  Current/Best:   17.39/  21.77 GFLOPS | Progress: (16/20) | 30.15 s     [Task  9/25]  Current/Best:   12.82/  21.77 GFLOPS | Progress: (20/
 20) | 34.56 s Done.
-     [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 10/25]  Current/Best:   14.85/  16.74 GFLOPS | Progress: (4/20) | 4.51 s     [Task 10/25]  Current/Best:   10.77/  16.74 GFLOPS | Progress: (8/20) | 6.33 s     [Task 10/25]  Current/Best:   16.15/  16.74 GFLOPS | Progress: (12/20) | 8.43 s     [Task 10/25]  Current/Best:   10.58/  21.53 GFLOPS | Progress: (16/20) | 10.31 s     [Task 10/25]  Current/Best:   14.59/  21.53 GFLOPS | Progress: (20/20) | 12.14 s Done.
-     [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 11/25]  Current/Best:   16.03/  21.79 GFLOPS | Progress: (4/20) | 4.56 s     [Task 11/25]  Current/Best:   21.13/  21.79 GFLOPS | Progress: (8/20) | 6.86 s     [Task 11/25]  Current/Best:   12.74/  21.79 GFLOPS | Progress: (12/20) | 8.97 s     [Task 11/25]  Current/Best:   14.78/  24.61 GFLOPS | Progress: (16/20) | 11.12 s     [Task 11/25]  Current/Best:   12.59/  24.61 GFLOPS | Progress: (20/20) | 13.70 s Done.
-     [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 12/25]  Current/Best:   10.35/  11.71 GFLOPS | Progress: (4/20) | 6.60 s     [Task 12/25]  Current/Best:    4.25/  15.87 GFLOPS | Progress: (8/20) | 11.93 s     [Task 12/25]  Current/Best:    6.17/  17.43 GFLOPS | Progress: (12/20) | 17.78 s     [Task 12/25]  Current/Best:   17.18/  22.02 GFLOPS | Progress: (16/20) | 19.64 s     [Task 12/25]  Current/Best:   21.41/  22.02 GFLOPS | Progress: (20/20) | 25.01 s Done.
-     [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 13/25]  Current/Best:    9.27/  14.87 GFLOPS | Progress: (4/20) | 5.98 s     [Task 13/25]  Current/Best:   21.09/  23.91 GFLOPS | Progress: (8/20) | 8.91 s     [Task 13/25]  Current/Best:   11.84/  23.91 GFLOPS | Progress: (12/20) | 13.33 s     [Task 13/25]  Current/Best:   12.39/  23.91 GFLOPS | Progress: (16/20) | 17.02 s     [Task 13/25]  Current/Best:   21.24/  23.91 GFLOPS | Progress: (20/20) | 20.65 s Done.
-     [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 14/25]  Current/Best:   10.47/  14.45 GFLOPS | Progress: (4/20) | 9.74 s     [Task 14/25]  Current/Best:   10.40/  18.19 GFLOPS | Progress: (8/20) | 16.91 s     [Task 14/25]  Current/Best:   13.13/  18.19 GFLOPS | Progress: (12/20) | 20.74 s     [Task 14/25]  Current/Best:   17.35/  18.19 GFLOPS | Progress: (16/20) | 27.78 s     [Task 14/25]  Current/Best:    7.13/  18.79 GFLOPS | Progress: (20/20) | 30.44 s Done.
-     [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 15/25]  Current/Best:    7.23/  18.83 GFLOPS | Progress: (4/20) | 5.07 s     [Task 15/25]  Current/Best:   17.59/  20.01 GFLOPS | Progress: (8/20) | 6.93 s     [Task 15/25]  Current/Best:   10.95/  20.01 GFLOPS | Progress: (12/20) | 9.13 s     [Task 15/25]  Current/Best:    8.59/  20.01 GFLOPS | Progress: (16/20) | 17.37 s     [Task 15/25]  Current/Best:   13.84/  22.14 GFLOPS | Progress: (20/20) | 22.13 s Done.
-     [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 16/25]  Current/Best:   17.94/  19.21 GFLOPS | Progress: (4/20) | 4.26 s     [Task 16/25]  Current/Best:   13.32/  19.21 GFLOPS | Progress: (8/20) | 6.13 s     [Task 16/25]  Current/Best:   11.27/  19.64 GFLOPS | Progress: (12/20) | 8.18 s     [Task 16/25]  Current/Best:    8.35/  20.51 GFLOPS | Progress: (16/20) | 10.96 s     [Task 16/25]  Current/Best:   12.10/  21.50 GFLOPS | Progress: (20/20) | 13.46 s Done.
-     [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 17/25]  Current/Best:   12.27/  23.24 GFLOPS | Progress: (4/20) | 5.11 s     [Task 17/25]  Current/Best:    6.14/  24.31 GFLOPS | Progress: (8/20) | 7.65 s     [Task 17/25]  Current/Best:   20.69/  24.31 GFLOPS | Progress: (12/20) | 9.96 s     [Task 17/25]  Current/Best:   10.34/  24.31 GFLOPS | Progress: (16/20) | 12.25 s     [Task 17/25]  Current/Best:   12.68/  24.31 GFLOPS | Progress: (20/20) | 15.94 s Done.
-     [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 18/25]  Current/Best:   11.68/  14.48 GFLOPS | Progress: (4/20) | 6.45 s     [Task 18/25]  Current/Best:   15.52/  15.72 GFLOPS | Progress: (8/20) | 9.37 s     [Task 18/25]  Current/Best:    9.43/  18.21 GFLOPS | Progress: (12/20) | 15.43 s     [Task 18/25]  Current/Best:   21.58/  21.58 GFLOPS | Progress: (16/20) | 21.63 s     [Task 18/25]  Current/Best:   11.36/  21.58 GFLOPS | Progress: (20/20) | 25.04 s Done.
-     [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 19/25]  Current/Best:   19.01/  20.94 GFLOPS | Progress: (4/20) | 5.65 s     [Task 19/25]  Current/Best:   11.05/  20.94 GFLOPS | Progress: (8/20) | 9.41 s     [Task 19/25]  Current/Best:   18.01/  22.06 GFLOPS | Progress: (12/20) | 13.48 s     [Task 19/25]  Current/Best:    2.79/  22.84 GFLOPS | Progress: (16/20) | 16.57 s     [Task 19/25]  Current/Best:    9.30/  22.84 GFLOPS | Progress: (20/20) | 20.77 s Done.
-     [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 20/25]  Current/Best:   15.95/  16.62 GFLOPS | Progress: (4/20) | 15.09 s     [Task 20/25]  Current/Best:   10.70/  18.91 GFLOPS | Progress: (8/20) | 18.79 s     [Task 20/25]  Current/Best:   14.26/  18.91 GFLOPS | Progress: (12/20) | 30.28 s Done.
-     [Task 20/25]  Current/Best:    9.38/  19.40 GFLOPS | Progress: (16/20) | 36.86 s     [Task 20/25]  Current/Best:   13.30/  22.95 GFLOPS | Progress: (20/20) | 38.76 s Done.
-     [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 21/25]  Current/Best:   17.73/  17.73 GFLOPS | Progress: (4/20) | 4.83 s     [Task 21/25]  Current/Best:   18.40/  18.40 GFLOPS | Progress: (8/20) | 7.17 s     [Task 21/25]  Current/Best:    2.83/  18.40 GFLOPS | Progress: (12/20) | 18.55 s     [Task 21/25]  Current/Best:    9.20/  22.26 GFLOPS | Progress: (16/20) | 21.98 s     [Task 21/25]  Current/Best:   18.03/  22.26 GFLOPS | Progress: (20/20) | 26.15 s     [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 22/25]  Current/Best:   11.68/  17.67 GFLOPS | Progress: (4/20) | 13.57 s     [Task 22/25]  Current/Best:    5.41/  20.08 GFLOPS | Progress: (8/20) | 16.31 s     [Task 22/25]  Current/Best:    8.08/  20.08 GFLOPS | Progress: (12/20) | 19.23 s     [Task 22/25]  Current/Best:   17.72/  21.80 GFLOPS | Progress: (16/20) | 21.07 s     [Task 22/25]  Current/Best:    2.79/  21.80 GFLOPS | Progress: (20/
 20) | 23.29 s     [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 23/25]  Current/Best:    6.37/  23.25 GFLOPS | Progress: (4/20) | 4.65 s     [Task 23/25]  Current/Best:   21.41/  23.25 GFLOPS | Progress: (8/20) | 7.14 s     [Task 23/25]  Current/Best:    6.36/  23.25 GFLOPS | Progress: (12/20) | 10.52 s     [Task 23/25]  Current/Best:   13.81/  23.25 GFLOPS | Progress: (16/20) | 16.02 s     [Task 23/25]  Current/Best:    2.78/  23.25 GFLOPS | Progress: (20/20) | 23.02 s Done.
-     [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 24/25]  Current/Best:    2.59/   7.73 GFLOPS | Progress: (4/20) | 4.47 s     [Task 24/25]  Current/Best:    5.25/   7.73 GFLOPS | Progress: (8/20) | 15.45 s     [Task 24/25]  Current/Best:    5.14/  10.15 GFLOPS | Progress: (12/20) | 26.39 s     [Task 24/25]  Current/Best:    1.80/  10.15 GFLOPS | Progress: (16/20) | 29.47 s     [Task 24/25]  Current/Best:    3.68/  10.15 GFLOPS | Progress: (20/20) | 40.50 s     [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
+     [Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  1/25]  Current/Best:   10.90/  23.66 GFLOPS | Progress: (4/20) | 8.78 s     [Task  1/25]  Current/Best:   21.73/  23.66 GFLOPS | Progress: (8/20) | 11.43 s     [Task  1/25]  Current/Best:   12.82/  23.66 GFLOPS | Progress: (12/20) | 15.50 s     [Task  1/25]  Current/Best:   15.10/  23.66 GFLOPS | Progress: (16/20) | 17.96 s     [Task  1/25]  Current/Best:    5.71/  23.66 GFLOPS | Progress: (20/20) | 21.86 s Done.
+     [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  2/25]  Current/Best:   11.86/  20.47 GFLOPS | Progress: (4/20) | 4.25 s     [Task  2/25]  Current/Best:   15.40/  20.47 GFLOPS | Progress: (8/20) | 6.82 s     [Task  2/25]  Current/Best:   11.84/  20.47 GFLOPS | Progress: (12/20) | 8.67 s     [Task  2/25]  Current/Best:    5.81/  20.47 GFLOPS | Progress: (16/20) | 10.00 s     [Task  2/25]  Current/Best:    5.36/  20.47 GFLOPS | Progress: (20/20) | 11.89 s Done.
+     [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  3/25]  Current/Best:   12.47/  22.07 GFLOPS | Progress: (4/20) | 4.70 s     [Task  3/25]  Current/Best:   15.30/  22.07 GFLOPS | Progress: (8/20) | 7.05 s     [Task  3/25]  Current/Best:   17.36/  22.07 GFLOPS | Progress: (12/20) | 9.82 s     [Task  3/25]  Current/Best:   22.27/  22.27 GFLOPS | Progress: (16/20) | 11.91 s     [Task  3/25]  Current/Best:   12.80/  22.27 GFLOPS | Progress: (20/20) | 14.62 s Done.
+     [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  4/25]  Current/Best:   13.64/  17.95 GFLOPS | Progress: (4/20) | 5.53 s     [Task  4/25]  Current/Best:    3.33/  17.95 GFLOPS | Progress: (8/20) | 7.90 s     [Task  4/25]  Current/Best:   17.92/  17.95 GFLOPS | Progress: (12/20) | 9.81 s     [Task  4/25]  Current/Best:   10.61/  17.95 GFLOPS | Progress: (16/20) | 12.01 s     [Task  4/25]  Current/Best:   20.15/  20.15 GFLOPS | Progress: (20/20) | 14.27 s Done.
+     [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  5/25]  Current/Best:   19.74/  20.36 GFLOPS | Progress: (4/20) | 4.62 s     [Task  5/25]  Current/Best:   12.50/  20.36 GFLOPS | Progress: (8/20) | 6.95 s     [Task  5/25]  Current/Best:    7.34/  21.98 GFLOPS | Progress: (12/20) | 9.32 s     [Task  5/25]  Current/Best:   17.72/  21.98 GFLOPS | Progress: (16/20) | 11.52 s     [Task  5/25]  Current/Best:   13.62/  21.98 GFLOPS | Progress: (20/20) | 13.47 s Done.
+     [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  6/25]  Current/Best:   17.48/  17.48 GFLOPS | Progress: (4/20) | 4.63 s     [Task  6/25]  Current/Best:   16.57/  17.48 GFLOPS | Progress: (8/20) | 7.09 s     [Task  6/25]  Current/Best:   12.75/  17.48 GFLOPS | Progress: (12/20) | 11.70 s     [Task  6/25]  Current/Best:   10.81/  17.48 GFLOPS | Progress: (16/20) | 14.59 s     [Task  6/25]  Current/Best:    4.09/  17.48 GFLOPS | Progress: (20/20) | 17.87 s Done.
+     [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  7/25]  Current/Best:    4.99/  19.03 GFLOPS | Progress: (4/20) | 4.96 s     [Task  7/25]  Current/Best:   22.37/  22.37 GFLOPS | Progress: (8/20) | 6.90 s     [Task  7/25]  Current/Best:   14.50/  22.37 GFLOPS | Progress: (12/20) | 9.48 s     [Task  7/25]  Current/Best:    9.24/  22.37 GFLOPS | Progress: (16/20) | 12.11 s     [Task  7/25]  Current/Best:    9.22/  22.37 GFLOPS | Progress: (20/20) | 14.64 s Done.
+     [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  8/25]  Current/Best:    3.58/  18.69 GFLOPS | Progress: (4/20) | 7.38 s     [Task  8/25]  Current/Best:    7.50/  18.69 GFLOPS | Progress: (8/20) | 10.09 s     [Task  8/25]  Current/Best:    9.88/  18.69 GFLOPS | Progress: (12/20) | 19.65 s     [Task  8/25]  Current/Best:    8.89/  18.69 GFLOPS | Progress: (16/20) | 23.55 s     [Task  8/25]  Current/Best:   15.36/  18.69 GFLOPS | Progress: (20/20) | 26.10 s Done.
+     [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  9/25]  Current/Best:    6.68/  19.86 GFLOPS | Progress: (4/20) | 4.40 s     [Task  9/25]  Current/Best:    8.80/  19.86 GFLOPS | Progress: (8/20) | 10.39 s     [Task  9/25]  Current/Best:    7.55/  19.86 GFLOPS | Progress: (12/20) | 15.29 s     [Task  9/25]  Current/Best:   10.42/  19.86 GFLOPS | Progress: (16/20) | 26.35 s     [Task  9/25]  Current/Best:    6.87/  19.86 GFLOPS | Progress: (20/20) | 37.32 s     [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 10/25]  Current/Best:   16.92/  16.92 GFLOPS | Progress: (4/20) | 4.42 s     [Task 10/25]  Current/Best:    3.63/  17.43 GFLOPS | Progress: (8/20) | 6.94 s     [Task 10/25]  Current/Best:    3.02/  17.43 GFLOPS | Progress: (12/20) | 9.34 s     [Task 10/25]  Current/Best:    3.07/  17.43 GFLOPS | Progress: (16/20) | 11.88 s     [Task 10/25]  Current/Best:   15.17/  17.43 GFLOPS | Progress: (20/20
 ) | 13.73 s Done.
+     [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 11/25]  Current/Best:   16.36/  19.05 GFLOPS | Progress: (4/20) | 5.29 s     [Task 11/25]  Current/Best:   11.35/  24.06 GFLOPS | Progress: (8/20) | 8.14 s     [Task 11/25]  Current/Best:   11.05/  24.06 GFLOPS | Progress: (12/20) | 11.04 s     [Task 11/25]  Current/Best:   16.13/  24.06 GFLOPS | Progress: (16/20) | 13.22 s     [Task 11/25]  Current/Best:   12.81/  24.06 GFLOPS | Progress: (20/20) | 16.05 s Done.
+     [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 12/25]  Current/Best:   15.87/  18.06 GFLOPS | Progress: (4/20) | 4.86 s     [Task 12/25]  Current/Best:   19.42/  19.42 GFLOPS | Progress: (8/20) | 6.74 s     [Task 12/25]  Current/Best:   17.29/  22.00 GFLOPS | Progress: (12/20) | 8.61 s     [Task 12/25]  Current/Best:    7.87/  22.00 GFLOPS | Progress: (16/20) | 10.94 s     [Task 12/25]  Current/Best:   11.97/  22.00 GFLOPS | Progress: (20/20) | 15.07 s Done.
+     [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 13/25]  Current/Best:   19.69/  21.72 GFLOPS | Progress: (4/20) | 4.52 s     [Task 13/25]  Current/Best:   11.15/  21.72 GFLOPS | Progress: (8/20) | 8.41 s     [Task 13/25]  Current/Best:   17.49/  21.72 GFLOPS | Progress: (12/20) | 10.77 s     [Task 13/25]  Current/Best:    5.14/  21.72 GFLOPS | Progress: (16/20) | 14.52 s     [Task 13/25]  Current/Best:    9.79/  21.72 GFLOPS | Progress: (20/20) | 18.43 s Done.
+     [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 14/25]  Current/Best:   14.73/  18.33 GFLOPS | Progress: (4/20) | 9.19 s     [Task 14/25]  Current/Best:   13.03/  18.33 GFLOPS | Progress: (8/20) | 13.06 s     [Task 14/25]  Current/Best:    7.18/  18.33 GFLOPS | Progress: (12/20) | 22.06 s     [Task 14/25]  Current/Best:    4.95/  18.33 GFLOPS | Progress: (16/20) | 27.98 s     [Task 14/25]  Current/Best:    5.23/  18.33 GFLOPS | Progress: (20/20) | 34.37 s Done.
+     [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 15/25]  Current/Best:    7.63/  15.27 GFLOPS | Progress: (4/20) | 10.44 s     [Task 15/25]  Current/Best:   22.17/  22.59 GFLOPS | Progress: (8/20) | 11.94 s     [Task 15/25]  Current/Best:    5.24/  22.59 GFLOPS | Progress: (12/20) | 13.79 s     [Task 15/25]  Current/Best:   11.02/  22.59 GFLOPS | Progress: (16/20) | 21.82 s     [Task 15/25]  Current/Best:    4.79/  22.59 GFLOPS | Progress: (20/20) | 30.75 s Done.
+     [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 16/25]  Current/Best:    8.33/  21.26 GFLOPS | Progress: (4/20) | 4.28 s     [Task 16/25]  Current/Best:    9.35/  21.26 GFLOPS | Progress: (8/20) | 7.50 s     [Task 16/25]  Current/Best:   15.95/  21.26 GFLOPS | Progress: (12/20) | 9.59 s     [Task 16/25]  Current/Best:    9.34/  21.26 GFLOPS | Progress: (16/20) | 12.30 s     [Task 16/25]  Current/Best:   18.56/  21.26 GFLOPS | Progress: (20/20) | 14.44 s Done.
+     [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 17/25]  Current/Best:   19.32/  19.32 GFLOPS | Progress: (4/20) | 4.99 s     [Task 17/25]  Current/Best:    9.88/  19.85 GFLOPS | Progress: (8/20) | 7.50 s     [Task 17/25]  Current/Best:   10.80/  19.85 GFLOPS | Progress: (12/20) | 11.26 s     [Task 17/25]  Current/Best:   21.93/  22.56 GFLOPS | Progress: (16/20) | 13.26 s     [Task 17/25]  Current/Best:    9.84/  23.17 GFLOPS | Progress: (20/20) | 15.57 s Done.
+     [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 18/25]  Current/Best:    5.77/  17.03 GFLOPS | Progress: (4/20) | 6.64 s     [Task 18/25]  Current/Best:   12.53/  19.25 GFLOPS | Progress: (8/20) | 11.30 s     [Task 18/25]  Current/Best:    6.69/  20.40 GFLOPS | Progress: (12/20) | 13.58 s     [Task 18/25]  Current/Best:   14.03/  21.91 GFLOPS | Progress: (16/20) | 21.40 s     [Task 18/25]  Current/Best:   14.70/  21.91 GFLOPS | Progress: (20/20) | 23.41 s Done.
+     [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 19/25]  Current/Best:    3.09/  21.43 GFLOPS | Progress: (4/20) | 6.61 s     [Task 19/25]  Current/Best:    1.55/  21.65 GFLOPS | Progress: (8/20) | 11.42 s     [Task 19/25]  Current/Best:    2.69/  21.65 GFLOPS | Progress: (12/20) | 14.97 s     [Task 19/25]  Current/Best:   19.11/  21.65 GFLOPS | Progress: (16/20) | 19.98 s     [Task 19/25]  Current/Best:   17.07/  21.65 GFLOPS | Progress: (20/20) | 24.24 s Done.
+     [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 20/25]  Current/Best:    4.76/  21.55 GFLOPS | Progress: (4/20) | 14.38 s     [Task 20/25]  Current/Best:   19.24/  22.63 GFLOPS | Progress: (8/20) | 21.71 s     [Task 20/25]  Current/Best:    9.62/  22.63 GFLOPS | Progress: (12/20) | 26.88 s     [Task 20/25]  Current/Best:   17.42/  22.63 GFLOPS | Progress: (16/20) | 29.33 s     [Task 20/25]  Current/Best:   10.59/  22.63 GFLOPS | Progress: (20/20) | 37.25 s     [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
      Done.
-     Done.
-     [Task 25/25]  Current/Best:    9.42/  10.14 GFLOPS | Progress: (4/20) | 5.71 s     [Task 25/25]  Current/Best:    3.14/  10.14 GFLOPS | Progress: (8/20) | 8.68 s     [Task 25/25]  Current/Best:    4.49/  10.23 GFLOPS | Progress: (12/20) | 12.31 s     [Task 25/25]  Current/Best:    1.60/  10.23 GFLOPS | Progress: (16/20) | 15.37 s     [Task 25/25]  Current/Best:    5.51/  10.23 GFLOPS | Progress: (20/20) | 26.31 s
+     [Task 21/25]  Current/Best:   13.41/  13.41 GFLOPS | Progress: (4/20) | 12.24 s     [Task 21/25]  Current/Best:    7.28/  13.41 GFLOPS | Progress: (8/20) | 18.73 s     [Task 21/25]  Current/Best:    4.71/  16.21 GFLOPS | Progress: (12/20) | 30.14 s     [Task 21/25]  Current/Best:    3.77/  16.21 GFLOPS | Progress: (16/20) | 32.38 s     [Task 21/25]  Current/Best:    8.47/  16.21 GFLOPS | Progress: (20/20) | 34.61 s Done.
+     [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 22/25]  Current/Best:   19.65/  21.74 GFLOPS | Progress: (4/20) | 5.62 s     [Task 22/25]  Current/Best:    7.67/  21.74 GFLOPS | Progress: (8/20) | 8.34 s     [Task 22/25]  Current/Best:   11.71/  21.74 GFLOPS | Progress: (12/20) | 10.74 s     [Task 22/25]  Current/Best:    5.22/  21.74 GFLOPS | Progress: (16/20) | 14.06 s     [Task 22/25]  Current/Best:   18.73/  21.74 GFLOPS | Progress: (20/20) | 15.75 s Done.
+     [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 23/25]  Current/Best:   17.77/  19.48 GFLOPS | Progress: (4/20) | 7.99 s     [Task 23/25]  Current/Best:   11.48/  22.55 GFLOPS | Progress: (8/20) | 11.78 s     [Task 23/25]  Current/Best:   10.66/  22.55 GFLOPS | Progress: (12/20) | 14.29 s     [Task 23/25]  Current/Best:    7.14/  22.55 GFLOPS | Progress: (16/20) | 19.84 s     [Task 23/25]  Current/Best:    6.19/  22.55 GFLOPS | Progress: (20/20) | 22.68 s Done.
+     [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 24/25]  Current/Best:    5.89/   9.59 GFLOPS | Progress: (4/20) | 6.70 s     [Task 24/25]  Current/Best:    1.83/   9.59 GFLOPS | Progress: (8/20) | 17.70 s     [Task 24/25]  Current/Best:    3.02/   9.59 GFLOPS | Progress: (12/20) | 28.74 s     [Task 24/25]  Current/Best:    7.37/   9.59 GFLOPS | Progress: (16/20) | 31.32 s     [Task 24/25]  Current/Best:    2.87/   9.59 GFLOPS | Progress: (20/20) | 42.32 s     [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 25/25]  Current/Best:    6.61/   6.61 GFLOPS | Progress: (4/20) | 10.61 s     [Task 25/25]  Current/Best:    8.73/   8.73 GFLOPS | Progress: (8/20) | 12.07 s     [Task 25/25]  Current/Best:    4.06/   8.83 GFLOPS | Progress: (12/20) | 14.39 s     [Task 25/25]  Current/Best:    4.36/   8.83 GFLOPS | Progress: (16/20) | 19.42 s     [Task 25/25]  Current/Best:    1.50/   9.37 GFLOPS | Progress: (20
 /20) | 21.50 s Done.
+
 
