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Posted to commits@tvm.apache.org by tq...@apache.org on 2024/02/20 05:21:34 UTC

(tvm-site) branch asf-site updated: deploying docs (apache/tvm@40ec46970f7e1b94a0eec3b4da8868d1ec179d69)

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 571dae9350 deploying docs (apache/tvm@40ec46970f7e1b94a0eec3b4da8868d1ec179d69)
571dae9350 is described below

commit 571dae9350d85e1a325316f8186e1efc869c2402
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Tue Feb 20 05:21:27 2024 +0000

    deploying docs (apache/tvm@40ec46970f7e1b94a0eec3b4da8868d1ec179d69)
---
 .../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       |  20 +-
 .../how_to/extend_tvm/sg_execution_times.rst.txt   |   8 +-
 .../how_to/extend_tvm/use_pass_instrument.rst.txt  |  16 +-
 .../optimize_operators/opt_conv_cuda.rst.txt       |   2 +-
 .../optimize_operators/opt_conv_tensorcore.rst.txt |   2 +-
 .../how_to/optimize_operators/opt_gemm.rst.txt     |  16 +-
 .../optimize_operators/sg_execution_times.rst.txt  |   8 +-
 .../sg_execution_times.rst.txt                     |  14 +-
 .../tune_conv2d_layer_cuda.rst.txt                 |   2 +-
 .../tune_network_cuda.rst.txt                      |   4 +-
 .../tune_network_x86.rst.txt                       |   4 +-
 .../tune_with_autotvm/sg_execution_times.rst.txt   |   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     |   4 +-
 docs/_sources/tutorial/autotvm_matmul_x86.rst.txt  |  20 +-
 docs/_sources/tutorial/autotvm_relay_x86.rst.txt   |  55 +++--
 .../tutorial/cross_compilation_and_rpc.rst.txt     |   2 +-
 docs/_sources/tutorial/intro_topi.rst.txt          |   2 +-
 docs/_sources/tutorial/sg_execution_times.rst.txt  |  18 +-
 .../tutorial/tensor_expr_get_started.rst.txt       |  51 ++--
 docs/commit_hash                                   |   2 +-
 docs/how_to/compile_models/from_darknet.html       |   2 +-
 docs/how_to/compile_models/from_oneflow.html       |  12 +-
 docs/how_to/compile_models/from_paddle.html        |   1 -
 docs/how_to/compile_models/from_pytorch.html       |  12 +-
 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 |  27 ++-
 .../deploy_models/deploy_model_on_android.html     |   2 +-
 .../deploy_object_detection_pytorch.html           |  48 ++--
 docs/how_to/deploy_models/deploy_prequantized.html |  10 +-
 .../deploy_models/deploy_prequantized_tflite.html  |   2 +-
 docs/how_to/deploy_models/sg_execution_times.html  |  24 +-
 docs/how_to/extend_tvm/sg_execution_times.html     |   8 +-
 docs/how_to/extend_tvm/use_pass_instrument.html    |  16 +-
 docs/how_to/optimize_operators/opt_conv_cuda.html  |   2 +-
 .../optimize_operators/opt_conv_tensorcore.html    |   2 +-
 docs/how_to/optimize_operators/opt_gemm.html       |  16 +-
 .../optimize_operators/sg_execution_times.html     |   8 +-
 .../sg_execution_times.html                        |  18 +-
 .../tune_conv2d_layer_cuda.html                    |   2 +-
 .../tune_with_autoscheduler/tune_network_cuda.html |   4 +-
 .../tune_with_autoscheduler/tune_network_x86.html  |   4 +-
 .../tune_with_autotvm/sg_execution_times.html      |   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  |   4 +-
 docs/how_to/work_with_microtvm/micro_train.html    |  16 +-
 .../work_with_microtvm/sg_execution_times.html     |  18 +-
 .../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 +-
 docs/reference/api/typedoc/assets/search.js        |   2 +-
 .../api/typedoc/classes/ArtifactCache.html         |  44 +++-
 docs/reference/api/typedoc/classes/DLDataType.html |  18 +-
 docs/reference/api/typedoc/classes/DLDevice.html   |  16 +-
 docs/reference/api/typedoc/classes/Instance.html   | 110 ++++-----
 docs/reference/api/typedoc/classes/Module.html     |  16 +-
 docs/reference/api/typedoc/classes/NDArray.html    |  34 +--
 docs/reference/api/typedoc/classes/RPCServer.html  |  20 +-
 docs/reference/api/typedoc/classes/Scalar.html     |  12 +-
 docs/reference/api/typedoc/classes/TVMArray.html   |  20 +-
 docs/reference/api/typedoc/classes/TVMObject.html  |  16 +-
 .../api/typedoc/classes/VirtualMachine.html        |  14 +-
 .../classes/_internal_.CachedCallStack.html        |  40 ++--
 .../classes/_internal_.CanvasRenderManager.html    |  14 +-
 .../typedoc/classes/_internal_.Environment.html    |  18 +-
 .../api/typedoc/classes/_internal_.FFILibrary.html |  26 +-
 .../api/typedoc/classes/_internal_.Memory.html     |  40 ++--
 .../typedoc/classes/_internal_.PackedFuncCell.html |  12 +-
 .../typedoc/classes/_internal_.RuntimeContext.html |  58 ++---
 .../api/typedoc/classes/_internal_.TVMString.html  |  18 +-
 .../typedoc/classes/_internal_.WebGPUContext.html  |  32 +--
 .../typedoc/enums/_internal_.RPCServerState.html   |  18 +-
 docs/reference/api/typedoc/functions/assert.html   |   6 +-
 .../api/typedoc/functions/createPolyfillWASI.html  |   6 +-
 ...tePolyfillWASI.html => deleteNDArrayCache.html} |  28 ++-
 .../api/typedoc/functions/detectGPUDevice.html     |   6 +-
 .../api/typedoc/functions/hasNDArrayInCache.html   |   6 +-
 .../api/typedoc/functions/instantiate.html         |   6 +-
 docs/reference/api/typedoc/functions/wasmPath.html |   6 +-
 docs/reference/api/typedoc/index.html              |   3 +
 .../api/typedoc/interfaces/Disposable.html         |   8 +-
 .../typedoc/interfaces/GPUDeviceDetectOutput.html  |  12 +-
 .../api/typedoc/interfaces/InitProgressReport.html |  14 +-
 .../api/typedoc/interfaces/LibraryProvider.html    |  10 +-
 ....html => _internal_.ArtifactCacheTemplate.html} |  91 ++++---
 .../interfaces/_internal_.FunctionInfo.html        |  12 +-
 .../interfaces/_internal_.NDArrayCacheEntry.html   |  18 +-
 .../interfaces/_internal_.NDArrayShardEntry.html   |  14 +-
 docs/reference/api/typedoc/modules/_internal_.html |   5 +-
 .../api/typedoc/types/InitProgressCallback.html    |   6 +-
 docs/reference/api/typedoc/types/PackedFunc.html   |   6 +-
 .../types/_internal_.FObjectConstructor.html       |   6 +-
 .../types/_internal_.FTVMWasmAllocSpace.html       |   6 +-
 .../types/_internal_.FTVMWasmFreeSpace.html        |   6 +-
 .../types/_internal_.FTVMWasmPackedCFunc.html      |   6 +-
 .../api/typedoc/types/_internal_.Pointer.html      |   6 +-
 .../typedoc/types/_internal_.TVMObjectBase.html    |   6 +-
 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       |   4 +-
 docs/tutorial/autotvm_matmul_x86.html              |  20 +-
 docs/tutorial/autotvm_relay_x86.html               | 265 ++++++++++-----------
 docs/tutorial/cross_compilation_and_rpc.html       |   2 +-
 docs/tutorial/intro_topi.html                      |   2 +-
 docs/tutorial/sg_execution_times.html              |  18 +-
 docs/tutorial/tensor_expr_get_started.html         |  47 ++--
 136 files changed, 1090 insertions(+), 942 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 c9393e31ba..17bffb0fb8 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  33.373 seconds)
+   **Total running time of the script:** ( 1 minutes  30.061 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 387c359f76..2d1a8b8f0a 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]      19%|#9        | 7.99M/41.5M [00:00<00:00, 75.9MB/s]      39%|###8      | 16.0M/41.5M [00:00<00:00, 47.8MB/s]      58%|#####7    | 24.0M/41.5M [00:00<00:00, 53.0MB/s]      77%|#######7  | 32.0M/41.5M [00:00<00:00, 58.5MB/s]     100%|##########| 41.5M/41.5M [00:00<00:00, 67.2MB/s]
+       0%|          | 0.00/41.5M [00:00<?, ?B/s]      19%|#9        | 7.99M/41.5M [00:00<00:00, 47.8MB/s]      35%|###4      | 14.3M/41.5M [00:00<00:00, 33.7MB/s]      54%|#####3    | 22.3M/41.5M [00:00<00:00, 44.2MB/s]      65%|######5   | 27.0M/41.5M [00:00<00:00, 44.9MB/s]      77%|#######7  | 32.0M/41.5M [00:00<00:00, 45.8MB/s]      92%|#########2| 38.3M/41.5M [00:00<00:00, 48.5MB/s]     100%|##########| 41.5M/41.5M [00:00<00:00, 45.0MB/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 148f460bc0..8df75c9e33 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -207,11 +207,6 @@ Look up prediction top 1 index in 1000 class synset.
 