 
 
@@ -766,8 +766,8 @@ improvement in comparing the optimized model to the unoptimized model.
 
  .. code-block:: none
 
-    optimized: {'mean': 381.63107256998046, 'median': 380.9882759500397, 'std': 1.7423971195174}
-    unoptimized: {'mean': 472.81652373001634, 'median': 473.12350920001336, 'std': 2.307640356318348}
+    optimized: {'mean': 420.20613707998564, 'median': 419.5116467000844, 'std': 3.1023702175735526}
+    unoptimized: {'mean': 491.0514597600195, 'median': 490.92375170002924, 'std': 1.5121823348393049}
 
 
 
@@ -790,7 +790,7 @@ profiling/benchmarking.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 13 minutes  15.681 seconds)
+   **Total running time of the script:** ( 13 minutes  27.631 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 5dd5c289be..60aadf49d7 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
 
-    1.143e-07 secs/op
+    1.21e-07 secs/op
 
 
 
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index 16e2e0784b..148f3bb00d 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, 0x1311d6e0)), stage(b, placeholder(b, 0x130ed5d0)), 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, 0x11bfa320)), stage(b, placeholder(b, 0x117f34f0)), 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 6d422408d1..538282d388 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,31 +5,31 @@
 
 Computation times
 =================
-**16:47.420** total execution time for **tutorial** files:
+**17:16.815** total execution time for **tutorial** files:
 
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 13:15.681 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 13:27.631 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:25.286 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:41.544 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 00:57.866 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 01:00.327 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:42.087 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:43.769 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:24.609 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:21.185 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.864 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:01.271 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:00.859 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.905 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.170 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.182 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_uma.py` (``uma.py``)                                             | 00:00.000 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)   | 00:00.000 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)                             | 00:00.000 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)   | 00:00.000 | 0.0 MB |
++------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``)                           | 00:00.000 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_install.py` (``install.py``)                                     | 00:00.000 | 0.0 MB |
diff --git a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
index 351bd917e6..853248f2b6 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -285,8 +285,8 @@ helper function to run a profile of the TVM generated code.
 
  .. code-block:: none
 
-    Numpy running time: 0.000008
-    naive: 0.000007
+    Numpy running time: 0.000007
+    naive: 0.000008
 
 
 
@@ -444,7 +444,7 @@ factor to be the number of threads on your CPU.
 
  .. code-block:: none
 
-    vector: 0.000040
+    vector: 0.000043
     # 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    7.6211700070416555e-06                   1.0
-                   naive              6.7833e-06      0.8900601867866093
-                parallel              6.9884e-06      0.9169720651216281
-                  vector    3.979460000000001e-05      5.221586706927072
+                   numpy    6.810990016674623e-06                    1.0
+                   naive              7.8756e-06      1.1563076705029673
+                parallel    7.0258000000000006e-06    1.0315387311975912
+                  vector    4.2536899999999996e-05     6.245332895197531
 
 
 
@@ -922,7 +922,7 @@ matrix multiplication.
 
  .. code-block:: none
 
-    Numpy running time: 0.016847
+    Numpy running time: 0.017763
 
 
 
@@ -980,7 +980,7 @@ optimizations.
 
  .. code-block:: none
 
-    none: 3.256538
+    none: 3.431128
 
 
 
@@ -1080,7 +1080,7 @@ schedule.
 
  .. code-block:: none
 
-    blocking: 0.327842
+    blocking: 0.291657
 
 
 
@@ -1164,7 +1164,7 @@ already cache friendly from our previous optimizations.
 
  .. code-block:: none
 
-    vectorization: 0.261305
+    vectorization: 0.273722
     # 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: 0.110385
+    loop permutation: 0.115916
     # 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: 0.104061
+    array packing: 0.107565
     # 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: 0.107764
+    block caching: 0.113049
     # 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: 0.127950
+    parallelization: 0.133392
     # 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             3.256538284                     1.0
-                blocking            0.3278417958     0.10067186908587868
-           vectorization            0.2613052621     0.08024019351587024
-        loop permutation            0.1103850672       0.033896443884091
-           array packing     0.10406077660000002    0.031954415248630935
-           block caching     0.10776395889999998    0.033091568254997976
-         parallelization            0.1279501574    0.039290235901307764
+                    none      3.4311277783999996                     1.0
+                blocking            0.2916568338     0.08500319796775542
+           vectorization            0.2737218407     0.07977605568150589
+        loop permutation     0.11591623649999998     0.03378371310731364
+           array packing            0.1075645505    0.031349619555748345
+           block caching            0.1130494898     0.03294820161221659
+         parallelization            0.1333924645     0.03887714859812171
 
 
 
@@ -1594,6 +1594,11 @@ operations with tunable parameters that allows you to automatically optimize
 the computation for specific platforms.
 
 
+.. rst-class:: sphx-glr-timing
+
+   **Total running time of the script:** ( 1 minutes  0.327 seconds)
+
+
 .. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
 
 .. only:: html
diff --git a/docs/commit_hash b/docs/commit_hash
index d7c1f3e1ba..761e5b04f1 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-89e9028849ae3803a10eda086434c8d9e3bc3298
+0f38ef2d6e6ecb7d1b8e164582f417b15b8f4e9a
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index eebadaabb3..062fa7e548 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -604,7 +604,7 @@ class:[&#39;truck 0.9266&#39;] left:471 top:83 right:689 bottom:169
 class:[&#39;bicycle 0.9984&#39;] left:111 top:113 right:577 bottom:447
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  31.046 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  35.180 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-darknet-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/7716f96385bd5abb6e822041e285be54/from_darknet.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_darknet.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index 9b3f05afea..a02a2c0d31 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -468,15 +468,13 @@ 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
 
   0%|          | 0.00/41.5M [00:00&lt;?, ?B/s]
-  3%|2         | 1.20M/41.5M [00:00&lt;00:03, 12.5MB/s]
- 17%|#6        | 6.86M/41.5M [00:00&lt;00:00, 40.1MB/s]
- 26%|##5       | 10.7M/41.5M [00:00&lt;00:00, 39.8MB/s]
- 39%|###8      | 16.0M/41.5M [00:00&lt;00:00, 34.9MB/s]
- 54%|#####3    | 22.3M/41.5M [00:00&lt;00:00, 41.4MB/s]
- 64%|######3   | 26.4M/41.5M [00:00&lt;00:00, 38.6MB/s]
- 77%|#######7  | 32.0M/41.5M [00:00&lt;00:00, 40.8MB/s]
- 92%|#########2| 38.3M/41.5M [00:01&lt;00:00, 41.3MB/s]
-100%|##########| 41.5M/41.5M [00:01&lt;00:00, 40.2MB/s]
+ 15%|#5        | 6.33M/41.5M [00:00&lt;00:02, 16.8MB/s]
+ 35%|###4      | 14.3M/41.5M [00:00&lt;00:01, 24.4MB/s]
+ 41%|####      | 16.8M/41.5M [00:00&lt;00:01, 24.0MB/s]
+ 58%|#####7    | 24.0M/41.5M [00:00&lt;00:00, 28.3MB/s]
+ 84%|########4 | 35.0M/41.5M [00:01&lt;00:00, 46.0MB/s]
+ 98%|#########8| 40.7M/41.5M [00:01&lt;00:00, 36.7MB/s]
+100%|##########| 41.5M/41.5M [00:01&lt;00:00, 32.6MB/s]
 </pre></div>
 </div>
 </div>
diff --git a/docs/how_to/compile_models/from_paddle.html b/docs/how_to/compile_models/from_paddle.html
index 12b26b40e5..bd9edb2cc6 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -503,6 +503,7 @@ 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  2.114 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 95258ea7ab..0395db3fa4 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -451,13 +451,14 @@ 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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- 36%|###5      | 16.0M/44.7M [00:00&lt;00:00, 58.2MB/s]
- 54%|#####3    | 24.0M/44.7M [00:00&lt;00:00, 63.0MB/s]
- 68%|######7   | 30.3M/44.7M [00:00&lt;00:00, 58.9MB/s]
- 81%|########  | 36.1M/44.7M [00:00&lt;00:00, 57.2MB/s]
- 93%|#########3| 41.6M/44.7M [00:00&lt;00:00, 47.4MB/s]
-100%|##########| 44.7M/44.7M [00:00&lt;00:00, 55.6MB/s]
+ 18%|#7        | 7.99M/44.7M [00:00&lt;00:00, 43.5MB/s]
+ 32%|###2      | 14.3M/44.7M [00:00&lt;00:00, 34.8MB/s]
+ 40%|###9      | 17.7M/44.7M [00:00&lt;00:00, 33.0MB/s]
+ 54%|#####3    | 24.0M/44.7M [00:00&lt;00:00, 35.7MB/s]
+ 72%|#######1  | 32.0M/44.7M [00:00&lt;00:00, 40.5MB/s]
+ 86%|########5 | 38.3M/44.7M [00:01&lt;00:00, 42.3MB/s]
+ 96%|#########6| 43.1M/44.7M [00:01&lt;00:00, 44.1MB/s]
+100%|##########| 44.7M/44.7M [00:01&lt;00:00, 41.7MB/s]
 </pre></div>
 </div>
 </div>
diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index 0edc70d2a1..e1c1d76eb0 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -671,7 +671,7 @@ banana (score = 0.00022)
 desk (score = 0.00019)
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 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-tensorflow-py">
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 <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 8123e4b688..2b13a635cb 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>06:26.266</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
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 <tr class="row-odd"><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>
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diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno.html b/docs/how_to/deploy_models/deploy_model_on_adreno.html
index 94ed33fec9..0238da5fac 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)
- 3994.3996    3994.8751    4000.6321    3989.2283      3.2530
+ 4122.0512    4122.1482    4125.6389    4118.9306      2.3064
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  19.772 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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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 a2a58def26..1555e5ad4d 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 +458,23 @@ 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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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 2549579712..ab2087eb21 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)
-  14.2251      14.2108      14.3957      14.1126       0.0912
+  14.8821      14.8402      15.5314      14.5001       0.2710
 </pre></div>
 </div>
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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 7878ecac49..629c9037fc 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -474,35 +474,33 @@ 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).
@@ -593,7 +591,7 @@ 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  26.331 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  35.699 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 28892fc62a..0fd012b612 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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@@ -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)
-  86.0477      85.9436      87.6205      85.5688       0.3207
+  88.8394      88.8050      89.4554      88.5079       0.2201
 </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>
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  29.713 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 24ef4470e1..08b7138dec 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)
-  105.0875     104.9699     107.3328     103.4988      1.0124
+  109.6496     109.6988     113.3938     108.4932      0.7184
 </pre></div>
 </div>
 <div class="admonition note">
diff --git a/docs/how_to/deploy_models/sg_execution_times.html b/docs/how_to/deploy_models/sg_execution_times.html
index ae209b7ad0..edfbc8a407 100644
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+++ 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>09:33.158</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>09:55.551</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 86%" />
@@ -369,35 +369,35 @@
 </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>03:26.331</p></td>
+<td><p>03:35.699</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><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>01:26.199</p></td>
+<td><p>01:29.713</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.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>01:17.224</p></td>
+<td><p>01:19.772</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>00:49.963</p></td>
+<td><p>00:52.021</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>00:49.773</p></td>
+<td><p>00:51.393</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_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>00:45.588</p></td>
+<td><p>00:47.132</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><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>00:29.131</p></td>
+<td><p>00:29.976</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><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>00:28.938</p></td>
+<td><p>00:29.835</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><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/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index ddaaeb4f6e..29d6bb4892 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>00:03.928</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:04.131</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
@@ -369,11 +369,11 @@
 </colgroup>
 <tbody>
 <tr class="row-odd"><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>00:02.737</p></td>
+<td><p>00:02.855</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><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>00:01.184</p></td>
+<td><p>00:01.269</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="low_level_custom_pass.html#sphx-glr-how-to-extend-tvm-low-level-custom-pass-py"><span class="std std-ref">Writing a Customized Pass</span></a> (<code class="docutils literal notranslate"><span class="pre">low_level_custom_pass.py</span></code>)</p></td>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 22e5454da1..867d46de19 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -545,10 +545,10 @@ 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: 25914us [25914us] (49.38%; 49.38%)
-FoldScaleAxis: 26567us [7us] (50.62%; 50.62%)
-        FoldConstant: 26560us [1831us] (50.61%; 99.97%)
-                InferType: 24728us [24728us] (47.12%; 93.10%)
+InferType: 25998us [25998us] (49.24%; 49.24%)
+FoldScaleAxis: 26803us [8us] (50.76%; 50.76%)
+        FoldConstant: 26794us [1892us] (50.75%; 99.97%)
+                InferType: 24902us [24902us] (47.16%; 92.94%)
 </pre></div>
 </div>
 </div>
@@ -570,10 +570,10 @@ 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: 24506us [24506us] (48.76%; 48.76%)
-FoldScaleAxis: 25754us [5us] (51.24%; 51.24%)
-        FoldConstant: 25749us [1662us] (51.23%; 99.98%)
-                InferType: 24087us [24087us] (47.92%; 93.55%)
+InferType: 24890us [24890us] (48.19%; 48.19%)
+FoldScaleAxis: 26755us [8us] (51.81%; 51.81%)
+        FoldConstant: 26747us [1937us] (51.79%; 99.97%)
+                InferType: 24810us [24810us] (48.04%; 92.76%)
 </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 120ec1ae3a..3f1c0ab620 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: 53.526622 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 40.099166 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 faeb937b2b..9cbf083d93 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: 11.137446 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.263565 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 1d4eac8f4b..f08d07edd4 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: 0.017209
-Baseline: 3.249494
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.017778
+Baseline: 3.122380
 </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: 0.281671
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.287623
 </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: 0.262739
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.270746
 </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: 0.111100
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.116796
 </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: 0.102508
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.108060
 </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: 0.110018
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.111517
 </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: 0.127944
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.132610
 </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 61def68d2c..68836a811d 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>00:32.431</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:33.274</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>00:29.489</p></td>
+<td><p>00:30.300</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>00:01.776</p></td>
+<td><p>00:01.832</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>00:01.167</p></td>
+<td><p>00:01.142</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 f13a7cf9e1..8555260f15 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>03:31.821</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>03:40.359</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>01:31.930</p></td>
+<td><p>01:36.236</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>01:11.148</p></td>
+<td><p>01:13.618</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>00:17.243</p></td>
+<td><p>00:17.940</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
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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 7bd1d9d38b..cdfe2a0dcb 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: 0.346 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.341 ms
 </pre></div>
 </div>
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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 b21a84923c..accdbf62e0 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -923,7 +923,7 @@ 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)
-   3.2591       3.2560       3.2657       3.2555       0.0047
+   3.2167       3.2109       3.2293       3.2098       0.0089
 </pre></div>
 </div>
 </div>
@@ -945,7 +945,7 @@ 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>
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 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-cuda-py">
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 <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 340325e45b..cac79cd354 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -945,7 +945,7 @@ 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)
-  730.7174     730.0098     732.2694     729.8730      1.0988
+  803.4541     803.7370     804.5003     802.1249      0.9902
 </pre></div>
 </div>
 </div>
@@ -967,7 +967,7 @@ 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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 <p><a class="reference download internal" download="" href="../../_downloads/e416b94ca1090b0897c0f6e0df95b911/tune_network_x86.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_x86.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autotvm/sg_execution_times.html b/docs/how_to/tune_with_autotvm/sg_execution_times.html
index caa719cfb1..fb4b47e751 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-tune-with-autotvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:23.949</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:23.912</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
 <table class="docutils align-default">
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@@ -369,11 +369,11 @@
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diff --git a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
index f42ab18edb..e4851e195e 100644
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@@ -630,7 +630,7 @@ and measure running time.</p>
 
 Best config:
 ,None
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 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autotvm-tune-conv2d-cuda-py">
diff --git a/docs/how_to/work_with_microtvm/micro_autotune.html b/docs/how_to/work_with_microtvm/micro_autotune.html
index 9b28808c07..791520c301 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -664,10 +664,10 @@ the tuned operator.</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build without Autotuning ##########
 Node Name                                     Ops                                           Time(us)  Time(%)  Shape              Inputs  Outputs  Measurements(us)
 ---------                                     ---                                           --------  -------  -----              ------  -------  ----------------
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-tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.818     0.948    (1, 6, 10, 10)     1       1        [2.818]
-tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.924     0.311    (1, 1, 10, 10, 3)  1       1        [0.924]
-Total_time                                    -                                             297.243   -        -                  -       -        -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  304.4     98.737   (1, 2, 10, 10, 3)  2       1        [304.4]
+tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.919     0.947    (1, 6, 10, 10)     1       1        [2.919]
+tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.976     0.317    (1, 1, 10, 10, 3)  1       1        [0.976]
+Total_time                                    -                                             308.295   -        -                  -       -        -
 </pre></div>
 </div>
 </div>
@@ -719,13 +719,13 @@ Total_time                                    -
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build with Autotuning ##########
 Node Name                                     Ops                                           Time(us)  Time(%)  Shape              Inputs  Outputs  Measurements(us)
 ---------                                     ---                                           --------  -------  -----              ------  -------  ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  108.6     97.626   (1, 6, 10, 10, 1)  2       1        [108.6]
-tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.716     1.543    (1, 6, 10, 10)     1       1        [1.716]
-tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.924     0.831    (1, 1, 10, 10, 3)  1       1        [0.924]
-Total_time                                    -                                             111.24    -        -                  -       -        -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  137.5     98.139   (1, 6, 10, 10, 1)  2       1        [137.5]
+tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.763     1.258    (1, 6, 10, 10)     1       1        [1.763]
+tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.845     0.603    (1, 3, 10, 10, 1)  1       1        [0.845]
+Total_time                                    -                                             140.108   -        -                  -       -        -
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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, 11.6MB/s]
-100%|##########| 3.42M/3.42M [00:00&lt;00:00, 18.5MB/s]
+ 61%|######    | 2.09M/3.42M [00:00&lt;00:00, 14.7MB/s]
+100%|##########| 3.42M/3.42M [00:00&lt;00:00, 23.1MB/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
 Torch top-1 id: 282, class name: tiger cat
 </pre></div>
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diff --git a/docs/how_to/work_with_microtvm/micro_train.html b/docs/how_to/work_with_microtvm/micro_train.html
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--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -543,7 +543,7 @@ take about <strong>2 minutes</strong> to download the Stanford Cars, while COCO
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-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&#39;/tmp/tmp_4hzk1t9/images/random&#39;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&#39;/tmp/tmpuwfq9vao/images/random&#39;
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 </div>
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@@ -603,8 +603,8 @@ objects to other stuff? We can display some examples from our datasets using <co
     <span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">&quot;off&quot;</span><span class="p">)</span>
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-/tmp/tmp_4hzk1t9/images/random contains 5000 images
+<img src="../../_images/sphx_glr_micro_train_001.png" srcset="../../_images/sphx_glr_micro_train_001.png" alt="[1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmpuwfq9vao/images/target contains 8144 images
+/tmp/tmpuwfq9vao/images/random contains 5000 images
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 </div>
@@ -716,13 +716,13 @@ the time on our validation set).</p>
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Epoch 1/3
-328/328 - 39s - loss: 0.2221 - accuracy: 0.9256 - val_loss: 0.1455 - val_accuracy: 0.9471 - 39s/epoch - 119ms/step
+328/328 - 39s - loss: 0.2173 - accuracy: 0.9259 - val_loss: 0.1433 - val_accuracy: 0.9517 - 39s/epoch - 119ms/step
 Epoch 2/3
-328/328 - 34s - loss: 0.1035 - accuracy: 0.9620 - val_loss: 0.1032 - val_accuracy: 0.9619 - 34s/epoch - 104ms/step
+328/328 - 35s - loss: 0.1003 - accuracy: 0.9622 - val_loss: 0.1236 - val_accuracy: 0.9562 - 35s/epoch - 108ms/step
 Epoch 3/3
-328/328 - 35s - loss: 0.0671 - accuracy: 0.9753 - val_loss: 0.0889 - val_accuracy: 0.9705 - 35s/epoch - 105ms/step
+328/328 - 35s - loss: 0.0617 - accuracy: 0.9773 - val_loss: 0.1019 - val_accuracy: 0.9656 - 35s/epoch - 108ms/step
 
-&lt;keras.callbacks.History object at 0x7fbd534f98b0&gt;
+&lt;keras.callbacks.History object at 0x7fbd31f2f730&gt;
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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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diff --git a/docs/how_to/work_with_microtvm/sg_execution_times.html b/docs/how_to/work_with_microtvm/sg_execution_times.html
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   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-work-with-microtvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>08:08.144</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
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 <table class="docutils align-default">
 <colgroup>
 <col style="width: 82%" />
@@ -369,27 +369,27 @@
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 <tr class="row-odd"><td><p><a class="reference internal" href="micro_train.html#sphx-glr-how-to-work-with-microtvm-micro-train-py"><span class="std std-ref">5. Training Vision Models for microTVM on Arduino</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_train.py</span></code>)</p></td>
-<td><p>04:49.621</p></td>
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-<td><p>01:25.883</p></td>
+<td><p>01:29.436</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="micro_autotune.html#sphx-glr-how-to-work-with-microtvm-micro-autotune-py"><span class="std std-ref">6. Model Tuning with microTVM</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_autotune.py</span></code>)</p></td>
-<td><p>01:25.008</p></td>
+<td><p>01:26.088</p></td>
 <td><p>0.0 MB</p></td>
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 <tr class="row-even"><td><p><a class="reference internal" href="micro_aot.html#sphx-glr-how-to-work-with-microtvm-micro-aot-py"><span class="std std-ref">3. microTVM Ahead-of-Time (AOT) Compilation</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_aot.py</span></code>)</p></td>
-<td><p>00:11.695</p></td>
+<td><p>00:12.045</p></td>
 <td><p>0.0 MB</p></td>
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 <tr class="row-odd"><td><p><a class="reference internal" href="micro_custom_ide.html#sphx-glr-how-to-work-with-microtvm-micro-custom-ide-py"><span class="std std-ref">9. Bring microTVM to your own development environment</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_custom_ide.py</span></code>)</p></td>
-<td><p>00:08.658</p></td>
+<td><p>00:08.874</p></td>
 <td><p>0.0 MB</p></td>
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 <tr class="row-even"><td><p><a class="reference internal" href="micro_tflite.html#sphx-glr-how-to-work-with-microtvm-micro-tflite-py"><span class="std std-ref">2. microTVM TFLite Tutorial</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_tflite.py</span></code>)</p></td>
-<td><p>00:07.278</p></td>
+<td><p>00:07.250</p></td>
 <td><p>0.0 MB</p></td>
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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 bd30b76235..400785acd9 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-work-with-relay-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:37.356</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:38.154</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 84%" />
@@ -369,15 +369,15 @@
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-<td><p>00:32.413</p></td>
+<td><p>00:33.186</p></td>
 <td><p>0.0 MB</p></td>
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-<td><p>00:03.066</p></td>
+<td><p>00:03.141</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>00:01.871</p></td>
+<td><p>00:01.820</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 e123eb9b30..8a465ff875 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -572,7 +572,7 @@ The following example customizes CUDA lowering rule for <code class="code docuti
 <a href="../../reference/api/python/ir.html#tvm.ir.register_intrin_lowering" title="tvm.ir.register_intrin_lowering" class="sphx-glr-backref-module-tvm-ir sphx-glr-backref-type-py-function"><span class="n">register_intrin_lowering</span></a><span class="p">(</span><span class="s2">&quot;tir.exp&quot;</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s2">&quot;cuda&quot;</span><span class="p">,</span> <span class="n">f</span><span class="o">= [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;function my_cuda_math_rule at 0x7fbf403949d0&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;function my_cuda_math_rule at 0x7fbf0a996820&gt;
 </pre></div>
 </div>
 <p>Register the rule to TVM with override option to override existing rule.
diff --git a/docs/how_to/work_with_schedules/sg_execution_times.html b/docs/how_to/work_with_schedules/sg_execution_times.html
index a737f52265..1da4a47efa 100644
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+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:05.171</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:05.075</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
@@ -369,35 +369,35 @@
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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>
-<td><p>00:01.031</p></td>
+<td><p>00:00.958</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
-<td><p>00:00.699</p></td>
+<td><p>00:00.701</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>00:00.696</p></td>
+<td><p>00:00.690</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>00:00.121</p></td>
+<td><p>00:00.123</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>00:00.068</p></td>
+<td><p>00:00.070</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>00:00.068</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>00:00.032</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index a4c59bed8b..775bd5a36a 100644
--- a/docs/reference/api/python/auto_scheduler.html
+++ b/docs/reference/api/python/auto_scheduler.html
@@ -1637,7 +1637,7 @@ history states as starting point to perform Evolutionary Search).</p></li>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy">
-<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
+<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
 <dd><p>The search policy that searches in a hierarchical search space defined by sketches.
 The policy randomly samples programs from the space defined by sketches and use evolutionary
 search to fine-tune them.</p>
@@ -1921,7 +1921,7 @@ Candidates:
 