 
 
-.. rst-class:: sphx-glr-timing
-
-   **Total running time of the script:** ( 1 minutes  1.572 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 8523a37489..c7637bee07 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, 59.1MB/s]      39%|###8      | 17.3M/44.7M [00:00<00:00, 78.5MB/s]      56%|#####6    | 25.1M/44.7M [00:00<00:00, 74.6MB/s]      82%|########1 | 36.4M/44.7M [00:00<00:00, 90.3MB/s]     100%|##########| 44.7M/44.7M [00:00<00:00, 81.9MB/s]
+       0%|          | 0.00/44.7M [00:00<?, ?B/s]      18%|#7        | 7.99M/44.7M [00:00<00:00, 54.6MB/s]      36%|###5      | 16.0M/44.7M [00:00<00:00, 64.9MB/s]      54%|#####3    | 24.0M/44.7M [00:00<00:00, 61.8MB/s]      68%|######7   | 30.3M/44.7M [00:00<00:00, 57.2MB/s]      80%|########  | 35.8M/44.7M [00:00<00:00, 40.8MB/s]      90%|########9 | 40.2M/44.7M [00:00<00:00, 39.4MB/s]     100%|##########| 44.7M/44.7M [00:00<00:00, 50.6MB/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 524ae745d6..7801140da8 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -430,7 +430,7 @@ Run the corresponding model on tensorflow
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  30.855 seconds)
+   **Total running time of the script:** ( 1 minutes  26.508 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 a3e9b5191a..7c1012b439 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
 =================
-**06:35.654** total execution time for **how_to_compile_models** files:
+**06:19.158** total execution time for **how_to_compile_models** files:
 
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:33.373 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)       | 01:30.061 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:30.855 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:26.508 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 01:01.572 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)         | 00:59.315 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:42.563 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``)       | 00:41.591 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:38.625 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)         | 00:36.002 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:28.794 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)       | 00:27.363 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:26.099 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)           | 00:25.622 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:10.887 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)         | 00:09.988 | 0.0 MB |
 +-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.887 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)             | 00:02.707 | 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 f3e8d9b061..99f4f22d37 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno.rst.txt
@@ -673,7 +673,7 @@ well as provides information about the model's performance
     Evaluate inference time cost...
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-     4120.9131    4120.8228    4124.4875    4118.7590      1.7898                  
+     3992.2676    3992.2148    4003.9555    3986.0833      4.8210                  
 
 
 
@@ -681,7 +681,7 @@ well as provides information about the model's performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  19.942 seconds)
+   **Total running time of the script:** ( 1 minutes  16.474 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 52dc0cb979..76bab4e1c9 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       8380416/102967424 [=>............................] - ETA: 1s      16769024/102967424 [===>..........................] - ETA: 1s      25157632/102967424 [======>.......................] - ETA: 1s      33546240/102967424 [========>.....................] - ETA: 0s      41934848/102967424 [===========>..................] - ETA: 0s      48578560/102967424 [=============>................] - ETA: 0s      50323456/102967424 [=============>................] - ETA: 0s
       58712064/102967424 [================>.............] - ETA: 0s      67100672/102967424 [==================>...........] - ETA: 0s      75489280/102967424 [====================>.........] - ETA: 0s      83877888/102967424 [=======================>......] - ETA: 0s      90521600/102967424 [=========================>....] - ETA: 0s      92266496/102967424 [=========================>....] - ETA: 0s     100646912/102967424 [============================>.] - ETA: 0s     102850560/102967424 [============================>.] -
  ETA: 0s     102967424/102967424 [==============================] - 1s 0us/step
+          8192/102967424 [..............................] - ETA: 0s       8380416/102967424 [=>............................] - ETA: 0s      16769024/102967424 [===>..........................] - ETA: 0s      24936448/102967424 [======>.......................] - ETA: 0s      29704192/102967424 [=======>......................] - ETA: 0s      33546240/102967424 [========>.....................] - ETA: 0s      40189952/102967424 [==========>...................] - ETA: 0s      44130304/102967424 [===========>..................] - ETA: 0s
       50323456/102967424 [=============>................] - ETA: 0s      60497920/102967424 [================>.............] - ETA: 0s      68493312/102967424 [==================>...........] - ETA: 0s      75202560/102967424 [====================>.........] - ETA: 0s      79880192/102967424 [======================>.......] - ETA: 0s      86237184/102967424 [========================>.....] - ETA: 0s      92839936/102967424 [==========================>...] - ETA: 0s      99180544/102967424 [===========================>..] -
  ETA: 0s     102965248/102967424 [============================>.] - ETA: 0s     102967424/102967424 [==============================] - 1s 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 f2b20ee9f6..49cfbdb41a 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)  
-      15.5916      15.5247      16.1442      15.0202       0.2958                  
+      14.0519      13.7847      14.6994      13.7134       0.4063                  
 
 
 
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 bed7ea538b..4fef78bf92 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<00:02, 73.1MB/s]       9%|9         | 16.0M/170M [00:00<00:02, 59.2MB/s]      14%|#4        | 24.0M/170M [00:00<00:02, 67.3MB/s]      19%|#8        | 32.0M/170M [00:00<00:02, 68.0MB/s]      24%|##3       | 40.0M/170M [00:00<00:01, 70.0MB/s]      28%|##8       | 48.0M/170M [00:00<00:01, 72.9MB/s]      33%|###3      | 56.3M/170M [00:00<00:01, 77.2MB/s]      38%|###7      | 64.1M/170M [00:00<00:01, 76.5MB/s]      42%|####2     | 72.0M/170M [00:01<00:01, 75.9MB/s]      48%|####7     | 81.3M/170M [00:01<00:01, 82.2MB/s]      53%|#####2    | 89.2M/170M [00:01<00:01, 51.0MB/s]      57%|#####6    | 96.0M/170M [00:01<00:01, 53.8MB/s]      61%|######1   | 104M/170M [00:01<00:01, 58.8MB/s]       66%|######5   | 112M/170M [00:01<00:00, 63.6MB/s]      72%|#######1  | 122M/170M [00:01<00:00, 68.6MB/s]      76%|#######6  | 129M/170M [00:02<00:00, 58.5MB/s]      81%|########1 | 138M/170M [00:02<00:00, 66.1MB/s]  
     85%|########5 | 145M/170M [00:02<00:00, 67.5MB/s]      89%|########9 | 152M/170M [00:02<00:00, 65.4MB/s]      95%|#########4| 161M/170M [00:02<00:00, 71.9MB/s]     100%|##########| 170M/170M [00:02<00:00, 68.9MB/s]
+       0%|          | 0.00/170M [00:00<?, ?B/s]       5%|4         | 7.99M/170M [00:00<00:02, 71.8MB/s]       9%|9         | 16.0M/170M [00:00<00:02, 71.1MB/s]      14%|#4        | 24.0M/170M [00:00<00:02, 68.5MB/s]      18%|#7        | 30.5M/170M [00:00<00:02, 67.1MB/s]      22%|##1       | 36.9M/170M [00:00<00:02, 50.0MB/s]      27%|##7       | 46.3M/170M [00:00<00:02, 58.5MB/s]      31%|###       | 52.3M/170M [00:00<00:02, 55.2MB/s]      34%|###4      | 57.8M/170M [00:01<00:02, 49.2MB/s]      38%|###7      | 64.0M/170M [00:01<00:02, 52.3MB/s]      42%|####2     | 72.0M/170M [00:01<00:01, 52.0MB/s]      47%|####7     | 80.0M/170M [00:01<00:01, 54.7MB/s]      52%|#####1    | 88.0M/170M [00:01<00:01, 59.4MB/s]      56%|#####5    | 94.3M/170M [00:01<00:01, 49.2MB/s]      60%|######    | 102M/170M [00:01<00:01, 53.3MB/s]       63%|######3   | 108M/170M [00:02<00:01, 53.0MB/s]      66%|######6   | 113M/170M [00:02<00:01, 51.7MB/s]      73%|#######2  | 123M/170M [00:02<00:00, 66.1MB/s] 
      77%|#######6  | 130M/170M [00:02<00:00, 55.0MB/s]      80%|########  | 136M/170M [00:02<00:00, 55.1MB/s]      85%|########4 | 144M/170M [00:02<00:00, 53.0MB/s]      88%|########8 | 150M/170M [00:02<00:00, 54.2MB/s]      92%|#########1| 156M/170M [00:02<00:00, 50.8MB/s]      95%|#########4| 161M/170M [00:03<00:00, 38.2MB/s]      98%|#########8| 167M/170M [00:03<00:00, 43.8MB/s]     100%|##########| 170M/170M [00:03<00:00, 52.7MB/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  37.507 seconds)
+   **Total running time of the script:** ( 3 minutes  19.059 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 d6fc3bdb3c..a526a58e86 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]      49%|####8     | 6.61M/13.6M [00:00<00:00, 69.2MB/s]      97%|#########7| 13.2M/13.6M [00:00<00:00, 62.7MB/s]     100%|##########| 13.6M/13.6M [00:00<00:00, 64.7MB/s]
+       0%|          | 0.00/13.6M [00:00<?, ?B/s]      59%|#####8    | 7.99M/13.6M [00:00<00:00, 57.3MB/s]      99%|#########9| 13.5M/13.6M [00:00<00:00, 52.8MB/s]     100%|##########| 13.6M/13.6M [00:00<00:00, 53.8MB/s]
 