 <dl class="py function">
 <dt class="sig sig-object py" id="tvm.auto_scheduler.auto_schedule">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
 <dd><p>THIS API IS DEPRECATED.</p>
 <p>Run auto scheduling search for a task.</p>
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index c19d21502d..dc0c8f2934 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1005">runtime.ts:1005</a></li></ul></aside></li></ul></section></section>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1025">runtime.ts:1025</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1025">runtime.ts:1025</a></li></ul></aside></li></ul></section>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1046">runtime.ts:1046</a></li></ul></aside></li></ul></section>
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 <p>Implementation of <a href="../interfaces/_internal_.ArtifactCacheTemplate.html">ArtifactCacheTemplate</a>.<a href="../interfaces/_internal_.ArtifactCacheTemplate.html#fetchWithCache">fetchWithCache</a></p>
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1009">runtime.ts:1009</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="hasAllKeys" class="tsd-anchor"></a>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1036">runtime.ts:1036</a></li></ul></aside></li></ul></section></section></div>
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 <h5><span class="tsd-kind-parameter">lanes</span>: <span class="tsd-signature-type">number</span></h5></li></ul></div>
 <h4 class="tsd-returns-title">Returns <a href="DLDataType.html" class="tsd-signature-type tsd-kind-class">DLDataType</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L419">runtime.ts:419</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L419">runtime.ts:419</a></li></ul></aside></li></ul></section></section>
 <section class="tsd-panel-group tsd-member-group">
 <h2>Properties</h2>
 <section class="tsd-panel tsd-member"><a id="bits" class="tsd-anchor"></a>
@@ -71,21 +71,21 @@
 <div class="tsd-comment tsd-typography"><p>Number of bits in the data type.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L415">runtime.ts:415</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L415">runtime.ts:415</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="code" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>code</span><a href="#code" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">code</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
 <div class="tsd-comment tsd-typography"><p>The type code</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L413">runtime.ts:413</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L413">runtime.ts:413</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="lanes" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>lanes</span><a href="#lanes" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">lanes</span><span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span></div>
 <div class="tsd-comment tsd-typography"><p>Number of vector lanes.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L417">runtime.ts:417</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L417">runtime.ts:417</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
 <h2>Methods</h2>
 <section class="tsd-panel tsd-member"><a id="numStorageBytes" class="tsd-anchor"></a>
@@ -95,7 +95,7 @@
 <li class="tsd-description">
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L434">runtime.ts:434</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L434">runtime.ts:434</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">
@@ -103,7 +103,7 @@
 <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/89e902884/web/src/runtime.ts#L425">runtime.ts:425</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L425">runtime.ts:425</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
 <div class="page-menu">
 <div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/DLDevice.html b/docs/reference/api/typedoc/classes/DLDevice.html
index c1a14e71c1..b975845eb0 100644
--- a/docs/reference/api/typedoc/classes/DLDevice.html
+++ b/docs/reference/api/typedoc/classes/DLDevice.html
@@ -23,7 +23,7 @@
 <ul class="tsd-hierarchy">
 <li><span class="target">DLDevice</span></li></ul></section><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L351">runtime.ts:351</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L351">runtime.ts:351</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 @@
 <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/89e902884/web/src/runtime.ts#L359">runtime.ts:359</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L359">runtime.ts:359</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/89e902884/web/src/runtime.ts#L355">runtime.ts:355</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L355">runtime.ts:355</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/89e902884/web/src/runtime.ts#L353">runtime.ts:353</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L353">runtime.ts:353</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/89e902884/web/src/runtime.ts#L378">runtime.ts:378</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L378">runtime.ts:378</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/89e902884/web/src/runtime.ts#L385">runtime.ts:385</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L385">runtime.ts:385</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 b0d46dabc6..dadc8de246 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/89e902884/web/src/runtime.ts#L1072">runtime.ts:1072</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1072">runtime.ts:1072</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">
@@ -145,24 +145,24 @@ 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/89e902884/web/src/runtime.ts#L1103">runtime.ts:1103</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1103">runtime.ts:1103</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/89e902884/web/src/runtime.ts#L1075">runtime.ts:1075</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1075">runtime.ts:1075</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/89e902884/web/src/runtime.ts#L1074">runtime.ts:1074</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1074">runtime.ts:1074</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/89e902884/web/src/runtime.ts#L1073">runtime.ts:1073</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1073">runtime.ts:1073</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="applyPresenceAndFrequencyPenalty" class="tsd-anchor"></a>
@@ -198,7 +198,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1870">runtime.ts:1870</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1870">runtime.ts:1870</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="applyRepetitionPenalty" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>apply<wbr/>Repetition<wbr/>Penalty</span><a href="#applyRepetitionPenalty" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">
@@ -223,7 +223,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1857">runtime.ts:1857</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1857">runtime.ts:1857</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">
@@ -244,7 +244,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1887">runtime.ts:1887</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1887">runtime.ts:1887</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">
@@ -261,7 +261,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L2087">runtime.ts:2087</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2087">runtime.ts:2087</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="asyncifyEnabled" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>asyncify<wbr/>Enabled</span><a href="#asyncifyEnabled" 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">
@@ -272,7 +272,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">boolean</span></h4><p>The asynctify mode toggle</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1171">runtime.ts:1171</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1171">runtime.ts:1171</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">
@@ -299,7 +299,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1236">runtime.ts:1236</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1236">runtime.ts:1236</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">
@@ -309,7 +309,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1195">runtime.ts:1195</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1195">runtime.ts:1195</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">
@@ -344,7 +344,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 <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/89e902884/web/src/runtime.ts#L1146">runtime.ts:1146</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1146">runtime.ts:1146</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">
@@ -361,7 +361,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1895">runtime.ts:1895</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1895">runtime.ts:1895</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">
@@ -371,7 +371,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1926">runtime.ts:1926</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1926">runtime.ts:1926</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">
@@ -388,7 +388,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 </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/89e902884/web/src/runtime.ts#L1737">runtime.ts:1737</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1737">runtime.ts:1737</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">
@@ -406,7 +406,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
 <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/89e902884/web/src/runtime.ts#L1414">runtime.ts:1414</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1414">runtime.ts:1414</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">
@@ -432,7 +432,7 @@ 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/89e902884/web/src/runtime.ts#L1263">runtime.ts:1263</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1263">runtime.ts:1263</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">
@@ -454,7 +454,7 @@ 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>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1729">runtime.ts:1729</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1729">runtime.ts:1729</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">
@@ -467,7 +467,7 @@ 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/89e902884/web/src/runtime.ts#L1175">runtime.ts:1175</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1175">runtime.ts:1175</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>
 <ul class="tsd-signatures">
@@ -493,7 +493,7 @@ only the first call will take effect.</p>
 <h4 class="tsd-returns-title">Returns <a href="NDArray.html" class="tsd-signature-type tsd-kind-class">NDArray</a></h4><p>The created ndarray.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1757">runtime.ts:1757</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1757">runtime.ts:1757</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">
@@ -506,7 +506,7 @@ a value to parent scope.</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/89e902884/web/src/runtime.ts#L1206">runtime.ts:1206</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1206">runtime.ts:1206</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">
@@ -532,7 +532,7 @@ a value to parent scope.</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">any</span><span class="tsd-signature-symbol">&gt;</span></h4><p>The meta data</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1505">runtime.ts:1505</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1505">runtime.ts:1505</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>
 <ul class="tsd-signatures">
@@ -550,7 +550,7 @@ a value to parent scope.</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/89e902884/web/src/runtime.ts#L1351">runtime.ts:1351</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1351">runtime.ts:1351</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>
 <ul class="tsd-signatures">
@@ -571,7 +571,7 @@ a value to parent scope.</p>
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 <h4 class="tsd-returns-title">Returns <a href="TVMObject.html" class="tsd-signature-type tsd-kind-class">TVMObject</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1442">runtime.ts:1442</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1442">runtime.ts:1442</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>
 <ul class="tsd-signatures">
@@ -589,7 +589,7 @@ a value to parent scope.</p>
 <h4 class="tsd-returns-title">Returns <a href="TVMObject.html" class="tsd-signature-type tsd-kind-class">TVMObject</a></h4><p>Parameters read.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1453">runtime.ts:1453</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1453">runtime.ts:1453</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>
 <ul class="tsd-signatures">
@@ -606,7 +606,7 @@ a value to parent scope.</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/89e902884/web/src/runtime.ts#L2152">runtime.ts:2152</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2152">runtime.ts:2152</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>
 <ul class="tsd-signatures">
@@ -624,7 +624,7 @@ a value to parent scope.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">boolean</span></h4><p>The check result.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1386">runtime.ts:1386</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1386">runtime.ts:1386</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>
 <ul class="tsd-signatures">
@@ -635,7 +635,7 @@ a value to parent scope.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">[]</span></h4><p>The name list.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1279">runtime.ts:1279</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1279">runtime.ts:1279</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>
 <ul class="tsd-signatures">
@@ -653,7 +653,7 @@ a value to parent scope.</p>
 <h4 class="tsd-returns-title">Returns <a href="TVMObject.html" class="tsd-signature-type tsd-kind-class">TVMObject</a></h4><p>The created shape tuple.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1960">runtime.ts:1960</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1960">runtime.ts:1960</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>
 <ul class="tsd-signatures">
@@ -671,7 +671,7 @@ a value to parent scope.</p>
 <h4 class="tsd-returns-title">Returns <a href="_internal_.TVMString.html" class="tsd-signature-type tsd-kind-class">TVMString</a></h4><p>The result TVMString.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1951">runtime.ts:1951</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1951">runtime.ts:1951</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>
 <ul class="tsd-signatures">
@@ -691,7 +691,7 @@ and needs to b explicitly disposed.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1939">runtime.ts:1939</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1939">runtime.ts:1939</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">
@@ -716,7 +716,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1249">runtime.ts:1249</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1249">runtime.ts:1249</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>
 <ul class="tsd-signatures">
@@ -726,7 +726,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1493">runtime.ts:1493</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1493">runtime.ts:1493</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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@@ -744,7 +744,7 @@ 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/89e902884/web/src/runtime.ts#L1466">runtime.ts:1466</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1466">runtime.ts:1466</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>
 <ul class="tsd-signatures">
@@ -762,7 +762,7 @@ 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/89e902884/web/src/runtime.ts#L1475">runtime.ts:1475</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1475">runtime.ts:1475</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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@@ -785,7 +785,7 @@ alive when exit the current scope.</p>
 <h5><span class="tsd-kind-parameter">override</span>: <span class="tsd-signature-type">boolean</span><span class="tsd-signature-symbol"> = false</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/89e902884/web/src/runtime.ts#L1484">runtime.ts:1484</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1484">runtime.ts:1484</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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@@ -813,7 +813,7 @@ These functions contains explicit continuation</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/89e902884/web/src/runtime.ts#L2060">runtime.ts:2060</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2060">runtime.ts:2060</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerAsyncifyFunc" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Asyncify<wbr/>Func</span><a href="#registerAsyncifyFunc" 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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@@ -852,7 +852,7 @@ The wasm needs to be compiled with Asynctify</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/89e902884/web/src/runtime.ts#L2041">runtime.ts:2041</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2041">runtime.ts:2041</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>
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@@ -875,7 +875,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1318">runtime.ts:1318</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1318">runtime.ts:1318</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerInitProgressCallback" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Init<wbr/>Progress<wbr/>Callback</span><a href="#registerInitProgressCallback" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -892,7 +892,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/web/src/runtime.ts#L1431">runtime.ts:1431</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerObjectConstructor" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Object<wbr/>Constructor</span><a href="#registerObjectConstructor" 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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@@ -917,7 +917,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1997">runtime.ts:1997</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1997">runtime.ts:1997</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="runtimeStatsText" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>runtime<wbr/>Stats<wbr/>Text</span><a href="#runtimeStatsText" 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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@@ -927,7 +927,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1184">runtime.ts:1184</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1184">runtime.ts:1184</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="sampleTopPFromLogits" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>sample<wbr/>TopPFrom<wbr/>Logits</span><a href="#sampleTopPFromLogits" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -953,7 +953,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1836">runtime.ts:1836</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1836">runtime.ts:1836</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="sampleTopPFromProb" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>sample<wbr/>TopPFrom<wbr/>Prob</span><a href="#sampleTopPFromProb" 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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@@ -975,7 +975,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1847">runtime.ts:1847</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1847">runtime.ts:1847</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="scalar" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>scalar</span><a href="#scalar" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -997,7 +997,7 @@ The wasm needs to be compiled with Asynctify</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1719">runtime.ts:1719</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1719">runtime.ts:1719</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="setPackedArguments" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>set<wbr/>Packed<wbr/>Arguments</span><a href="#setPackedArguments" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -1027,7 +1027,7 @@ Allocate new temporary space from the stack if necessary.</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/89e902884/web/src/runtime.ts#L2290">runtime.ts:2290</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2290">runtime.ts:2290</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="setSeed" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>set<wbr/>Seed</span><a href="#setSeed" 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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@@ -1042,7 +1042,7 @@ Allocate new temporary space from the stack if necessary.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1824">runtime.ts:1824</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1824">runtime.ts:1824</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="showImage" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>show<wbr/>Image</span><a href="#showImage" 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">
@@ -1059,7 +1059,7 @@ Allocate new temporary space from the stack if necessary.</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/89e902884/web/src/runtime.ts#L1904">runtime.ts:1904</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1904">runtime.ts:1904</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="systemLib" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>system<wbr/>Lib</span><a href="#systemLib" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -1071,7 +1071,7 @@ 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/89e902884/web/src/runtime.ts#L1272">runtime.ts:1272</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1272">runtime.ts:1272</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="toDLDataType" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>toDLData<wbr/>Type</span><a href="#toDLDataType" 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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@@ -1089,7 +1089,7 @@ System lib is a global module that contains self register functions in startup.<
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L1673">runtime.ts:1673</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1673">runtime.ts:1673</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1397">runtime.ts:1397</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1969">runtime.ts:1969</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1803">runtime.ts:1803</a></li></ul></aside></li></ul></section>
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@@ -1172,7 +1172,7 @@ 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/0f38ef2d6/web/src/runtime.ts#L1745">runtime.ts:1745</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L1220">runtime.ts:1220</a></li></ul></aside></li></ul></section>
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@@ -1228,7 +1228,7 @@ to make sure you use await when calling the funciton.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L2024">runtime.ts:2024</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/LinearCongruentialGenerator.html b/docs/reference/api/typedoc/classes/LinearCongruentialGenerator.html
index c1ae3973d6..dfb90b6675 100644
--- a/docs/reference/api/typedoc/classes/LinearCongruentialGenerator.html
+++ b/docs/reference/api/typedoc/classes/LinearCongruentialGenerator.html
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L87">support.ts:87</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L87">support.ts:87</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L97">support.ts:97</a></li></ul></aside></li></ul></section></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L90">support.ts:90</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L90">support.ts:90</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L88">support.ts:88</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L88">support.ts:88</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L89">support.ts:89</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L89">support.ts:89</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
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 <section class="tsd-panel tsd-member"><a id="nextInt" class="tsd-anchor"></a>
@@ -89,7 +89,7 @@ sepcification in <a href="https://en.cppreference.com/w/cpp/numeric/random/linea
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L126">support.ts:126</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L126">support.ts:126</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="randomFloat" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>random<wbr/>Float</span><a href="#randomFloat" 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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@@ -100,7 +100,7 @@ sepcification in <a href="https://en.cppreference.com/w/cpp/numeric/random/linea
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/support.ts#L140">support.ts:140</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L140">support.ts:140</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="setSeed" class="tsd-anchor"></a>
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@@ -118,7 +118,7 @@ sepcification in <a href="https://en.cppreference.com/w/cpp/numeric/random/linea
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/support.ts#L110">support.ts:110</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 032f00eae6..1e89473e25 100644
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L699">runtime.ts:699</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L699">runtime.ts:699</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L704">runtime.ts:704</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L704">runtime.ts:704</a></li></ul></aside></li></ul></section></section>
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@@ -88,7 +88,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L714">runtime.ts:714</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L714">runtime.ts:714</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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L742">runtime.ts:742</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L742">runtime.ts:742</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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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/web/src/runtime.ts#L729">runtime.ts:729</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="importModule" class="tsd-anchor"></a>
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@@ -145,7 +145,7 @@ only the first call will take effect.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L776">runtime.ts:776</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
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L442">runtime.ts:442</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L442">runtime.ts:442</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L462">runtime.ts:462</a></li></ul></aside></li></ul></section></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L452">runtime.ts:452</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L448">runtime.ts:448</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L448">runtime.ts:448</a></li></ul></aside></section>
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 <div class="tsd-comment tsd-typography"><p>Whether it is a temporary view that can become invalid after the call.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L454">runtime.ts:454</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L454">runtime.ts:454</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="ndim" class="tsd-anchor"></a>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L446">runtime.ts:446</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L446">runtime.ts:446</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="shape" class="tsd-anchor"></a>
 <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/89e902884/web/src/runtime.ts#L450">runtime.ts:450</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L450">runtime.ts:450</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/89e902884/web/src/runtime.ts#L562">runtime.ts:562</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L562">runtime.ts:562</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/89e902884/web/src/runtime.ts#L606">runtime.ts:606</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L606">runtime.ts:606</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>
 <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/89e902884/web/src/runtime.ts#L547">runtime.ts:547</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L547">runtime.ts:547</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>
 <ul class="tsd-signatures">
@@ -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/89e902884/web/src/runtime.ts#L540">runtime.ts:540</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L540">runtime.ts:540</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">
@@ -194,7 +194,7 @@ 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/89e902884/web/src/runtime.ts#L528">runtime.ts:528</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L528">runtime.ts:528</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>
 <ul class="tsd-signatures">
@@ -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/89e902884/web/src/runtime.ts#L672">runtime.ts:672</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L672">runtime.ts:672</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>
 <ul class="tsd-signatures">
@@ -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/89e902884/web/src/runtime.ts#L641">runtime.ts:641</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L641">runtime.ts:641</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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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L517">runtime.ts:517</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L517">runtime.ts:517</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 43d2979281..7527ec87c2 100644
--- a/docs/reference/api/typedoc/classes/RPCServer.html
+++ b/docs/reference/api/typedoc/classes/RPCServer.html
@@ -23,7 +23,7 @@
 <ul class="tsd-hierarchy">
 <li><span class="target">RPCServer</span></li></ul></section><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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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/89e902884/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/0f38ef2d6/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">
 <h2>Properties</h2>
 <section class="tsd-panel tsd-member"><a id="getImports" class="tsd-anchor"></a>
@@ -113,12 +113,12 @@
 <li class="tsd-description">
 <h4 class="tsd-returns-title">Returns <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">unknown</span><span class="tsd-signature-symbol">&gt;</span></h4></li></ul></li></ul></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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/89e902884/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/0f38ef2d6/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="logger" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>logger</span><a href="#logger" aria-label="Permalink" class="tsd-anchor-icon"><svg 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>
@@ -136,22 +136,22 @@
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 <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/89e902884/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/0f38ef2d6/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>
 <h3 class="tsd-anchor-link"><span>socket</span><a href="#socket" 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">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/89e902884/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/0f38ef2d6/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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 <div class="tsd-signature"><span class="tsd-kind-property">state</span><span class="tsd-signature-symbol">:</span> <a href="../enums/_internal_.RPCServerState.html" class="tsd-signature-type tsd-kind-enum">RPCServerState</a><span class="tsd-signature-symbol"> = RPCServerState.InitHeader</span></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li></ul></aside></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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 99232a3b92..d5410235d5 100644
--- a/docs/reference/api/typedoc/classes/Scalar.html
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L289">runtime.ts:289</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L289">runtime.ts:289</a></li></ul></aside>
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 <h4 class="tsd-returns-title">Returns <a href="Scalar.html" class="tsd-signature-type tsd-kind-class">Scalar</a></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L295">runtime.ts:295</a></li></ul></aside></li></ul></section></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L293">runtime.ts:293</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L293">runtime.ts:293</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L291">runtime.ts:291</a></li></ul></aside></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L291">runtime.ts:291</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 1aa380cf66..11e2e9fbae 100644
--- a/docs/reference/api/typedoc/classes/TVMArray.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L873">runtime.ts:873</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L873">runtime.ts:873</a></li></ul></aside>
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@@ -63,7 +63,7 @@
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L874">runtime.ts:874</a></li></ul></aside></li></ul></section></section>
 <section class="tsd-panel-group tsd-member-group">
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@@ -78,7 +78,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L804">runtime.ts:804</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L804">runtime.ts:804</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="get" class="tsd-anchor"></a>
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@@ -96,7 +96,7 @@ only the first call will take effect.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L893">runtime.ts:893</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L893">runtime.ts:893</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member tsd-is-inherited"><a id="getHandle" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L819">runtime.ts:819</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L819">runtime.ts:819</a></li></ul></aside></li></ul></section>
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@@ -125,7 +125,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L885">runtime.ts:885</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L885">runtime.ts:885</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member tsd-is-inherited"><a id="typeIndex" class="tsd-anchor"></a>
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@@ -136,7 +136,7 @@ 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#typeIndex">typeIndex</a></p>
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L827">runtime.ts:827</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L827">runtime.ts:827</a></li></ul></aside></li></ul></section>
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@@ -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/89e902884/web/src/runtime.ts#L847">runtime.ts:847</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L847">runtime.ts:847</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/TVMObject.html b/docs/reference/api/typedoc/classes/TVMObject.html
index d53408166c..0a2bab8bb8 100644
--- a/docs/reference/api/typedoc/classes/TVMObject.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L789">runtime.ts:789</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L789">runtime.ts:789</a></li></ul></aside>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L794">runtime.ts:794</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>
@@ -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/89e902884/web/src/runtime.ts#L804">runtime.ts:804</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L804">runtime.ts:804</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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 <aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L819">runtime.ts:819</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>
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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/89e902884/web/src/runtime.ts#L827">runtime.ts:827</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L827">runtime.ts:827</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="typeKey" class="tsd-anchor"></a>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L847">runtime.ts:847</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
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L928">runtime.ts:928</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L928">runtime.ts:928</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L935">runtime.ts:935</a></li></ul></aside></li></ul></section></section>
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 <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/89e902884/web/src/runtime.ts#L948">runtime.ts:948</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L948">runtime.ts:948</a></li></ul></aside></li></ul></section>
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@@ -101,7 +101,7 @@ 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/89e902884/web/src/runtime.ts#L956">runtime.ts:956</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L956">runtime.ts:956</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="getInternalModule" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L963">runtime.ts:963</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.AsyncifyHandler.html b/docs/reference/api/typedoc/classes/_internal_.AsyncifyHandler.html
index 81e30f88d1..825ea05de7 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L44">asyncify.ts:44</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L58">asyncify.ts:58</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="enabled" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L69">asyncify.ts:69</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L69">asyncify.ts:69</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="getState" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>get<wbr/>State</span><a href="#getState" 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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@@ -81,7 +81,7 @@
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L78">asyncify.ts:78</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L78">asyncify.ts:78</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="wrapExport" class="tsd-anchor"></a>
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@@ -124,7 +124,7 @@
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L140">asyncify.ts:140</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="wrapImport" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>wrap<wbr/>Import</span><a href="#wrapImport" 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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@@ -167,7 +167,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L88">asyncify.ts:88</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L88">asyncify.ts:88</a></li></ul></aside></li></ul></section></section></div>
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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 f78bd0121d..7eda7e2781 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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
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@@ -86,7 +86,7 @@ can still call into storeXX</li>
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 <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/89e902884/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/0f38ef2d6/web/src/memory.ts#L225">memory.ts:225</a></li></ul></aside></li></ul></section></section>
 <section class="tsd-panel-group tsd-member-group">
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@@ -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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/web/src/memory.ts#L208">memory.ts:208</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
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 <section class="tsd-panel tsd-member"><a id="allocPtrArray" class="tsd-anchor"></a>
@@ -115,7 +115,7 @@ can still call into storeXX</li>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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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/89e902884/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/0f38ef2d6/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>
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@@ -156,7 +156,7 @@ Allocate new temporary space for bytes.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -180,7 +180,7 @@ and will be filled when we commit the data.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -199,7 +199,7 @@ No further store function should be called.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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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/89e902884/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/0f38ef2d6/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>
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@@ -230,7 +230,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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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/89e902884/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/0f38ef2d6/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>
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@@ -240,7 +240,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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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/89e902884/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/0f38ef2d6/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>
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@@ -255,7 +255,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -270,7 +270,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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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/89e902884/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/0f38ef2d6/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>
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@@ -285,7 +285,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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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/89e902884/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/0f38ef2d6/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>
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@@ -300,7 +300,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -315,7 +315,7 @@ Note that the returned value becomes obsolete if alloc is called on the stack.</
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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/89e902884/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/0f38ef2d6/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/89e902884/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/0f38ef2d6/web/src/memory.ts#L334">memory.ts:334</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html b/docs/reference/api/typedoc/classes/_internal_.CanvasRenderManager.html
index 2a947ff724..a8f7d2d5cf 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/89e902884/web/src/webgpu.ts#L168">webgpu.ts:168</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L168">webgpu.ts:168</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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@@ -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/89e902884/web/src/webgpu.ts#L177">webgpu.ts:177</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L177">webgpu.ts:177</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/89e902884/web/src/webgpu.ts#L251">webgpu.ts:251</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L251">webgpu.ts:251</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/89e902884/web/src/webgpu.ts#L327">webgpu.ts:327</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L327">webgpu.ts:327</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/89e902884/web/src/webgpu.ts#L277">webgpu.ts:277</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L277">webgpu.ts:277</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.Environment.html b/docs/reference/api/typedoc/classes/_internal_.Environment.html
index 2e2c9aebbb..cc71ad2eaa 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/89e902884/web/src/environment.ts#L68">environment.ts:68</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/89e902884/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/0f38ef2d6/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/89e902884/web/src/environment.ts#L70">environment.ts:70</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/89e902884/web/src/environment.ts#L69">environment.ts:69</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/89e902884/web/src/environment.ts#L78">environment.ts:78</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/89e902884/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/0f38ef2d6/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/89e902884/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/0f38ef2d6/web/src/environment.ts#L105">environment.ts:105</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
index ec9cc404a4..47642d4110 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/89e902884/web/src/runtime.ts#L52">runtime.ts:52</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L52">runtime.ts:52</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 @@
 <h5><span class="tsd-kind-parameter">imports</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></h5></li></ul></div>
 <h4 class="tsd-returns-title">Returns <a href="_internal_.FFILibrary.html" class="tsd-signature-type tsd-kind-class">FFILibrary</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L60">runtime.ts:60</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L60">runtime.ts:60</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/89e902884/web/src/runtime.ts#L55">runtime.ts:55</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L55">runtime.ts:55</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/89e902884/web/src/runtime.ts#L54">runtime.ts:54</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L54">runtime.ts:54</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/89e902884/web/src/runtime.ts#L53">runtime.ts:53</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L53">runtime.ts:53</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/89e902884/web/src/runtime.ts#L56">runtime.ts:56</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L56">runtime.ts:56</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/89e902884/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/0f38ef2d6/web/src/runtime.ts#L86">runtime.ts:86</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/89e902884/web/src/runtime.ts#L75">runtime.ts:75</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L75">runtime.ts:75</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>
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 <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/89e902884/web/src/runtime.ts#L94">runtime.ts:94</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L94">runtime.ts:94</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>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L105">runtime.ts:105</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L105">runtime.ts:105</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>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L82">runtime.ts:82</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_.Memory.html b/docs/reference/api/typedoc/classes/_internal_.Memory.html
index e97199d2ae..25e7d2a283 100644
--- a/docs/reference/api/typedoc/classes/_internal_.Memory.html
+++ b/docs/reference/api/typedoc/classes/_internal_.Memory.html
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 <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/89e902884/web/src/memory.ts#L31">memory.ts:31</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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">
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 <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/89e902884/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/0f38ef2d6/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/89e902884/web/src/memory.ts#L32">memory.ts:32</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/89e902884/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/0f38ef2d6/web/src/memory.ts#L33">memory.ts:33</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
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 <section class="tsd-panel tsd-member"><a id="loadCString" class="tsd-anchor"></a>
@@ -101,7 +101,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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 @@
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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/89e902884/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/0f38ef2d6/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>
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@@ -127,7 +127,7 @@
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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/89e902884/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/0f38ef2d6/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>
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@@ -140,7 +140,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -153,7 +153,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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>
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@@ -217,7 +217,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/web/src/memory.ts#L60">memory.ts:60</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="loadU32" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>load<wbr/>U32</span><a href="#loadU32" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -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/89e902884/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/0f38ef2d6/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 @@
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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/89e902884/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/0f38ef2d6/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>
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@@ -256,7 +256,7 @@
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><aside class="tsd-sources">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/0f38ef2d6/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/89e902884/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/0f38ef2d6/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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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/memory.ts#L175">memory.ts:175</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L308">runtime.ts:308</a></li></ul></aside></li></ul></section></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L313">runtime.ts:313</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L313">runtime.ts:313</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L322">runtime.ts:322</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L175">runtime.ts:175</a></li></ul></aside></li></ul></section></section>
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 <div class="tsd-signature"><span class="tsd-kind-property">apply<wbr/>Presence<wbr/>And<wbr/>Frequency<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">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L170">runtime.ts:170</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L170">runtime.ts:170</a></li></ul></aside></section>
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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">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L169">runtime.ts:169</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L169">runtime.ts:169</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L171">runtime.ts:171</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L161">runtime.ts:161</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L159">runtime.ts:159</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L162">runtime.ts:162</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L152">runtime.ts:152</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L153">runtime.ts:153</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/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/89e902884/web/src/runtime.ts#L156">runtime.ts:156</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L166">runtime.ts:166</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</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/89e902884/web/src/runtime.ts#L163">runtime.ts:163</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L163">runtime.ts:163</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="paramModuleFromCacheByName" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>param<wbr/>Module<wbr/>From<wbr/>Cache<wbr/>By<wbr/>Name</span><a href="#paramModuleFromCacheByName" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">param<wbr/>Module<wbr/>From<wbr/>Cache<wbr/>By<wbr/>Name</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L164">runtime.ts:164</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L164">runtime.ts:164</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="sampleTopPFromLogits" class="tsd-anchor"></a>
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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">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L167">runtime.ts:167</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L167">runtime.ts:167</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="sampleTopPFromProb" class="tsd-anchor"></a>
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 <div class="tsd-signature"><span class="tsd-kind-property">sample<wbr/>TopPFrom<wbr/>Prob</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/89e902884/web/src/runtime.ts#L168">runtime.ts:168</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L168">runtime.ts:168</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="stringMake" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>string<wbr/>Make</span><a href="#stringMake" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">string<wbr/>Make</span><span class="tsd-signature-symbol">:</span> <a href="../types/PackedFunc.html" class="tsd-signature-type tsd-kind-type-alias">PackedFunc</a></div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L155">runtime.ts:155</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L155">runtime.ts:155</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
 <h2>Methods</h2>
 <section class="tsd-panel tsd-member"><a id="attachToCurrentScope" class="tsd-anchor"></a>
@@ -225,7 +225,7 @@
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><p>the same object.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L247">runtime.ts:247</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L247">runtime.ts:247</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">
@@ -233,7 +233,7 @@
 <li class="tsd-description">
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L221">runtime.ts:221</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L221">runtime.ts:221</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">
@@ -251,7 +251,7 @@
 <h5><span class="tsd-kind-parameter">obj</span>: <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h5></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L266">runtime.ts:266</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L266">runtime.ts:266</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">
@@ -264,7 +264,7 @@ 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/89e902884/web/src/runtime.ts#L198">runtime.ts:198</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L198">runtime.ts:198</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">
@@ -272,7 +272,7 @@ only the first call will take effect.</p>
 <li class="tsd-description">
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L225">runtime.ts:225</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L225">runtime.ts:225</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">
@@ -290,7 +290,7 @@ 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/89e902884/web/src/runtime.ts#L256">runtime.ts:256</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L256">runtime.ts:256</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
 <div class="page-menu">
 <div class="tsd-navigation settings">
diff --git a/docs/reference/api/typedoc/classes/_internal_.TVMString.html b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
index cfe65bbf71..384c2f1cc6 100644
--- a/docs/reference/api/typedoc/classes/_internal_.TVMString.html
+++ b/docs/reference/api/typedoc/classes/_internal_.TVMString.html
@@ -26,7 +26,7 @@
 <ul class="tsd-hierarchy">
 <li><span class="target">TVMString</span></li></ul></li></ul></section><aside class="tsd-sources">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L899">runtime.ts:899</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L899">runtime.ts:899</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
 <section class="tsd-panel tsd-index-panel">
 <details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -63,7 +63,7 @@
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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/89e902884/web/src/runtime.ts#L900">runtime.ts:900</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L900">runtime.ts:900</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/89e902884/web/src/runtime.ts#L804">runtime.ts:804</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L804">runtime.ts:804</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/89e902884/web/src/runtime.ts#L819">runtime.ts:819</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L819">runtime.ts:819</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/89e902884/web/src/runtime.ts#L911">runtime.ts:911</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L911">runtime.ts:911</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/89e902884/web/src/runtime.ts#L827">runtime.ts:827</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L827">runtime.ts:827</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/89e902884/web/src/runtime.ts#L847">runtime.ts:847</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L847">runtime.ts:847</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 c9de7d1ec5..232c394278 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/89e902884/web/src/webgpu.ts#L345">webgpu.ts:345</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L345">webgpu.ts:345</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/89e902884/web/src/webgpu.ts#L370">webgpu.ts:370</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L370">webgpu.ts:370</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/89e902884/web/src/webgpu.ts#L346">webgpu.ts:346</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L346">webgpu.ts:346</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="memory" class="tsd-anchor"></a>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/webgpu.ts#L347">webgpu.ts:347</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L347">webgpu.ts:347</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L454">webgpu.ts:454</a></li></ul></aside></li></ul></section>
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@@ -110,7 +110,7 @@ Manages all the webgpu resources here.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L446">webgpu.ts:446</a></li></ul></aside></li></ul></section>
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@@ -139,7 +139,7 @@ Manages all the webgpu resources here.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L428">webgpu.ts:428</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="createShader" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L466">webgpu.ts:466</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L478">webgpu.ts:478</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L378">webgpu.ts:378</a></li></ul></aside></li></ul></section>
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@@ -216,7 +216,7 @@ via createComputePipelineAsync</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L413">webgpu.ts:413</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L734">webgpu.ts:734</a></li></ul></aside></li></ul></section>
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@@ -242,7 +242,7 @@ via createComputePipelineAsync</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L400">webgpu.ts:400</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L393">webgpu.ts:393</a></li></ul></aside></li></ul></section></section></div>
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diff --git a/docs/reference/api/typedoc/enums/_internal_.AsyncifyStateKind.html b/docs/reference/api/typedoc/enums/_internal_.AsyncifyStateKind.html
index 6cb92ca5a8..e37e325ed4 100644
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L30">asyncify.ts:30</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L30">asyncify.ts:30</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L31">asyncify.ts:31</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L31">asyncify.ts:31</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/asyncify.ts#L33">asyncify.ts:33</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L33">asyncify.ts:33</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/asyncify.ts#L32">asyncify.ts:32</a></li></ul></aside></section></section></div>
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diff --git a/docs/reference/api/typedoc/enums/_internal_.RPCServerState.html b/docs/reference/api/typedoc/enums/_internal_.RPCServerState.html
index 01d1805521..e1154bfbc6 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/rpc_server.ts#L27">rpc_server.ts:27</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/rpc_server.ts#L28">rpc_server.ts:28</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="InitHeaderKey" class="tsd-anchor"></a>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/rpc_server.ts#L29">rpc_server.ts:29</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="InitServer" class="tsd-anchor"></a>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/rpc_server.ts#L30">rpc_server.ts:30</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/0f38ef2d6/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/0f38ef2d6/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/0f38ef2d6/web/src/types.ts#L39">types.ts:39</a></li></ul></aside></section></section></div>
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index 1d0849c5c6..7a67ed30ab 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/artifact_cache.ts#L22">artifact_cache.ts:22</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/artifact_cache.ts#L31">artifact_cache.ts:31</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/artifact_cache.ts#L41">artifact_cache.ts:41</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/artifact_cache.ts#L26">artifact_cache.ts:26</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/artifact_cache.ts#L36">artifact_cache.ts:36</a></li></ul></aside></li></ul></section></section></div>
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index 2f8b01a57b..9b2a86ed4e 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L335">webgpu.ts:335</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L337">webgpu.ts:337</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L338">webgpu.ts:338</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/webgpu.ts#L336">webgpu.ts:336</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L973">runtime.ts:973</a></li></ul></aside>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L978">runtime.ts:978</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L978">runtime.ts:978</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L976">runtime.ts:976</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L976">runtime.ts:976</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/0f38ef2d6/web/src/runtime.ts#L974">runtime.ts:974</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L979">runtime.ts:979</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/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/0f38ef2d6/web/src/runtime.ts#L975">runtime.ts:975</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L982">runtime.ts:982</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L983">runtime.ts:983</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L984">runtime.ts:984</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L984">runtime.ts:984</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/89e902884/web/src/runtime.ts#L985">runtime.ts:985</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L985">runtime.ts:985</a></li></ul></aside></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/runtime.ts#L986">runtime.ts:986</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/ctypes.ts#L194">ctypes.ts:194</a></li></ul></aside></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/0f38ef2d6/web/src/ctypes.ts#L197">ctypes.ts:197</a></li></ul></aside></div>
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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 19e90915c8..4b8f40ae3e 100644
--- a/docs/topic/vta/tutorials/frontend/deploy_detection.html
+++ b/docs/topic/vta/tutorials/frontend/deploy_detection.html
@@ -619,7 +619,7 @@ and dense layer which will both be executed in fp32 on the CPU.</p></li>
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 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/workspace/python/tvm/relay/build_module.py:345: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
   warnings.warn(
-yolov3-tiny inference graph built in 25.91s!
+yolov3-tiny inference graph built in 27.20s!
 </pre></div>
 </div>
 </div>
@@ -704,6 +704,7 @@ Download test image</p>
         alu_counter     :           849056
 </pre></div>
 </div>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  0.711 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-topic-vta-tutorials-frontend-deploy-detection-py">
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diff --git a/docs/topic/vta/tutorials/frontend/sg_execution_times.html b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
index feedcc742a..7c335323dc 100644
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+++ b/docs/topic/vta/tutorials/frontend/sg_execution_times.html
@@ -360,7 +360,7 @@
             