 
 
@@ -409,7 +409,7 @@ Here we give an example of how to measure performance of TVM compiled models.
 
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-      89.0116      88.9525      89.5557      88.6711       0.2051                  
+      85.9024      85.8525      94.0248      85.4598       0.8446                  
 
 
 
@@ -457,7 +457,7 @@ TODO
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  28.912 seconds)
+   **Total running time of the script:** ( 1 minutes  23.893 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 a74df63813..2c139d292d 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized_tflite.rst.txt
@@ -423,7 +423,7 @@ Here we give an example of how to measure performance of TVM compiled models.
 
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-      110.0844     109.9932     117.5614     109.4831      0.7955                  
+      104.0844     103.7407     111.7406     102.8417      1.3186                  
 
 
 
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 f64c67ec28..06a34e38f4 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
 =================
-**09:55.389** total execution time for **how_to_deploy_models** files:
+**09:17.971** 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``) | 03:37.507 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:19.059 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:28.912 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)                         | 01:23.893 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:19.942 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``)                   | 01:16.474 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:51.386 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:48.465 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)                 | 00:51.351 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)           | 00:48.277 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:46.699 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``)         | 00:45.603 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:29.809 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``)                       | 00:28.112 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:29.772 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)                       | 00:28.078 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)                                     | 00:00.010 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)                                     | 00:00.009 | 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 f849201d81..84da8519dd 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
 =================
-**00:04.129** total execution time for **how_to_extend_tvm** files:
+**00:04.029** total execution time for **how_to_extend_tvm** files:
 
 +-------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)     | 00:02.898 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)     | 00:02.840 | 0.0 MB |
 +-------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)               | 00:01.223 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)               | 00:01.181 | 0.0 MB |
 +-------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``) | 00:00.008 | 0.0 MB |
+| :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 e9e591a08c..0e0e6ef1fe 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: 25251us [25251us] (48.11%; 48.11%)
-    FoldScaleAxis: 27240us [8us] (51.89%; 51.89%)
-            FoldConstant: 27232us [1802us] (51.88%; 99.97%)
-                    InferType: 25430us [25430us] (48.45%; 93.38%)
+    InferType: 24147us [24147us] (48.13%; 48.13%)
+    FoldScaleAxis: 26029us [8us] (51.87%; 51.87%)
+            FoldConstant: 26021us [1789us] (51.86%; 99.97%)
+                    InferType: 24231us [24231us] (48.29%; 93.12%)
 
 
 
@@ -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: 25570us [25570us] (48.75%; 48.75%)
-    FoldScaleAxis: 26881us [8us] (51.25%; 51.25%)
-            FoldConstant: 26873us [1923us] (51.23%; 99.97%)
-                    InferType: 24950us [24950us] (47.57%; 92.84%)
+    InferType: 24084us [24084us] (47.96%; 47.96%)
+    FoldScaleAxis: 26134us [8us] (52.04%; 52.04%)
+            FoldConstant: 26126us [1835us] (52.02%; 99.97%)
+                    InferType: 24290us [24290us] (48.37%; 92.98%)
 
 
 
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 f200e34d07..dc845266ca 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: 53.534080 ms
+    Convolution: 53.516769 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 151b6f1b1d..050d54c41f 100644
--- a/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_conv_tensorcore.rst.txt
@@ -598,7 +598,7 @@ be able to run on our build server
 
  .. code-block:: none
 
-    conv2d with tensor core: 12.273584 ms
+    conv2d with tensor core: 12.267178 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 f08a8df63b..c89c0ac928 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: 0.018615
-    Baseline: 3.445997
+    Numpy running time: 0.015412
+    Baseline: 3.349918
 
 
 
@@ -227,7 +227,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
 
  .. code-block:: none
 
-    Opt1: 0.303034
+    Opt1: 0.280479
 
 
 
@@ -318,7 +318,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
 
  .. code-block:: none
 
-    Opt2: 0.274051
+    Opt2: 0.257398
 
 
 
@@ -406,7 +406,7 @@ the access pattern for A matrix is more cache friendly.
 
  .. code-block:: none
 
-    Opt3: 0.116609
+    Opt3: 0.110577
 
 
 
@@ -523,7 +523,7 @@ flattening.
 
  .. code-block:: none
 
-    Opt4: 0.107666
+    Opt4: 0.103413
 
 
 
@@ -635,7 +635,7 @@ write to C when all the block results are ready.
 
  .. code-block:: none
 
-    Opt5: 0.112580
+    Opt5: 0.094043
 
 
 
@@ -748,7 +748,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
 
  .. code-block:: none
 
-    Opt6: 0.135795
+    Opt6: 0.111092
 
 
 
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 82929b6a8d..744c92fb75 100644
--- a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**00:34.281** total execution time for **how_to_optimize_operators** files:
+**00:31.515** total execution time for **how_to_optimize_operators** files:
 
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:31.199 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)                       | 00:28.485 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.885 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.837 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.196 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)             | 00:01.193 | 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 c4a707ddd7..48e9db67f7 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
 =================
-**03:37.601** total execution time for **how_to_tune_with_autoscheduler** files:
+**03:28.361** 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``)             | 01:34.624 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)             | 01:31.417 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:12.769 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)           | 01:09.919 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:17.598 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)             | 00:16.794 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:16.315 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:15.734 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)           | 00:16.194 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:14.400 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)               | 00:00.101 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)               | 00:00.097 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
index e4320ab4cc..2797b93c6e 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
@@ -766,7 +766,7 @@ We build the binary and check its correctness and performance.
 
  .. code-block:: none
 
-    Execution time of this operator: 0.337 ms
+    Execution time of this operator: 0.335 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 fc1cfb53d4..1444caed18 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)  
-       3.1982       3.1980       3.1987       3.1978       0.0004                  
+       3.2060       3.2050       3.2094       3.2036       0.0025                  
 
 
 
@@ -660,7 +660,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  12.769 seconds)
+   **Total running time of the script:** ( 1 minutes  9.919 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 2d51c8b67e..e40830b3f4 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)  
-      766.2548     763.7351     771.9287     763.1004      4.0205                  
+      707.6538     708.1811     708.6993     706.0811      1.1320                  
 
 
 
@@ -682,7 +682,7 @@ Other Tips
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  34.624 seconds)
+   **Total running time of the script:** ( 1 minutes  31.417 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 d6af5155c2..b919f891e8 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
 =================
-**00:23.999** total execution time for **how_to_tune_with_autotvm** files:
+**00:22.491** 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``)           | 00:23.962 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)           | 00:22.456 | 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``)               | 00:00.020 | 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 915370d13f..41624eb010 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: 0.037035
+    Time cost of this operator: 0.037219
 
 
 
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 14698b589e..aea4685470 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  305.1     98.712   (1, 2, 10, 10, 3)  2       1        [305.1]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       3.027     0.979    (1, 6, 10, 10)     1       1        [3.027]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.953     0.308    (1, 1, 10, 10, 3)  1       1        [0.953]           
-    Total_time                                    -                                             309.08    -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  293.4     98.723   (1, 2, 10, 10, 3)  2       1        [293.4]           
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       2.872     0.966    (1, 6, 10, 10)     1       1        [2.872]           
+    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                                    -                                             297.195   -        -                  -       -        -                 
 
 
 