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-<p><strong>00:58.587</strong> total execution time for <strong>topic_vta_tutorials_frontend</strong> files:</p>
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-<p><strong>00:03.203</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
+<p><strong>00:03.221</strong> total execution time for <strong>topic_vta_tutorials_optimize</strong> files:</p>
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-<p><strong>00:00.781</strong> total execution time for <strong>topic_vta_tutorials</strong> files:</p>
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diff --git a/docs/tutorial/auto_scheduler_matmul_x86.html b/docs/tutorial/auto_scheduler_matmul_x86.html
index eea7ce0cb6..3b46fe1d99 100644
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+++ b/docs/tutorial/auto_scheduler_matmul_x86.html
@@ -589,7 +589,7 @@ class Module:
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+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 95.753 ms
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 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Resume search:
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@@ -661,7 +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  25.286 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  41.544 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-auto-scheduler-matmul-x86-py">
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diff --git a/docs/tutorial/autotvm_matmul_x86.html b/docs/tutorial/autotvm_matmul_x86.html
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-No: 7   GFLOPS: 12.70/12.70     result: MeasureResult(costs=(0.021133044799999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6931145191192627, timestamp=1710952631.215719)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 128])],None,78
-No: 8   GFLOPS: 8.94/12.70      result: MeasureResult(costs=(0.0300193318,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7496693134307861, timestamp=1710952631.9548552)       [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 64])],None,61
-No: 9   GFLOPS: 0.52/12.70      result: MeasureResult(costs=(0.5165772869999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.509665966033936, timestamp=1710952640.574059)   [(&#39;tile_y&#39;, [-1, 64]), (&#39;tile_x&#39;, [-1, 1])],None,6
-No: 10  GFLOPS: 1.96/12.70      result: MeasureResult(costs=(0.1367587458,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4044830799102783, timestamp=1710952643.0227075)       [(&#39;tile_y&#39;, [-1, 1]), (&#39;tile_x&#39;, [-1, 2])],None,10
+No: 1   GFLOPS: 10.52/10.52     result: MeasureResult(costs=(0.0255119836,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7534909248352051, timestamp=1710958532.3695402)       [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 64])],None,63
+No: 2   GFLOPS: 10.31/10.52     result: MeasureResult(costs=(0.026043288999999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6888840198516846, timestamp=1710958533.0425768)       [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 64])],None,61
+No: 3   GFLOPS: 13.37/13.37     result: MeasureResult(costs=(0.0200773646,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5822114944458008, timestamp=1710958533.6184666)       [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 64])],None,68
+No: 4   GFLOPS: 3.65/13.37      result: MeasureResult(costs=(0.07347294480000001,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4587929248809814, timestamp=1710958535.0518515)        [(&#39;tile_y&#39;, [-1, 64]), (&#39;tile_x&#39;, [-1, 8])],None,36
+No: 5   GFLOPS: 1.94/13.37      result: MeasureResult(costs=(0.13806226959999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4694745540618896, timestamp=1710958537.653597) [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 1])],None,3
+No: 6   GFLOPS: 3.46/13.37      result: MeasureResult(costs=(0.0775120986,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.516719102859497, timestamp=1710958539.1676307)        [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 2])],None,11
+No: 7   GFLOPS: 10.55/13.37     result: MeasureResult(costs=(0.0254555586,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6843729019165039, timestamp=1710958539.8332918)       [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 32])],None,52
+No: 8   GFLOPS: 0.99/13.37      result: MeasureResult(costs=(0.2720029142,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.609287977218628, timestamp=1710958544.4492793)        [(&#39;tile_y&#39;, [-1, 512]), (&#39;tile_x&#39;, [-1, 2])],None,19
+No: 9   GFLOPS: 8.21/13.37      result: MeasureResult(costs=(0.0327070768,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7589902877807617, timestamp=1710958545.3176453)       [(&#39;tile_y&#39;, [-1, 16]), (&#39;tile_x&#39;, [-1, 8])],None,34
+No: 10  GFLOPS: 3.63/13.37      result: MeasureResult(costs=(0.0740125118,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.410879135131836, timestamp=1710958546.7573817)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 8])],None,38
 </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 7c7bf7471c..5f9ff8c0e6 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;: 472.81652373001634, &#39;median&#39;: 473.12350920001336, &#39;std&#39;: 2.307640356318348}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;mean&#39;: 491.0514597600195, &#39;median&#39;: 490.92375170002924, &#39;std&#39;: 1.5121823348393049}
 </pre></div>
 </div>
 </div>
@@ -767,179 +767,178 @@ depending on the specifics of the model and the target platform.</p>
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  1/25]  Current/Best:   15.60/  20.89 GFLOPS | Progress: (4/20) | 8.00 s
-[Task  1/25]  Current/Best:   19.16/  20.89 GFLOPS | Progress: (8/20) | 10.54 s
-[Task  1/25]  Current/Best:    5.68/  20.89 GFLOPS | Progress: (12/20) | 14.31 s
-[Task  1/25]  Current/Best:   20.90/  20.90 GFLOPS | Progress: (16/20) | 16.44 s
-[Task  1/25]  Current/Best:   10.59/  20.90 GFLOPS | Progress: (20/20) | 18.77 s Done.
+[Task  1/25]  Current/Best:   10.90/  23.66 GFLOPS | Progress: (4/20) | 8.78 s
+[Task  1/25]  Current/Best:   21.73/  23.66 GFLOPS | Progress: (8/20) | 11.43 s
+[Task  1/25]  Current/Best:   12.82/  23.66 GFLOPS | Progress: (12/20) | 15.50 s
+[Task  1/25]  Current/Best:   15.10/  23.66 GFLOPS | Progress: (16/20) | 17.96 s
+[Task  1/25]  Current/Best:    5.71/  23.66 GFLOPS | Progress: (20/20) | 21.86 s Done.
 
 [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  2/25]  Current/Best:    5.81/  23.49 GFLOPS | Progress: (4/20) | 4.08 s
-[Task  2/25]  Current/Best:   13.81/  23.49 GFLOPS | Progress: (8/20) | 5.65 s
-[Task  2/25]  Current/Best:   11.19/  23.49 GFLOPS | Progress: (12/20) | 7.12 s
-[Task  2/25]  Current/Best:   19.84/  23.49 GFLOPS | Progress: (16/20) | 8.79 s
-[Task  2/25]  Current/Best:   17.10/  23.49 GFLOPS | Progress: (20/20) | 10.38 s Done.
+[Task  2/25]  Current/Best:   11.86/  20.47 GFLOPS | Progress: (4/20) | 4.25 s
+[Task  2/25]  Current/Best:   15.40/  20.47 GFLOPS | Progress: (8/20) | 6.82 s
+[Task  2/25]  Current/Best:   11.84/  20.47 GFLOPS | Progress: (12/20) | 8.67 s
+[Task  2/25]  Current/Best:    5.81/  20.47 GFLOPS | Progress: (16/20) | 10.00 s
+[Task  2/25]  Current/Best:    5.36/  20.47 GFLOPS | Progress: (20/20) | 11.89 s Done.
 
 [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  3/25]  Current/Best:   22.97/  22.97 GFLOPS | Progress: (4/20) | 4.72 s
-[Task  3/25]  Current/Best:   12.90/  22.97 GFLOPS | Progress: (8/20) | 8.80 s
-[Task  3/25]  Current/Best:   23.40/  23.40 GFLOPS | Progress: (12/20) | 11.11 s
-[Task  3/25]  Current/Best:   15.52/  23.40 GFLOPS | Progress: (16/20) | 14.33 s
-[Task  3/25]  Current/Best:   21.75/  23.76 GFLOPS | Progress: (20/20) | 16.04 s Done.
+[Task  3/25]  Current/Best:   12.47/  22.07 GFLOPS | Progress: (4/20) | 4.70 s
+[Task  3/25]  Current/Best:   15.30/  22.07 GFLOPS | Progress: (8/20) | 7.05 s
+[Task  3/25]  Current/Best:   17.36/  22.07 GFLOPS | Progress: (12/20) | 9.82 s
+[Task  3/25]  Current/Best:   22.27/  22.27 GFLOPS | Progress: (16/20) | 11.91 s
+[Task  3/25]  Current/Best:   12.80/  22.27 GFLOPS | Progress: (20/20) | 14.62 s Done.
 
 [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  4/25]  Current/Best:    3.50/  21.87 GFLOPS | Progress: (4/20) | 7.69 s
-[Task  4/25]  Current/Best:   10.55/  21.87 GFLOPS | Progress: (8/20) | 9.92 s
-[Task  4/25]  Current/Best:   15.13/  21.87 GFLOPS | Progress: (12/20) | 17.32 s
-[Task  4/25]  Current/Best:   11.17/  21.87 GFLOPS | Progress: (16/20) | 19.40 s
-[Task  4/25]  Current/Best:   12.55/  21.87 GFLOPS | Progress: (20/20) | 21.50 s Done.
+[Task  4/25]  Current/Best:   13.64/  17.95 GFLOPS | Progress: (4/20) | 5.53 s
+[Task  4/25]  Current/Best:    3.33/  17.95 GFLOPS | Progress: (8/20) | 7.90 s
+[Task  4/25]  Current/Best:   17.92/  17.95 GFLOPS | Progress: (12/20) | 9.81 s
+[Task  4/25]  Current/Best:   10.61/  17.95 GFLOPS | Progress: (16/20) | 12.01 s
+[Task  4/25]  Current/Best:   20.15/  20.15 GFLOPS | Progress: (20/20) | 14.27 s Done.
 