@@ -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  102.4     97.437   (1, 6, 10, 10, 1)  2       1        [102.4]           
-    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.845     1.755    (1, 6, 10, 10)     1       1        [1.845]           
-    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.849     0.808    (1, 3, 10, 10, 1)  1       1        [0.849]           
-    Total_time                                    -                                             105.093   -        -                  -       -        -                 
+    tvmgen_default_fused_nn_contrib_conv2d_NCHWc  tvmgen_default_fused_nn_contrib_conv2d_NCHWc  97.625    97.35    (1, 6, 10, 10, 1)  2       1        [97.625]          
+    tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.715     1.711    (1, 6, 10, 10)     1       1        [1.715]           
+    tvmgen_default_fused_layout_transform         tvmgen_default_fused_layout_transform         0.942     0.939    (1, 1, 10, 10, 3)  1       1        [0.942]           
+    Total_time                                    -                                             100.282   -        -                  -       -        -                 
 
 
 
@@ -439,7 +439,7 @@ Timing the tuned program
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  25.345 seconds)
+   **Total running time of the script:** ( 1 minutes  26.204 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 5a45ca0207..d25680ad4b 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]     100%|##########| 3.42M/3.42M [00:00<00:00, 209MB/s]
+       0%|          | 0.00/3.42M [00:00<?, ?B/s]     100%|##########| 3.42M/3.42M [00:00<00:00, 43.6MB/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  28.383 seconds)
+   **Total running time of the script:** ( 1 minutes  26.137 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 c34f6073e3..582d168edf 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/tmp11ulehpn/images/random'
+    '/tmp/tmpcpdsqncq/images/random'
 
 
 
@@ -317,8 +317,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
 
  .. code-block:: none
 
-    /tmp/tmp11ulehpn/images/target contains 8144 images
-    /tmp/tmp11ulehpn/images/random contains 5000 images
+    /tmp/tmpcpdsqncq/images/target contains 8144 images
+    /tmp/tmpcpdsqncq/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: 0.2202 - accuracy: 0.9232 - val_loss: 0.1044 - val_accuracy: 0.9600 - 39s/epoch - 120ms/step
+    328/328 - 38s - loss: 0.2148 - accuracy: 0.9246 - val_loss: 0.1094 - val_accuracy: 0.9649 - 38s/epoch - 117ms/step
     Epoch 2/3
-    328/328 - 36s - loss: 0.0953 - accuracy: 0.9665 - val_loss: 0.0923 - val_accuracy: 0.9698 - 36s/epoch - 108ms/step
+    328/328 - 34s - loss: 0.1033 - accuracy: 0.9628 - val_loss: 0.1250 - val_accuracy: 0.9532 - 34s/epoch - 105ms/step
     Epoch 3/3
-    328/328 - 35s - loss: 0.0650 - accuracy: 0.9740 - val_loss: 0.1052 - val_accuracy: 0.9664 - 35s/epoch - 108ms/step
+    328/328 - 34s - loss: 0.0643 - accuracy: 0.9751 - val_loss: 0.1263 - val_accuracy: 0.9619 - 34s/epoch - 104ms/step
 
-    <keras.callbacks.History object at 0x7f378e905dc0>
+    <keras.callbacks.History object at 0x7ef7b8e20d00>
 
 
 
@@ -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  7.031 seconds)
+   **Total running time of the script:** ( 4 minutes  34.370 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 326a918e3f..25fcd0e134 100644
--- a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
@@ -5,20 +5,20 @@
 
 Computation times
 =================
-**07:30.181** total execution time for **how_to_work_with_microtvm** files:
+**07:54.614** total execution time for **how_to_work_with_microtvm** files:
 
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:07.031 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``)           | 04:34.370 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:28.383 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:26.204 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)     | 01:25.345 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``)       | 01:26.137 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:11.975 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``)               | 00:11.407 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:09.108 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:08.794 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:08.339 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)         | 00:07.702 | 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 64d68a0342..d1ad3db254 100644
--- a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
 
 Computation times
 =================
-**00:38.558** total execution time for **how_to_work_with_relay** files:
+**00:37.027** total execution time for **how_to_work_with_relay** files:
 
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:33.507 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:32.096 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.200 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)           | 00:03.089 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:01.843 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)                             | 00:01.836 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)                 | 00:00.007 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
index 0cb7994c5f..4ad9c378e8 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 0x7f3c49730940>
+    <function my_cuda_math_rule at 0x7ef7bf48cee0>
 
 
 
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 5fa34b6047..bd0cebb5a8 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
 =================
-**00:05.336** total execution time for **how_to_work_with_schedules** files:
+**00:05.266** total execution time for **how_to_work_with_schedules** files:
 
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.532 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)                 | 00:02.516 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:01.098 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)                     | 00:01.062 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.713 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)                     | 00:00.707 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.707 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)                               | 00:00.699 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.119 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)                     | 00:00.116 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.069 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.067 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)                               | 00:00.066 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)                               | 00:00.065 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)               | 00:00.031 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)               | 00:00.033 | 0.0 MB |
 +------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
index 186ed6ac36..e0b8aed8dc 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 27.32s!
+    yolov3-tiny inference graph built in 24.74s!
 
 
 
@@ -445,11 +445,6 @@ Download test image
 
 
 
-.. rst-class:: sphx-glr-timing
-
-   **Total running time of the script:** ( 1 minutes  0.311 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 0a8063ce3a..6a64022a41 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
 =================
-**01:00.311** total execution time for **topic_vta_tutorials_frontend** files:
+**00:57.066** total execution time for **topic_vta_tutorials_frontend** files:
 
 +--------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 01:00.311 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:57.066 | 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 7a7aaf2af0..3973aebf81 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
 =================
-**00:03.311** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.161** total execution time for **topic_vta_tutorials_optimize** files:
 
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.816 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)         | 00:02.681 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.495 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.481 | 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 d713bd2631..cc657ecd22 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
 =================
-**00:00.836** total execution time for **topic_vta_tutorials** files:
+**00:00.814** total execution time for **topic_vta_tutorials** files:
 
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.433 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.422 | 0.0 MB |
 +---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.403 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.392 | 0.0 MB |
 +---------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index a364cddece..58b3413e77 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: 93.449 ms
+    Execution time of this operator: 93.042 ms
 
 
 
@@ -434,7 +434,7 @@ operations.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  17.720 seconds)
+   **Total running time of the script:** ( 1 minutes  19.540 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 04de457bca..bd3e15e59b 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: 10.32/10.32     result: MeasureResult(costs=(0.0260187832,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7063686847686768, timestamp=1708338659.9917269)       [('tile_y', [-1, 32]), ('tile_x', [-1, 256])],None,85
-    No: 2   GFLOPS: 0.51/10.32      result: MeasureResult(costs=(0.5255900928,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.666619539260864, timestamp=1708338668.6665368)        [('tile_y', [-1, 256]), ('tile_x', [-1, 1])],None,8
-    No: 3   GFLOPS: 10.35/10.35     result: MeasureResult(costs=(0.025931175600000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6999287605285645, timestamp=1708338669.3384058)       [('tile_y', [-1, 8]), ('tile_x', [-1, 64])],None,63
-    No: 4   GFLOPS: 9.73/10.35      result: MeasureResult(costs=(0.027588438799999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7359044551849365, timestamp=1708338670.0366158)       [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
-    No: 5   GFLOPS: 3.61/10.35      result: MeasureResult(costs=(0.0743391898,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.452099323272705, timestamp=1708338671.6099627)        [('tile_y', [-1, 256]), ('tile_x', [-1, 8])],None,38
-    No: 6   GFLOPS: 2.02/10.35      result: MeasureResult(costs=(0.1330904792,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3837616443634033, timestamp=1708338673.9933755)       [('tile_y', [-1, 256]), ('tile_x', [-1, 4])],None,28
-    No: 7   GFLOPS: 1.98/10.35      result: MeasureResult(costs=(0.135604258,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.427419424057007, timestamp=1708338676.4230852) [('tile_y', [-1, 8]), ('tile_x', [-1, 1])],None,3
-    No: 8   GFLOPS: 13.98/13.98     result: MeasureResult(costs=(0.019206590000000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5729765892028809, timestamp=1708338676.9917262)       [('tile_y', [-1, 16]), ('tile_x', [-1, 32])],None,54
-    No: 9   GFLOPS: 12.10/13.98     result: MeasureResult(costs=(0.0221877238,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5923464298248291, timestamp=1708338677.6931167)       [('tile_y', [-1, 32]), ('tile_x', [-1, 128])],None,75
-    No: 10  GFLOPS: 4.48/13.98      result: MeasureResult(costs=(0.059951310599999995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.1851580142974854, timestamp=1708338678.9165745)       [('tile_y', [-1, 4]), ('tile_x', [-1, 2])],None,12
+    No: 1   GFLOPS: 13.52/13.52     result: MeasureResult(costs=(0.019855878200000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5977396965026855, timestamp=1708403749.1573048)       [('tile_y', [-1, 4]), ('tile_x', [-1, 256])],None,82
+    No: 2   GFLOPS: 12.43/13.52     result: MeasureResult(costs=(0.0215930482,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.644538402557373, timestamp=1708403749.7606938)        [('tile_y', [-1, 4]), ('tile_x', [-1, 128])],None,72
+    No: 3   GFLOPS: 13.40/13.52     result: MeasureResult(costs=(0.020025174200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6629865169525146, timestamp=1708403750.3400686)       [('tile_y', [-1, 256]), ('tile_x', [-1, 128])],None,78
+    No: 4   GFLOPS: 7.10/13.52      result: MeasureResult(costs=(0.0378319892,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8453638553619385, timestamp=1708403751.1921952)       [('tile_y', [-1, 2]), ('tile_x', [-1, 4])],None,21
+    No: 5   GFLOPS: 1.06/13.52      result: MeasureResult(costs=(0.2536294136,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.310134172439575, timestamp=1708403755.6260414)        [('tile_y', [-1, 256]), ('tile_x', [-1, 2])],None,18
+    No: 6   GFLOPS: 12.10/13.52     result: MeasureResult(costs=(0.0221792298,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6235024929046631, timestamp=1708403756.2389832)       [('tile_y', [-1, 64]), ('tile_x', [-1, 256])],None,86
+    No: 7   GFLOPS: 2.07/13.52      result: MeasureResult(costs=(0.1297528456,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3157236576080322, timestamp=1708403758.5657632)       [('tile_y', [-1, 8]), ('tile_x', [-1, 1])],None,3
+    No: 8   GFLOPS: 7.47/13.52      result: MeasureResult(costs=(0.0359419954,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8336803913116455, timestamp=1708403759.3992014)       [('tile_y', [-1, 2]), ('tile_x', [-1, 8])],None,31
+    No: 9   GFLOPS: 9.14/13.52      result: MeasureResult(costs=(0.0293813112,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6828923225402832, timestamp=1708403760.195342)        [('tile_y', [-1, 1]), ('tile_x', [-1, 32])],None,50
+    No: 10  GFLOPS: 8.41/13.52      result: MeasureResult(costs=(0.0319117384,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7190907001495361, timestamp=1708403760.954458)        [('tile_y', [-1, 1]), ('tile_x', [-1, 16])],None,40
 