 [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  5/25]  Current/Best:    5.84/  15.89 GFLOPS | Progress: (4/20) | 4.64 s
-[Task  5/25]  Current/Best:    9.05/  15.89 GFLOPS | Progress: (8/20) | 6.54 s
-[Task  5/25]  Current/Best:    5.38/  21.32 GFLOPS | Progress: (12/20) | 8.52 s
-[Task  5/25]  Current/Best:   19.69/  21.32 GFLOPS | Progress: (16/20) | 10.98 s
-[Task  5/25]  Current/Best:   11.11/  21.32 GFLOPS | Progress: (20/20) | 13.19 s Done.
+[Task  5/25]  Current/Best:   19.74/  20.36 GFLOPS | Progress: (4/20) | 4.62 s
+[Task  5/25]  Current/Best:   12.50/  20.36 GFLOPS | Progress: (8/20) | 6.95 s
+[Task  5/25]  Current/Best:    7.34/  21.98 GFLOPS | Progress: (12/20) | 9.32 s
+[Task  5/25]  Current/Best:   17.72/  21.98 GFLOPS | Progress: (16/20) | 11.52 s
+[Task  5/25]  Current/Best:   13.62/  21.98 GFLOPS | Progress: (20/20) | 13.47 s Done.
 
 [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  6/25]  Current/Best:   15.50/  15.50 GFLOPS | Progress: (4/20) | 5.72 s
-[Task  6/25]  Current/Best:   13.81/  23.42 GFLOPS | Progress: (8/20) | 8.52 s
-[Task  6/25]  Current/Best:    4.88/  23.42 GFLOPS | Progress: (12/20) | 10.83 s
-[Task  6/25]  Current/Best:   13.85/  23.42 GFLOPS | Progress: (16/20) | 14.21 s
-[Task  6/25]  Current/Best:   13.91/  23.42 GFLOPS | Progress: (20/20) | 16.69 s Done.
+[Task  6/25]  Current/Best:   17.48/  17.48 GFLOPS | Progress: (4/20) | 4.63 s
+[Task  6/25]  Current/Best:   16.57/  17.48 GFLOPS | Progress: (8/20) | 7.09 s
+[Task  6/25]  Current/Best:   12.75/  17.48 GFLOPS | Progress: (12/20) | 11.70 s
+[Task  6/25]  Current/Best:   10.81/  17.48 GFLOPS | Progress: (16/20) | 14.59 s
+[Task  6/25]  Current/Best:    4.09/  17.48 GFLOPS | Progress: (20/20) | 17.87 s Done.
 
 [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  7/25]  Current/Best:   17.30/  18.84 GFLOPS | Progress: (4/20) | 4.68 s
-[Task  7/25]  Current/Best:   12.22/  20.44 GFLOPS | Progress: (8/20) | 7.39 s
-[Task  7/25]  Current/Best:   18.39/  20.44 GFLOPS | Progress: (12/20) | 9.49 s
-[Task  7/25]  Current/Best:    5.37/  20.44 GFLOPS | Progress: (16/20) | 12.72 s
-[Task  7/25]  Current/Best:   10.28/  20.44 GFLOPS | Progress: (20/20) | 15.74 s Done.
+[Task  7/25]  Current/Best:    4.99/  19.03 GFLOPS | Progress: (4/20) | 4.96 s
+[Task  7/25]  Current/Best:   22.37/  22.37 GFLOPS | Progress: (8/20) | 6.90 s
+[Task  7/25]  Current/Best:   14.50/  22.37 GFLOPS | Progress: (12/20) | 9.48 s
+[Task  7/25]  Current/Best:    9.24/  22.37 GFLOPS | Progress: (16/20) | 12.11 s
+[Task  7/25]  Current/Best:    9.22/  22.37 GFLOPS | Progress: (20/20) | 14.64 s Done.
 
 [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  8/25]  Current/Best:    3.95/  18.06 GFLOPS | Progress: (4/20) | 5.70 s
-[Task  8/25]  Current/Best:    6.13/  18.06 GFLOPS | Progress: (8/20) | 17.32 s
-[Task  8/25]  Current/Best:   16.64/  18.06 GFLOPS | Progress: (12/20) | 20.86 s
-[Task  8/25]  Current/Best:   13.80/  18.06 GFLOPS | Progress: (16/20) | 23.57 s
-[Task  8/25]  Current/Best:   21.90/  21.90 GFLOPS | Progress: (20/20) | 26.38 s
-[Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  9/25]  Current/Best:   17.69/  17.69 GFLOPS | Progress: (4/20) | 5.81 s
-[Task  9/25]  Current/Best:   19.84/  19.84 GFLOPS | Progress: (8/20) | 15.98 s
-[Task  9/25]  Current/Best:   11.88/  21.77 GFLOPS | Progress: (12/20) | 22.97 s
-[Task  9/25]  Current/Best:   17.39/  21.77 GFLOPS | Progress: (16/20) | 30.15 s
-[Task  9/25]  Current/Best:   12.82/  21.77 GFLOPS | Progress: (20/20) | 34.56 s Done.
+[Task  8/25]  Current/Best:    3.58/  18.69 GFLOPS | Progress: (4/20) | 7.38 s
+[Task  8/25]  Current/Best:    7.50/  18.69 GFLOPS | Progress: (8/20) | 10.09 s
+[Task  8/25]  Current/Best:    9.88/  18.69 GFLOPS | Progress: (12/20) | 19.65 s
+[Task  8/25]  Current/Best:    8.89/  18.69 GFLOPS | Progress: (16/20) | 23.55 s
+[Task  8/25]  Current/Best:   15.36/  18.69 GFLOPS | Progress: (20/20) | 26.10 s Done.
 
+[Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
+[Task  9/25]  Current/Best:    6.68/  19.86 GFLOPS | Progress: (4/20) | 4.40 s
+[Task  9/25]  Current/Best:    8.80/  19.86 GFLOPS | Progress: (8/20) | 10.39 s
+[Task  9/25]  Current/Best:    7.55/  19.86 GFLOPS | Progress: (12/20) | 15.29 s
+[Task  9/25]  Current/Best:   10.42/  19.86 GFLOPS | Progress: (16/20) | 26.35 s
+[Task  9/25]  Current/Best:    6.87/  19.86 GFLOPS | Progress: (20/20) | 37.32 s
 [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 10/25]  Current/Best:   14.85/  16.74 GFLOPS | Progress: (4/20) | 4.51 s
-[Task 10/25]  Current/Best:   10.77/  16.74 GFLOPS | Progress: (8/20) | 6.33 s
-[Task 10/25]  Current/Best:   16.15/  16.74 GFLOPS | Progress: (12/20) | 8.43 s
-[Task 10/25]  Current/Best:   10.58/  21.53 GFLOPS | Progress: (16/20) | 10.31 s
-[Task 10/25]  Current/Best:   14.59/  21.53 GFLOPS | Progress: (20/20) | 12.14 s Done.
+[Task 10/25]  Current/Best:   16.92/  16.92 GFLOPS | Progress: (4/20) | 4.42 s
+[Task 10/25]  Current/Best:    3.63/  17.43 GFLOPS | Progress: (8/20) | 6.94 s
+[Task 10/25]  Current/Best:    3.02/  17.43 GFLOPS | Progress: (12/20) | 9.34 s
+[Task 10/25]  Current/Best:    3.07/  17.43 GFLOPS | Progress: (16/20) | 11.88 s
+[Task 10/25]  Current/Best:   15.17/  17.43 GFLOPS | Progress: (20/20) | 13.73 s Done.
 
 [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 11/25]  Current/Best:   16.03/  21.79 GFLOPS | Progress: (4/20) | 4.56 s
-[Task 11/25]  Current/Best:   21.13/  21.79 GFLOPS | Progress: (8/20) | 6.86 s
-[Task 11/25]  Current/Best:   12.74/  21.79 GFLOPS | Progress: (12/20) | 8.97 s
-[Task 11/25]  Current/Best:   14.78/  24.61 GFLOPS | Progress: (16/20) | 11.12 s
-[Task 11/25]  Current/Best:   12.59/  24.61 GFLOPS | Progress: (20/20) | 13.70 s Done.
+[Task 11/25]  Current/Best:   16.36/  19.05 GFLOPS | Progress: (4/20) | 5.29 s
+[Task 11/25]  Current/Best:   11.35/  24.06 GFLOPS | Progress: (8/20) | 8.14 s
+[Task 11/25]  Current/Best:   11.05/  24.06 GFLOPS | Progress: (12/20) | 11.04 s
+[Task 11/25]  Current/Best:   16.13/  24.06 GFLOPS | Progress: (16/20) | 13.22 s
+[Task 11/25]  Current/Best:   12.81/  24.06 GFLOPS | Progress: (20/20) | 16.05 s Done.
 
 [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 12/25]  Current/Best:   10.35/  11.71 GFLOPS | Progress: (4/20) | 6.60 s
-[Task 12/25]  Current/Best:    4.25/  15.87 GFLOPS | Progress: (8/20) | 11.93 s
-[Task 12/25]  Current/Best:    6.17/  17.43 GFLOPS | Progress: (12/20) | 17.78 s
-[Task 12/25]  Current/Best:   17.18/  22.02 GFLOPS | Progress: (16/20) | 19.64 s
-[Task 12/25]  Current/Best:   21.41/  22.02 GFLOPS | Progress: (20/20) | 25.01 s Done.
+[Task 12/25]  Current/Best:   15.87/  18.06 GFLOPS | Progress: (4/20) | 4.86 s
+[Task 12/25]  Current/Best:   19.42/  19.42 GFLOPS | Progress: (8/20) | 6.74 s
+[Task 12/25]  Current/Best:   17.29/  22.00 GFLOPS | Progress: (12/20) | 8.61 s
+[Task 12/25]  Current/Best:    7.87/  22.00 GFLOPS | Progress: (16/20) | 10.94 s
+[Task 12/25]  Current/Best:   11.97/  22.00 GFLOPS | Progress: (20/20) | 15.07 s Done.
 
 [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 13/25]  Current/Best:    9.27/  14.87 GFLOPS | Progress: (4/20) | 5.98 s
-[Task 13/25]  Current/Best:   21.09/  23.91 GFLOPS | Progress: (8/20) | 8.91 s
-[Task 13/25]  Current/Best:   11.84/  23.91 GFLOPS | Progress: (12/20) | 13.33 s
-[Task 13/25]  Current/Best:   12.39/  23.91 GFLOPS | Progress: (16/20) | 17.02 s
-[Task 13/25]  Current/Best:   21.24/  23.91 GFLOPS | Progress: (20/20) | 20.65 s Done.
+[Task 13/25]  Current/Best:   19.69/  21.72 GFLOPS | Progress: (4/20) | 4.52 s
+[Task 13/25]  Current/Best:   11.15/  21.72 GFLOPS | Progress: (8/20) | 8.41 s
+[Task 13/25]  Current/Best:   17.49/  21.72 GFLOPS | Progress: (12/20) | 10.77 s
+[Task 13/25]  Current/Best:    5.14/  21.72 GFLOPS | Progress: (16/20) | 14.52 s
+[Task 13/25]  Current/Best:    9.79/  21.72 GFLOPS | Progress: (20/20) | 18.43 s Done.
 
 [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 14/25]  Current/Best:   10.47/  14.45 GFLOPS | Progress: (4/20) | 9.74 s
-[Task 14/25]  Current/Best:   10.40/  18.19 GFLOPS | Progress: (8/20) | 16.91 s
-[Task 14/25]  Current/Best:   13.13/  18.19 GFLOPS | Progress: (12/20) | 20.74 s
-[Task 14/25]  Current/Best:   17.35/  18.19 GFLOPS | Progress: (16/20) | 27.78 s
-[Task 14/25]  Current/Best:    7.13/  18.79 GFLOPS | Progress: (20/20) | 30.44 s Done.
+[Task 14/25]  Current/Best:   14.73/  18.33 GFLOPS | Progress: (4/20) | 9.19 s
+[Task 14/25]  Current/Best:   13.03/  18.33 GFLOPS | Progress: (8/20) | 13.06 s
+[Task 14/25]  Current/Best:    7.18/  18.33 GFLOPS | Progress: (12/20) | 22.06 s
+[Task 14/25]  Current/Best:    4.95/  18.33 GFLOPS | Progress: (16/20) | 27.98 s
+[Task 14/25]  Current/Best:    5.23/  18.33 GFLOPS | Progress: (20/20) | 34.37 s Done.
 
 [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 15/25]  Current/Best:    7.23/  18.83 GFLOPS | Progress: (4/20) | 5.07 s
-[Task 15/25]  Current/Best:   17.59/  20.01 GFLOPS | Progress: (8/20) | 6.93 s
-[Task 15/25]  Current/Best:   10.95/  20.01 GFLOPS | Progress: (12/20) | 9.13 s
-[Task 15/25]  Current/Best:    8.59/  20.01 GFLOPS | Progress: (16/20) | 17.37 s
-[Task 15/25]  Current/Best:   13.84/  22.14 GFLOPS | Progress: (20/20) | 22.13 s Done.
+[Task 15/25]  Current/Best:    7.63/  15.27 GFLOPS | Progress: (4/20) | 10.44 s
+[Task 15/25]  Current/Best:   22.17/  22.59 GFLOPS | Progress: (8/20) | 11.94 s
+[Task 15/25]  Current/Best:    5.24/  22.59 GFLOPS | Progress: (12/20) | 13.79 s
+[Task 15/25]  Current/Best:   11.02/  22.59 GFLOPS | Progress: (16/20) | 21.82 s
+[Task 15/25]  Current/Best:    4.79/  22.59 GFLOPS | Progress: (20/20) | 30.75 s Done.
 
 [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 16/25]  Current/Best:   17.94/  19.21 GFLOPS | Progress: (4/20) | 4.26 s
-[Task 16/25]  Current/Best:   13.32/  19.21 GFLOPS | Progress: (8/20) | 6.13 s
-[Task 16/25]  Current/Best:   11.27/  19.64 GFLOPS | Progress: (12/20) | 8.18 s
-[Task 16/25]  Current/Best:    8.35/  20.51 GFLOPS | Progress: (16/20) | 10.96 s
-[Task 16/25]  Current/Best:   12.10/  21.50 GFLOPS | Progress: (20/20) | 13.46 s Done.
+[Task 16/25]  Current/Best:    8.33/  21.26 GFLOPS | Progress: (4/20) | 4.28 s
+[Task 16/25]  Current/Best:    9.35/  21.26 GFLOPS | Progress: (8/20) | 7.50 s
+[Task 16/25]  Current/Best:   15.95/  21.26 GFLOPS | Progress: (12/20) | 9.59 s
+[Task 16/25]  Current/Best:    9.34/  21.26 GFLOPS | Progress: (16/20) | 12.30 s
+[Task 16/25]  Current/Best:   18.56/  21.26 GFLOPS | Progress: (20/20) | 14.44 s Done.
 
 [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 17/25]  Current/Best:   12.27/  23.24 GFLOPS | Progress: (4/20) | 5.11 s
-[Task 17/25]  Current/Best:    6.14/  24.31 GFLOPS | Progress: (8/20) | 7.65 s
-[Task 17/25]  Current/Best:   20.69/  24.31 GFLOPS | Progress: (12/20) | 9.96 s
-[Task 17/25]  Current/Best:   10.34/  24.31 GFLOPS | Progress: (16/20) | 12.25 s
-[Task 17/25]  Current/Best:   12.68/  24.31 GFLOPS | Progress: (20/20) | 15.94 s Done.
+[Task 17/25]  Current/Best:   19.32/  19.32 GFLOPS | Progress: (4/20) | 4.99 s
+[Task 17/25]  Current/Best:    9.88/  19.85 GFLOPS | Progress: (8/20) | 7.50 s
+[Task 17/25]  Current/Best:   10.80/  19.85 GFLOPS | Progress: (12/20) | 11.26 s
+[Task 17/25]  Current/Best:   21.93/  22.56 GFLOPS | Progress: (16/20) | 13.26 s
+[Task 17/25]  Current/Best:    9.84/  23.17 GFLOPS | Progress: (20/20) | 15.57 s Done.
 
 [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 18/25]  Current/Best:   11.68/  14.48 GFLOPS | Progress: (4/20) | 6.45 s
-[Task 18/25]  Current/Best:   15.52/  15.72 GFLOPS | Progress: (8/20) | 9.37 s
-[Task 18/25]  Current/Best:    9.43/  18.21 GFLOPS | Progress: (12/20) | 15.43 s
-[Task 18/25]  Current/Best:   21.58/  21.58 GFLOPS | Progress: (16/20) | 21.63 s
-[Task 18/25]  Current/Best:   11.36/  21.58 GFLOPS | Progress: (20/20) | 25.04 s Done.
+[Task 18/25]  Current/Best:    5.77/  17.03 GFLOPS | Progress: (4/20) | 6.64 s
+[Task 18/25]  Current/Best:   12.53/  19.25 GFLOPS | Progress: (8/20) | 11.30 s
+[Task 18/25]  Current/Best:    6.69/  20.40 GFLOPS | Progress: (12/20) | 13.58 s
+[Task 18/25]  Current/Best:   14.03/  21.91 GFLOPS | Progress: (16/20) | 21.40 s
+[Task 18/25]  Current/Best:   14.70/  21.91 GFLOPS | Progress: (20/20) | 23.41 s Done.
 