 
 
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 31b9244d5f..fc1e00ce4d 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': 493.17011977997026, 'median': 493.14711975002865, 'std': 2.4254435877078127}
+    {'mean': 465.3329487299925, 'median': 465.1625409499957, 'std': 1.8629931775089623}
 
 
 
@@ -582,31 +582,29 @@ 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:   17.59/  20.14 GFLOPS | Progress: (4/20) | 9.29 s     [Task  1/25]  Current/Best:   19.37/  20.39 GFLOPS | Progress: (8/20) | 12.56 s     [Task  1/25]  Current/Best:   13.77/  21.43 GFLOPS | Progress: (12/20) | 14.99 s     [Task  1/25]  Current/Best:   14.32/  21.43 GFLOPS | Progress: (16/20) | 18.61 s     [Task  1/25]  Current/Best:   12.53/  21.43 GFLOPS | Progress: (20/20) | 21.68 s Done.
-     [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  2/25]  Current/Best:   12.78/  20.71 GFLOPS | Progress: (4/20) | 4.14 s     [Task  2/25]  Current/Best:    4.71/  20.71 GFLOPS | Progress: (8/20) | 5.77 s     [Task  2/25]  Current/Best:    9.26/  20.71 GFLOPS | Progress: (12/20) | 7.40 s     [Task  2/25]  Current/Best:    6.77/  20.71 GFLOPS | Progress: (16/20) | 9.05 s     [Task  2/25]  Current/Best:   14.08/  20.71 GFLOPS | Progress: (20/20) | 10.68 s Done.
-     [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  3/25]  Current/Best:   18.56/  19.63 GFLOPS | Progress: (4/20) | 4.55 s     [Task  3/25]  Current/Best:   13.80/  19.63 GFLOPS | Progress: (8/20) | 7.31 s     [Task  3/25]  Current/Best:   10.15/  19.81 GFLOPS | Progress: (12/20) | 10.80 s     [Task  3/25]  Current/Best:   15.67/  19.81 GFLOPS | Progress: (16/20) | 13.30 s     [Task  3/25]  Current/Best:    9.83/  23.70 GFLOPS | Progress: (20/20) | 16.18 s Done.
-     [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  4/25]  Current/Best:   15.08/  16.30 GFLOPS | Progress: (4/20) | 5.34 s     [Task  4/25]  Current/Best:   18.23/  18.23 GFLOPS | Progress: (8/20) | 9.75 s     [Task  4/25]  Current/Best:    7.90/  19.27 GFLOPS | Progress: (12/20) | 12.29 s     [Task  4/25]  Current/Best:   17.07/  21.60 GFLOPS | Progress: (16/20) | 14.05 s     [Task  4/25]  Current/Best:    6.16/  21.60 GFLOPS | Progress: (20/20) | 18.67 s Done.
-     [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  5/25]  Current/Best:    5.83/  17.07 GFLOPS | Progress: (4/20) | 5.07 s     [Task  5/25]  Current/Best:   20.25/  20.25 GFLOPS | Progress: (8/20) | 7.17 s     [Task  5/25]  Current/Best:   10.93/  20.25 GFLOPS | Progress: (12/20) | 9.61 s     [Task  5/25]  Current/Best:   11.24/  20.25 GFLOPS | Progress: (16/20) | 11.77 s     [Task  5/25]  Current/Best:   15.74/  20.25 GFLOPS | Progress: (20/20) | 13.87 s Done.
-     [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  6/25]  Current/Best:   15.96/  15.96 GFLOPS | Progress: (4/20) | 5.00 s     [Task  6/25]  Current/Best:   13.59/  15.96 GFLOPS | Progress: (8/20) | 8.12 s     [Task  6/25]  Current/Best:    3.44/  15.96 GFLOPS | Progress: (12/20) | 12.20 s     [Task  6/25]  Current/Best:   11.39/  15.96 GFLOPS | Progress: (16/20) | 14.66 s     [Task  6/25]  Current/Best:   20.40/  20.40 GFLOPS | Progress: (20/20) | 16.81 s Done.
-     [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  7/25]  Current/Best:    5.78/  17.67 GFLOPS | Progress: (4/20) | 5.43 s     [Task  7/25]  Current/Best:    9.54/  17.67 GFLOPS | Progress: (8/20) | 8.08 s     [Task  7/25]  Current/Best:    9.43/  17.67 GFLOPS | Progress: (12/20) | 10.65 s     [Task  7/25]  Current/Best:   22.65/  22.65 GFLOPS | Progress: (16/20) | 13.02 s     [Task  7/25]  Current/Best:   17.97/  22.65 GFLOPS | Progress: (20/20) | 15.09 s Done.
-     [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  8/25]  Current/Best:    6.62/  15.49 GFLOPS | Progress: (4/20) | 8.89 s     [Task  8/25]  Current/Best:   15.75/  15.75 GFLOPS | Progress: (8/20) | 11.29 s     [Task  8/25]  Current/Best:   11.57/  15.75 GFLOPS | Progress: (12/20) | 22.77 s     [Task  8/25]  Current/Best:    5.22/  15.75 GFLOPS | Progress: (16/20) | 28.82 s     [Task  8/25]  Current/Best:    4.00/  15.75 GFLOPS | Progress: (20/20) | 31.45 s     [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  9/25]  Current/Best:   10.65/  17.62 GFLOPS | Progress: (4/20) | 8.71 s     [Task  9/25]  Current/Best:   11.02/  17.81 GFLOPS | Progress: (8/20) | 13.17 s     [Task  9/25]  Current/Best:   15.42/  17.81 GFLOPS | Progress: (12/20) | 24.62 s     [Task  9/25]  Current/Best:   11.55/  17.81 GFLOPS | Progress: (16/20) | 27.65 s     [Task  9/25]  Current/Best:    3.41/  22.82 GFLOPS | Progress: (20/
 20) | 36.84 s Done.
-     [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 10/25]  Current/Best:   14.81/  14.81 GFLOPS | Progress: (4/20) | 5.35 s     [Task 10/25]  Current/Best:   13.13/  20.22 GFLOPS | Progress: (8/20) | 7.51 s     [Task 10/25]  Current/Best:    9.58/  20.22 GFLOPS | Progress: (12/20) | 9.54 s     [Task 10/25]  Current/Best:    5.06/  21.13 GFLOPS | Progress: (16/20) | 11.71 s     [Task 10/25]  Current/Best:   14.28/  21.13 GFLOPS | Progress: (20/20) | 13.68 s Done.
-     [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 11/25]  Current/Best:   11.16/  12.39 GFLOPS | Progress: (4/20) | 5.74 s     [Task 11/25]  Current/Best:   23.49/  23.49 GFLOPS | Progress: (8/20) | 7.58 s     [Task 11/25]  Current/Best:   11.67/  23.49 GFLOPS | Progress: (12/20) | 11.43 s     [Task 11/25]  Current/Best:   15.87/  23.49 GFLOPS | Progress: (16/20) | 15.22 s     [Task 11/25]  Current/Best:    3.10/  23.49 GFLOPS | Progress: (20/20) | 18.07 s Done.
-     [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 12/25]  Current/Best:    9.08/  15.88 GFLOPS | Progress: (4/20) | 5.26 s     [Task 12/25]  Current/Best:   17.75/  17.75 GFLOPS | Progress: (8/20) | 8.82 s     [Task 12/25]  Current/Best:   13.40/  17.75 GFLOPS | Progress: (12/20) | 12.40 s     [Task 12/25]  Current/Best:   13.44/  17.75 GFLOPS | Progress: (16/20) | 14.80 s     [Task 12/25]  Current/Best:   15.49/  17.75 GFLOPS | Progress: (20/20) | 17.25 s Done.
-     [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 13/25]  Current/Best:   21.00/  21.00 GFLOPS | Progress: (4/20) | 4.77 s     [Task 13/25]  Current/Best:    6.98/  21.00 GFLOPS | Progress: (8/20) | 7.87 s     [Task 13/25]  Current/Best:    3.10/  21.00 GFLOPS | Progress: (12/20) | 12.29 s     [Task 13/25]  Current/Best:   20.13/  21.00 GFLOPS | Progress: (16/20) | 14.27 s     [Task 13/25]  Current/Best:    5.51/  21.00 GFLOPS | Progress: (20/20) | 16.97 s Done.
-     [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 14/25]  Current/Best:    6.38/  13.78 GFLOPS | Progress: (4/20) | 14.45 s     [Task 14/25]  Current/Best:    5.59/  15.88 GFLOPS | Progress: (8/20) | 21.74 s     [Task 14/25]  Current/Best:   12.34/  15.88 GFLOPS | Progress: (12/20) | 25.82 s     [Task 14/25]  Current/Best:    4.72/  15.88 GFLOPS | Progress: (16/20) | 28.75 s     [Task 14/25]  Current/Best:   14.45/  15.88 GFLOPS | Progress: (20/20) | 31.28 s Done.
-     [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 15/25]  Current/Best:   18.59/  18.59 GFLOPS | Progress: (4/20) | 6.47 s     [Task 15/25]  Current/Best:   20.40/  21.16 GFLOPS | Progress: (8/20) | 13.28 s     [Task 15/25]  Current/Best:   13.37/  21.16 GFLOPS | Progress: (12/20) | 15.81 s     [Task 15/25]  Current/Best:   17.87/  21.16 GFLOPS | Progress: (16/20) | 26.89 s     [Task 15/25]  Current/Best:   10.24/  21.16 GFLOPS | Progress: (20/20) | 32.17 s     [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 16/25]  Current/Best:   16.41/  16.41 GFLOPS | Progress: (4/20) | 4.78 s     [Task 16/25]  Current/Best:    8.70/  16.41 GFLOPS | Progress: (8/20) | 7.69 s     [Task 16/25]  Current/Best:   14.56/  16.41 GFLOPS | Progress: (12/20) | 10.11 s     [Task 16/25]  Current/Best:   10.89/  20.41 GFLOPS | Progress: (16/20) | 13.58 s     [Task 16/25]  Current/Best:    7.38/  20.41 GFLOPS | Progress: (20/2
 0) | 15.62 s Done.
-     [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 17/25]  Current/Best:   12.84/  22.36 GFLOPS | Progress: (4/20) | 4.80 s     [Task 17/25]  Current/Best:    8.22/  22.36 GFLOPS | Progress: (8/20) | 7.72 s     [Task 17/25]  Current/Best:   12.19/  22.36 GFLOPS | Progress: (12/20) | 10.63 s Done.
+     [Task  1/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  1/25]  Current/Best:   13.07/  20.46 GFLOPS | Progress: (4/20) | 7.76 s     [Task  1/25]  Current/Best:    3.56/  23.29 GFLOPS | Progress: (8/20) | 11.02 s     [Task  1/25]  Current/Best:    5.75/  23.29 GFLOPS | Progress: (12/20) | 14.04 s     [Task  1/25]  Current/Best:   11.49/  23.29 GFLOPS | Progress: (16/20) | 16.55 s     [Task  1/25]  Current/Best:   16.23/  23.29 GFLOPS | Progress: (20/20) | 18.98 s Done.
+     [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  2/25]  Current/Best:    8.13/  14.83 GFLOPS | Progress: (4/20) | 4.25 s     [Task  2/25]  Current/Best:   14.42/  17.69 GFLOPS | Progress: (8/20) | 5.99 s     [Task  2/25]  Current/Best:   21.94/  21.94 GFLOPS | Progress: (12/20) | 7.23 s     [Task  2/25]  Current/Best:   16.55/  21.94 GFLOPS | Progress: (16/20) | 8.73 s     [Task  2/25]  Current/Best:    7.48/  22.21 GFLOPS | Progress: (20/20) | 9.97 s Done.
+     [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  3/25]  Current/Best:    3.28/  15.98 GFLOPS | Progress: (4/20) | 6.02 s     [Task  3/25]  Current/Best:   23.91/  23.91 GFLOPS | Progress: (8/20) | 8.44 s     [Task  3/25]  Current/Best:   20.44/  23.91 GFLOPS | Progress: (12/20) | 12.14 s     [Task  3/25]  Current/Best:   15.18/  23.91 GFLOPS | Progress: (16/20) | 14.26 s     [Task  3/25]  Current/Best:   12.34/  23.91 GFLOPS | Progress: (20/20) | 16.60 s Done.
+     [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  4/25]  Current/Best:   17.56/  17.56 GFLOPS | Progress: (4/20) | 4.48 s     [Task  4/25]  Current/Best:    6.34/  22.46 GFLOPS | Progress: (8/20) | 6.28 s     [Task  4/25]  Current/Best:   11.15/  22.46 GFLOPS | Progress: (12/20) | 9.44 s     [Task  4/25]  Current/Best:    5.33/  22.46 GFLOPS | Progress: (16/20) | 11.20 s     [Task  4/25]  Current/Best:   15.50/  22.46 GFLOPS | Progress: (20/20) | 14.10 s Done.
+     [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  5/25]  Current/Best:   12.05/  18.44 GFLOPS | Progress: (4/20) | 4.44 s     [Task  5/25]  Current/Best:   19.58/  23.15 GFLOPS | Progress: (8/20) | 6.19 s     [Task  5/25]  Current/Best:   18.73/  23.15 GFLOPS | Progress: (12/20) | 8.29 s     [Task  5/25]  Current/Best:   16.60/  23.15 GFLOPS | Progress: (16/20) | 10.00 s     [Task  5/25]  Current/Best:   15.56/  23.15 GFLOPS | Progress: (20/20) | 12.42 s Done.
+     [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  6/25]  Current/Best:   20.52/  20.52 GFLOPS | Progress: (4/20) | 6.48 s     [Task  6/25]  Current/Best:   12.04/  20.52 GFLOPS | Progress: (8/20) | 8.66 s     [Task  6/25]  Current/Best:   13.76/  20.52 GFLOPS | Progress: (12/20) | 12.36 s     [Task  6/25]  Current/Best:   16.60/  20.52 GFLOPS | Progress: (16/20) | 15.00 s     [Task  6/25]  Current/Best:   14.32/  20.52 GFLOPS | Progress: (20/20) | 19.65 s Done.
+     [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  7/25]  Current/Best:    6.48/  19.67 GFLOPS | Progress: (4/20) | 4.73 s     [Task  7/25]  Current/Best:   14.22/  19.67 GFLOPS | Progress: (8/20) | 7.80 s     [Task  7/25]  Current/Best:    6.47/  19.67 GFLOPS | Progress: (12/20) | 10.18 s     [Task  7/25]  Current/Best:   11.18/  21.97 GFLOPS | Progress: (16/20) | 12.32 s     [Task  7/25]  Current/Best:   18.90/  21.97 GFLOPS | Progress: (20/20) | 14.80 s Done.
+     [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  8/25]  Current/Best:   13.38/  17.30 GFLOPS | Progress: (4/20) | 5.11 s     [Task  8/25]  Current/Best:   11.30/  17.30 GFLOPS | Progress: (8/20) | 9.69 s     [Task  8/25]  Current/Best:   11.76/  17.30 GFLOPS | Progress: (12/20) | 12.07 s     [Task  8/25]  Current/Best:   12.98/  19.98 GFLOPS | Progress: (16/20) | 17.26 s     [Task  8/25]  Current/Best:   15.63/  19.98 GFLOPS | Progress: (20/20) | 28.62 s     [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task  9/25]  Current/Best:    8.93/  16.75 GFLOPS | Progress: (4/20) | 10.74 s     [Task  9/25]  Current/Best:   19.15/  19.78 GFLOPS | Progress: (8/20) | 13.48 s     [Task  9/25]  Current/Best:   11.05/  21.49 GFLOPS | Progress: (12/20) | 17.05 s     [Task  9/25]  Current/Best:    9.89/  21.49 GFLOPS | Progress: (16/20) | 22.11 s     [Task  9/25]  Current/Best:   13.20/  21.49 GFLOPS | Progress: (20/
 20) | 26.35 s Done.