 [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 19/25]  Current/Best:   19.01/  20.94 GFLOPS | Progress: (4/20) | 5.65 s
-[Task 19/25]  Current/Best:   11.05/  20.94 GFLOPS | Progress: (8/20) | 9.41 s
-[Task 19/25]  Current/Best:   18.01/  22.06 GFLOPS | Progress: (12/20) | 13.48 s
-[Task 19/25]  Current/Best:    2.79/  22.84 GFLOPS | Progress: (16/20) | 16.57 s
-[Task 19/25]  Current/Best:    9.30/  22.84 GFLOPS | Progress: (20/20) | 20.77 s Done.
+[Task 19/25]  Current/Best:    3.09/  21.43 GFLOPS | Progress: (4/20) | 6.61 s
+[Task 19/25]  Current/Best:    1.55/  21.65 GFLOPS | Progress: (8/20) | 11.42 s
+[Task 19/25]  Current/Best:    2.69/  21.65 GFLOPS | Progress: (12/20) | 14.97 s
+[Task 19/25]  Current/Best:   19.11/  21.65 GFLOPS | Progress: (16/20) | 19.98 s
+[Task 19/25]  Current/Best:   17.07/  21.65 GFLOPS | Progress: (20/20) | 24.24 s Done.
 
 [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 20/25]  Current/Best:   15.95/  16.62 GFLOPS | Progress: (4/20) | 15.09 s
-[Task 20/25]  Current/Best:   10.70/  18.91 GFLOPS | Progress: (8/20) | 18.79 s
-[Task 20/25]  Current/Best:   14.26/  18.91 GFLOPS | Progress: (12/20) | 30.28 s Done.
-
-[Task 20/25]  Current/Best:    9.38/  19.40 GFLOPS | Progress: (16/20) | 36.86 s
-[Task 20/25]  Current/Best:   13.30/  22.95 GFLOPS | Progress: (20/20) | 38.76 s Done.
-
-[Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 21/25]  Current/Best:   17.73/  17.73 GFLOPS | Progress: (4/20) | 4.83 s
-[Task 21/25]  Current/Best:   18.40/  18.40 GFLOPS | Progress: (8/20) | 7.17 s
-[Task 21/25]  Current/Best:    2.83/  18.40 GFLOPS | Progress: (12/20) | 18.55 s
-[Task 21/25]  Current/Best:    9.20/  22.26 GFLOPS | Progress: (16/20) | 21.98 s
-[Task 21/25]  Current/Best:   18.03/  22.26 GFLOPS | Progress: (20/20) | 26.15 s
+[Task 20/25]  Current/Best:    4.76/  21.55 GFLOPS | Progress: (4/20) | 14.38 s
+[Task 20/25]  Current/Best:   19.24/  22.63 GFLOPS | Progress: (8/20) | 21.71 s
+[Task 20/25]  Current/Best:    9.62/  22.63 GFLOPS | Progress: (12/20) | 26.88 s
+[Task 20/25]  Current/Best:   17.42/  22.63 GFLOPS | Progress: (16/20) | 29.33 s
+[Task 20/25]  Current/Best:   10.59/  22.63 GFLOPS | Progress: (20/20) | 37.25 s
+[Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
+ Done.
+
+[Task 21/25]  Current/Best:   13.41/  13.41 GFLOPS | Progress: (4/20) | 12.24 s
+[Task 21/25]  Current/Best:    7.28/  13.41 GFLOPS | Progress: (8/20) | 18.73 s
+[Task 21/25]  Current/Best:    4.71/  16.21 GFLOPS | Progress: (12/20) | 30.14 s
+[Task 21/25]  Current/Best:    3.77/  16.21 GFLOPS | Progress: (16/20) | 32.38 s
+[Task 21/25]  Current/Best:    8.47/  16.21 GFLOPS | Progress: (20/20) | 34.61 s Done.
+
 [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 22/25]  Current/Best:   11.68/  17.67 GFLOPS | Progress: (4/20) | 13.57 s
-[Task 22/25]  Current/Best:    5.41/  20.08 GFLOPS | Progress: (8/20) | 16.31 s
-[Task 22/25]  Current/Best:    8.08/  20.08 GFLOPS | Progress: (12/20) | 19.23 s
-[Task 22/25]  Current/Best:   17.72/  21.80 GFLOPS | Progress: (16/20) | 21.07 s
-[Task 22/25]  Current/Best:    2.79/  21.80 GFLOPS | Progress: (20/20) | 23.29 s
+[Task 22/25]  Current/Best:   19.65/  21.74 GFLOPS | Progress: (4/20) | 5.62 s
+[Task 22/25]  Current/Best:    7.67/  21.74 GFLOPS | Progress: (8/20) | 8.34 s
+[Task 22/25]  Current/Best:   11.71/  21.74 GFLOPS | Progress: (12/20) | 10.74 s
+[Task 22/25]  Current/Best:    5.22/  21.74 GFLOPS | Progress: (16/20) | 14.06 s
+[Task 22/25]  Current/Best:   18.73/  21.74 GFLOPS | Progress: (20/20) | 15.75 s Done.
+
 [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 23/25]  Current/Best:    6.37/  23.25 GFLOPS | Progress: (4/20) | 4.65 s
-[Task 23/25]  Current/Best:   21.41/  23.25 GFLOPS | Progress: (8/20) | 7.14 s
-[Task 23/25]  Current/Best:    6.36/  23.25 GFLOPS | Progress: (12/20) | 10.52 s
-[Task 23/25]  Current/Best:   13.81/  23.25 GFLOPS | Progress: (16/20) | 16.02 s
-[Task 23/25]  Current/Best:    2.78/  23.25 GFLOPS | Progress: (20/20) | 23.02 s Done.
+[Task 23/25]  Current/Best:   17.77/  19.48 GFLOPS | Progress: (4/20) | 7.99 s
+[Task 23/25]  Current/Best:   11.48/  22.55 GFLOPS | Progress: (8/20) | 11.78 s
+[Task 23/25]  Current/Best:   10.66/  22.55 GFLOPS | Progress: (12/20) | 14.29 s
+[Task 23/25]  Current/Best:    7.14/  22.55 GFLOPS | Progress: (16/20) | 19.84 s
+[Task 23/25]  Current/Best:    6.19/  22.55 GFLOPS | Progress: (20/20) | 22.68 s Done.
 
 [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 24/25]  Current/Best:    2.59/   7.73 GFLOPS | Progress: (4/20) | 4.47 s
-[Task 24/25]  Current/Best:    5.25/   7.73 GFLOPS | Progress: (8/20) | 15.45 s
-[Task 24/25]  Current/Best:    5.14/  10.15 GFLOPS | Progress: (12/20) | 26.39 s
-[Task 24/25]  Current/Best:    1.80/  10.15 GFLOPS | Progress: (16/20) | 29.47 s
-[Task 24/25]  Current/Best:    3.68/  10.15 GFLOPS | Progress: (20/20) | 40.50 s
-[Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
- Done.
- Done.
-
-[Task 25/25]  Current/Best:    9.42/  10.14 GFLOPS | Progress: (4/20) | 5.71 s
-[Task 25/25]  Current/Best:    3.14/  10.14 GFLOPS | Progress: (8/20) | 8.68 s
-[Task 25/25]  Current/Best:    4.49/  10.23 GFLOPS | Progress: (12/20) | 12.31 s
-[Task 25/25]  Current/Best:    1.60/  10.23 GFLOPS | Progress: (16/20) | 15.37 s
-[Task 25/25]  Current/Best:    5.51/  10.23 GFLOPS | Progress: (20/20) | 26.31 s
+[Task 24/25]  Current/Best:    5.89/   9.59 GFLOPS | Progress: (4/20) | 6.70 s
+[Task 24/25]  Current/Best:    1.83/   9.59 GFLOPS | Progress: (8/20) | 17.70 s
+[Task 24/25]  Current/Best:    3.02/   9.59 GFLOPS | Progress: (12/20) | 28.74 s
+[Task 24/25]  Current/Best:    7.37/   9.59 GFLOPS | Progress: (16/20) | 31.32 s
+[Task 24/25]  Current/Best:    2.87/   9.59 GFLOPS | Progress: (20/20) | 42.32 s
+[Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
+[Task 25/25]  Current/Best:    6.61/   6.61 GFLOPS | Progress: (4/20) | 10.61 s
+[Task 25/25]  Current/Best:    8.73/   8.73 GFLOPS | Progress: (8/20) | 12.07 s
+[Task 25/25]  Current/Best:    4.06/   8.83 GFLOPS | Progress: (12/20) | 14.39 s
+[Task 25/25]  Current/Best:    4.36/   8.83 GFLOPS | Progress: (16/20) | 19.42 s
+[Task 25/25]  Current/Best:    1.50/   9.37 GFLOPS | Progress: (20/20) | 21.50 s Done.
 </pre></div>
 </div>
 <p>The output from this tuning process will look something like this:</p>
@@ -1041,8 +1040,8 @@ improvement in comparing the optimized model to the unoptimized model.</p>
 <span class="nb">print</span><span class="p">(</span><span class="s2">&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;: 381.63107256998046, &#39;median&#39;: 380.9882759500397, &#39;std&#39;: 1.7423971195174}
-unoptimized: {&#39;mean&#39;: 472.81652373001634, &#39;median&#39;: 473.12350920001336, &#39;std&#39;: 2.307640356318348}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {&#39;mean&#39;: 420.20613707998564, &#39;median&#39;: 419.5116467000844, &#39;std&#39;: 3.1023702175735526}
+unoptimized: {&#39;mean&#39;: 491.0514597600195, &#39;median&#39;: 490.92375170002924, &#39;std&#39;: 1.5121823348393049}
 </pre></div>
 </div>
 </div>
@@ -1056,7 +1055,7 @@ models.</p>
 <p>Here we presented a simple example using ResNet-50 v2 locally. However, TVM
 supports many more features including cross-compilation, remote execution and
 profiling/benchmarking.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 13 minutes  15.681 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 13 minutes  27.631 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 65ae871648..fd6b02cbc5 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>1.143e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.21e-07 secs/op
 </pre></div>
 </div>
 </div>
diff --git a/docs/tutorial/intro_topi.html b/docs/tutorial/intro_topi.html
index a636c3f9ae..c42cc3f0cf 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, 0x1311d6e0)), stage(b, placeholder(b, 0x130ed5d0)), 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, 0x11bfa320)), stage(b, placeholder(b, 0x117f34f0)), 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 141c9910c5..6d6967c6e4 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>16:47.420</strong> total execution time for <strong>tutorial</strong> files:</p>
+<p><strong>17:16.815</strong> total execution time for <strong>tutorial</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
@@ -369,46 +369,46 @@
 </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>13:15.681</p></td>
+<td><p>13:27.631</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>01:25.286</p></td>
+<td><p>01:41.544</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>00:57.866</p></td>
+<td><p>01:00.327</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="relay_quick_start.html#sphx-glr-tutorial-relay-quick-start-py"><span class="std std-ref">Quick Start Tutorial for Compiling Deep Learning Models</span></a> (<code class="docutils literal notranslate"><span class="pre">relay_quick_start.py</span></code>)</p></td>
-<td><p>00:42.087</p></td>
+<td><p>00:43.769</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>00:24.609</p></td>
+<td><p>00:21.185</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>00:00.864</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tensor_ir_blitz_course.html#sphx-glr-tutorial-tensor-ir-blitz-course-py"><span class="std std-ref">Blitz Course to TensorIR</span></a> (<code class="docutils literal notranslate"><span class="pre">tensor_ir_blitz_course.py</span></code>)</p></td>
+<td><p>00:01.271</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>00:00.859</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="intro_topi.html#sphx-glr-tutorial-intro-topi-py"><span class="std std-ref">Introduction to TOPI</span></a> (<code class="docutils literal notranslate"><span class="pre">intro_topi.py</span></code>)</p></td>
+<td><p>00:00.905</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>00:00.170</p></td>
+<td><p>00:00.182</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>
 <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="tvmc_command_line_driver.html#sphx-glr-tutorial-tvmc-command-line-driver-py"><span class="std std-ref">Compiling and Optimizing a Model with TVMC</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_command_line_driver.py</span></code>)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tvmc_python.html#sphx-glr-tutorial-tvmc-python-py"><span class="std std-ref">Getting Starting using TVMC Python: a high-level API for TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_python.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0 MB</p></td>
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-<tr class="row-odd"><td><p><a class="reference internal" href="tvmc_python.html#sphx-glr-tutorial-tvmc-python-py"><span class="std std-ref">Getting Starting using TVMC Python: a high-level API for TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_python.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tvmc_command_line_driver.html#sphx-glr-tutorial-tvmc-command-line-driver-py"><span class="std std-ref">Compiling and Optimizing a Model with TVMC</span></a> (<code class="docutils literal notranslate"><span class="pre">tvmc_command_line_driver.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
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diff --git a/docs/tutorial/tensor_expr_get_started.html b/docs/tutorial/tensor_expr_get_started.html
index a88679ba99..af9a2dde67 100644
--- a/docs/tutorial/tensor_expr_get_started.html
+++ b/docs/tutorial/tensor_expr_get_started.html
@@ -569,8 +569,8 @@ helper function to run a profile of the TVM generated code.</p>
 <span class="n">evaluate_addition</span><span class="p">(</span><span class="n">fadd</span><span class="p">,</span> <a href="../reference/api/python/target.html#tvm.target.Target" title="tvm.target.Target" class="sphx-glr-backref-module-tvm-target sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">tgt</span></a><span class="p">,</span> <span class="s2">&quot;naive&quot;</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#list" ti [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000008
-naive: 0.000007
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000007
+naive: 0.000008
 </pre></div>
 </div>
 </div>
@@ -664,7 +664,7 @@ factor to be the number of threads on your CPU.</p>
 <span class="nb">print</span><span class="p">(</span><a href="../reference/api/python/driver.html#tvm.lower" title="tvm.lower" class="sphx-glr-backref-module-tvm sphx-glr-backref-type-py-function"><span class="n">tvm</span><span class="o">.</span><span class="n">lower</span></a><span class="p">(</span><a href="../reference/api/python/te.html#tvm.te.Schedule" title="tvm.te.Schedule" class="sphx-glr-backref-module-tvm-te sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector: 0.000040
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector: 0.000043
 # 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    7.6211700070416555e-06                   1.0
-   naive              6.7833e-06      0.8900601867866093
-parallel              6.9884e-06      0.9169720651216281
-  vector    3.979460000000001e-05      5.221586706927072
+   numpy    6.810990016674623e-06                    1.0
+   naive              7.8756e-06      1.1563076705029673
+parallel    7.0258000000000006e-06    1.0315387311975912
+  vector    4.2536899999999996e-05     6.245332895197531
 </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: 0.016847
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.017763
 </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: 3.256538
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>none: 3.431128
 </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: 0.327842
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>blocking: 0.291657
 </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: 0.261305
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vectorization: 0.273722
 # 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: 0.110385
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>loop permutation: 0.115916
 # 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: 0.104061
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array packing: 0.107565
 # 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: 0.107764
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>block caching: 0.113049
 # 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: 0.127950
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallelization: 0.133392
 # 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             3.256538284                     1.0
-        blocking            0.3278417958     0.10067186908587868
-   vectorization            0.2613052621     0.08024019351587024
-loop permutation            0.1103850672       0.033896443884091
-   array packing     0.10406077660000002    0.031954415248630935
-   block caching     0.10776395889999998    0.033091568254997976
- parallelization            0.1279501574    0.039290235901307764
+            none      3.4311277783999996                     1.0
+        blocking            0.2916568338     0.08500319796775542
+   vectorization            0.2737218407     0.07977605568150589
+loop permutation     0.11591623649999998     0.03378371310731364
+   array packing            0.1075645505    0.031349619555748345
+   block caching            0.1130494898     0.03294820161221659
+ parallelization            0.1333924645     0.03887714859812171
 </pre></div>
 </div>
 <p>Note that the outputs on the web page reflect the running times on a
@@ -1507,6 +1507,7 @@ is</p>
 you can build generic templates of the matrix multiplication and other
 operations with tunable parameters that allows you to automatically optimize
 the computation for specific platforms.</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  0.327 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-tensor-expr-get-started-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/40a01cffb015a67aaec0fad7e27cf80d/tensor_expr_get_started.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tensor_expr_get_started.py</span></code></a></p>