+     [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 10/25]  Current/Best:   14.48/  18.02 GFLOPS | Progress: (4/20) | 5.43 s     [Task 10/25]  Current/Best:    6.22/  18.02 GFLOPS | Progress: (8/20) | 7.33 s     [Task 10/25]  Current/Best:   14.69/  18.02 GFLOPS | Progress: (12/20) | 9.35 s     [Task 10/25]  Current/Best:   16.65/  18.02 GFLOPS | Progress: (16/20) | 12.43 s     [Task 10/25]  Current/Best:   14.87/  18.86 GFLOPS | Progress: (20/20) | 14.31 s Done.
+     [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 11/25]  Current/Best:   15.06/  19.53 GFLOPS | Progress: (4/20) | 4.87 s     [Task 11/25]  Current/Best:   14.75/  21.10 GFLOPS | Progress: (8/20) | 8.58 s     [Task 11/25]  Current/Best:    9.88/  22.72 GFLOPS | Progress: (12/20) | 10.63 s     [Task 11/25]  Current/Best:    1.63/  22.72 GFLOPS | Progress: (16/20) | 15.06 s     [Task 11/25]  Current/Best:    7.89/  22.72 GFLOPS | Progress: (20/20) | 17.25 s Done.
+     [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 12/25]  Current/Best:    5.53/  14.93 GFLOPS | Progress: (4/20) | 9.81 s     [Task 12/25]  Current/Best:   12.90/  16.03 GFLOPS | Progress: (8/20) | 12.10 s     [Task 12/25]  Current/Best:    6.18/  17.06 GFLOPS | Progress: (12/20) | 15.00 s     [Task 12/25]  Current/Best:    5.30/  17.06 GFLOPS | Progress: (16/20) | 18.38 s     [Task 12/25]  Current/Best:    3.43/  17.06 GFLOPS | Progress: (20/20) | 22.29 s Done.
+     [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 13/25]  Current/Best:   12.58/  15.63 GFLOPS | Progress: (4/20) | 4.88 s     [Task 13/25]  Current/Best:   10.98/  20.34 GFLOPS | Progress: (8/20) | 8.54 s     [Task 13/25]  Current/Best:   17.06/  20.34 GFLOPS | Progress: (12/20) | 11.22 s     [Task 13/25]  Current/Best:   17.19/  20.34 GFLOPS | Progress: (16/20) | 13.63 s     [Task 13/25]  Current/Best:    8.80/  20.41 GFLOPS | Progress: (20/20) | 16.73 s Done.
+     [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 14/25]  Current/Best:   12.16/  12.16 GFLOPS | Progress: (4/20) | 8.91 s     [Task 14/25]  Current/Best:   22.00/  22.00 GFLOPS | Progress: (8/20) | 16.51 s     [Task 14/25]  Current/Best:   12.95/  22.00 GFLOPS | Progress: (12/20) | 22.79 s     [Task 14/25]  Current/Best:    3.73/  22.00 GFLOPS | Progress: (16/20) | 30.83 s     [Task 14/25]  Current/Best:   14.06/  22.00 GFLOPS | Progress: (20/20) | 35.45 s Done.
+     [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 15/25]  Current/Best:    9.25/  20.55 GFLOPS | Progress: (4/20) | 4.99 s     [Task 15/25]  Current/Best:   16.05/  20.55 GFLOPS | Progress: (8/20) | 12.45 s     [Task 15/25]  Current/Best:   13.85/  21.64 GFLOPS | Progress: (12/20) | 14.50 s     [Task 15/25]  Current/Best:   17.65/  21.64 GFLOPS | Progress: (16/20) | 19.06 s     [Task 15/25]  Current/Best:   13.92/  21.64 GFLOPS | Progress: (20/20) | 21.27 s Done.
+     [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 16/25]  Current/Best:   15.61/  19.39 GFLOPS | Progress: (4/20) | 5.51 s     [Task 16/25]  Current/Best:   11.59/  19.39 GFLOPS | Progress: (8/20) | 7.34 s     [Task 16/25]  Current/Best:   13.81/  19.44 GFLOPS | Progress: (12/20) | 9.38 s     [Task 16/25]  Current/Best:   10.25/  19.44 GFLOPS | Progress: (16/20) | 12.41 s     [Task 16/25]  Current/Best:   18.73/  19.44 GFLOPS | Progress: (20/20) | 14.23 s Done.
+     [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 17/25]  Current/Best:   24.07/  24.07 GFLOPS | Progress: (4/20) | 5.57 s     [Task 17/25]  Current/Best:   10.21/  24.07 GFLOPS | Progress: (8/20) | 8.89 s     [Task 17/25]  Current/Best:   21.40/  24.07 GFLOPS | Progress: (12/20) | 12.39 s     [Task 17/25]  Current/Best:   14.19/  24.07 GFLOPS | Progress: (16/20) | 15.26 s     [Task 17/25]  Current/Best:   22.78/  24.07 GFLOPS | Progress: (20/20) | 17.94 s Done.
+     [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 18/25]  Current/Best:   19.47/  23.23 GFLOPS | Progress: (4/20) | 4.61 s     [Task 18/25]  Current/Best:   17.31/  23.23 GFLOPS | Progress: (8/20) | 9.68 s     [Task 18/25]  Current/Best:    6.34/  23.23 GFLOPS | Progress: (12/20) | 13.71 s     [Task 18/25]  Current/Best:   13.06/  23.23 GFLOPS | Progress: (16/20) | 16.79 s     [Task 18/25]  Current/Best:    8.57/  23.23 GFLOPS | Progress: (20/20) | 19.19 s Done.
+     [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 19/25]  Current/Best:    9.87/  22.46 GFLOPS | Progress: (4/20) | 5.58 s     [Task 19/25]  Current/Best:    1.60/  22.46 GFLOPS | Progress: (8/20) | 9.53 s     [Task 19/25]  Current/Best:   12.54/  22.46 GFLOPS | Progress: (12/20) | 15.31 s     [Task 19/25]  Current/Best:   10.68/  22.46 GFLOPS | Progress: (16/20) | 18.61 s     [Task 19/25]  Current/Best:    5.53/  22.46 GFLOPS | Progress: (20/20) | 21.88 s Done.
+     [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 20/25]  Current/Best:   12.64/  19.32 GFLOPS | Progress: (4/20) | 4.57 s     [Task 20/25]  Current/Best:    5.34/  22.45 GFLOPS | Progress: (8/20) | 7.01 s     [Task 20/25]  Current/Best:   12.61/  22.45 GFLOPS | Progress: (12/20) | 18.85 s     [Task 20/25]  Current/Best:    9.68/  22.45 GFLOPS | Progress: (16/20) | 27.79 s     [Task 20/25]  Current/Best:    7.97/  22.45 GFLOPS | Progress: (20/20) | 36.18 s     [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 21/25]  Current/Best:   10.53/  17.00 GFLOPS | Progress: (4/20) | 6.91 s Done.
      Done.
-     [Task 17/25]  Current/Best:    9.49/  22.36 GFLOPS | Progress: (16/20) | 13.94 s     [Task 17/25]  Current/Best:   21.32/  22.36 GFLOPS | Progress: (20/20) | 17.51 s Done.
-     [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 18/25]  Current/Best:   18.26/  21.13 GFLOPS | Progress: (4/20) | 5.09 s     [Task 18/25]  Current/Best:   16.44/  21.13 GFLOPS | Progress: (8/20) | 8.79 s     [Task 18/25]  Current/Best:   19.59/  21.13 GFLOPS | Progress: (12/20) | 11.27 s     [Task 18/25]  Current/Best:   11.40/  21.80 GFLOPS | Progress: (16/20) | 16.12 s     [Task 18/25]  Current/Best:   13.90/  21.96 GFLOPS | Progress: (20/20) | 18.87 s Done.
-     [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 19/25]  Current/Best:    9.22/  21.90 GFLOPS | Progress: (4/20) | 6.46 s     [Task 19/25]  Current/Best:   12.15/  21.90 GFLOPS | Progress: (8/20) | 10.64 s     [Task 19/25]  Current/Best:   11.30/  21.90 GFLOPS | Progress: (12/20) | 15.36 s     [Task 19/25]  Current/Best:   19.04/  21.90 GFLOPS | Progress: (16/20) | 19.46 s     [Task 19/25]  Current/Best:   12.19/  21.98 GFLOPS | Progress: (20/20) | 23.25 s Done.
-     [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 20/25]  Current/Best:   17.53/  17.53 GFLOPS | Progress: (4/20) | 10.61 s     [Task 20/25]  Current/Best:   10.51/  18.25 GFLOPS | Progress: (8/20) | 19.76 s     [Task 20/25]  Current/Best:   12.15/  18.25 GFLOPS | Progress: (12/20) | 22.96 s     [Task 20/25]  Current/Best:   14.85/  18.25 GFLOPS | Progress: (16/20) | 30.22 s     [Task 20/25]  Current/Best:   12.00/  18.25 GFLOPS | Progress: (20/20) | 42.01 s     [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 21/25]  Current/Best:   13.05/  18.11 GFLOPS | Progress: (4/20) | 6.18 s     [Task 21/25]  Current/Best:    5.62/  18.95 GFLOPS | Progress: (8/20) | 13.64 s     [Task 21/25]  Current/Best:   17.34/  19.82 GFLOPS | Progress: (12/20) | 15.89 s     [Task 21/25]  Current/Best:   15.71/  19.82 GFLOPS | Progress: (16/20) | 17.77 s     [Task 21/25]  Current/Best:    6.54/  19.82 GFLOPS | Progress: (20
 /20) | 27.56 s Done.
-     [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 22/25]  Current/Best:   11.03/  19.48 GFLOPS | Progress: (4/20) | 5.16 s     [Task 22/25]  Current/Best:    5.10/  19.48 GFLOPS | Progress: (8/20) | 7.06 s     [Task 22/25]  Current/Best:    5.31/  19.48 GFLOPS | Progress: (12/20) | 9.10 s     [Task 22/25]  Current/Best:   12.81/  19.48 GFLOPS | Progress: (16/20) | 12.41 s     [Task 22/25]  Current/Best:    9.27/  19.48 GFLOPS | Progress: (20/20) | 15.12 s Done.
-     [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 23/25]  Current/Best:    5.33/  22.29 GFLOPS | Progress: (4/20) | 5.04 s     [Task 23/25]  Current/Best:    8.32/  22.29 GFLOPS | Progress: (8/20) | 9.11 s     [Task 23/25]  Current/Best:    9.60/  22.29 GFLOPS | Progress: (12/20) | 14.89 s     [Task 23/25]  Current/Best:   14.55/  22.37 GFLOPS | Progress: (16/20) | 18.50 s     [Task 23/25]  Current/Best:    6.11/  22.37 GFLOPS | Progress: (20/20) | 20.98 s Done.
-     [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 24/25]  Current/Best:    5.74/   5.74 GFLOPS | Progress: (4/20) | 13.65 s     [Task 24/25]  Current/Best:    5.20/   5.74 GFLOPS | Progress: (8/20) | 18.61 s     [Task 24/25]  Current/Best:    2.20/   5.74 GFLOPS | Progress: (12/20) | 29.65 s     [Task 24/25]  Current/Best:    7.97/   7.97 GFLOPS | Progress: (16/20) | 41.81 s     [Task 24/25]  Current/Best:    0.62/   9.37 GFLOPS | Progress: (20/20) | 46.67 s     [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 25/25]  Current/Best:    1.54/   5.74 GFLOPS | Progress: (4/20) | 5.90 s     [Task 25/25]  Current/Best:    5.92/   7.92 GFLOPS | Progress: (8/20) | 7.28 s Done.
-     Done.
-     [Task 25/25]  Current/Best:    1.55/   7.92 GFLOPS | Progress: (12/20) | 18.26 s     [Task 25/25]  Current/Best:    9.20/   9.26 GFLOPS | Progress: (16/20) | 20.71 s     [Task 25/25]  Current/Best:    1.55/   9.26 GFLOPS | Progress: (20/20) | 24.22 s
+     [Task 21/25]  Current/Best:   15.12/  19.49 GFLOPS | Progress: (8/20) | 18.03 s     [Task 21/25]  Current/Best:    2.82/  19.49 GFLOPS | Progress: (12/20) | 29.46 s     [Task 21/25]  Current/Best:   11.08/  19.49 GFLOPS | Progress: (16/20) | 32.55 s     [Task 21/25]  Current/Best:   18.43/  20.81 GFLOPS | Progress: (20/20) | 34.63 s     [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 22/25]  Current/Best:   11.27/  11.27 GFLOPS | Progress: (4/20) | 6.19 s     [Task 22/25]  Current/Best:   11.39/  22.90 GFLOPS | Progress: (8/20) | 7.94 s     [Task 22/25]  Current/Best:    6.35/  22.90 GFLOPS | Progress: (12/20) | 9.82 s     [Task 22/25]  Current/Best:   15.11/  22.90 GFLOPS | Progress: (16/20) | 12.14 s     [Task 22/25]  Current/Best:    6.65/  22.90 GFLOPS | Progress: (20/20) | 14.74 s Done.
+     [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 23/25]  Current/Best:   13.08/  20.07 GFLOPS | Progress: (4/20) | 5.96 s     [Task 23/25]  Current/Best:   10.19/  21.42 GFLOPS | Progress: (8/20) | 8.83 s     [Task 23/25]  Current/Best:   14.87/  21.42 GFLOPS | Progress: (12/20) | 11.56 s     [Task 23/25]  Current/Best:   20.64/  21.42 GFLOPS | Progress: (16/20) | 13.64 s     [Task 23/25]  Current/Best:    6.39/  21.42 GFLOPS | Progress: (20/20) | 18.70 s Done.
+     [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 24/25]  Current/Best:    7.12/   7.12 GFLOPS | Progress: (4/20) | 13.52 s     [Task 24/25]  Current/Best:    4.41/  10.60 GFLOPS | Progress: (8/20) | 24.48 s     [Task 24/25]  Current/Best:    4.54/  10.71 GFLOPS | Progress: (12/20) | 27.69 s     [Task 24/25]  Current/Best:    6.25/  10.71 GFLOPS | Progress: (16/20) | 34.57 s     [Task 24/25]  Current/Best:    5.23/  10.71 GFLOPS | Progress: (20/20) | 45.58 s     [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s     [Task 25/25]  Current/Best:    8.52/   9.12 GFLOPS | Progress: (4/20) | 5.91 s     [Task 25/25]  Current/Best:    8.60/   9.39 GFLOPS | Progress: (8/20) | 10.66 s     [Task 25/25]  Current/Best:    7.43/   9.39 GFLOPS | Progress: (12/20) | 14.67 s     [Task 25/25]  Current/Best:    8.41/   9.39 GFLOPS | Progress: (16/20) | 15.98 s     [Task 25/25]  Current/Best:    6.54/   9.39 GFLOPS | Progress: (20
 /20) | 26.92 s
 
 
 
@@ -675,6 +673,7 @@ model using optimized operators to speed up our computations.
  .. code-block:: none
 
      Done.
+     Done.
 
 
 
@@ -766,8 +765,8 @@ improvement in comparing the optimized model to the unoptimized model.
 
  .. code-block:: none
 
-    optimized: {'mean': 417.7346471299825, 'median': 417.1831609999572, 'std': 2.554834312181736}
-    unoptimized: {'mean': 493.17011977997026, 'median': 493.14711975002865, 'std': 2.4254435877078127}
+    optimized: {'mean': 378.17025628999545, 'median': 377.43049289997543, 'std': 2.9727689047893278}
+    unoptimized: {'mean': 465.3329487299925, 'median': 465.1625409499957, 'std': 1.8629931775089623}
 
 
 
@@ -790,7 +789,7 @@ profiling/benchmarking.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 13 minutes  36.375 seconds)
+   **Total running time of the script:** ( 12 minutes  53.637 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 873d85568b..d7c454668d 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
 
-    1.193e-07 secs/op
+    1.179e-07 secs/op
 
 
 
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index 8efb726d11..6cb4a5c38d 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, 0x10d6a5d0)), stage(b, placeholder(b, 0x76ebd20)), 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, 0x20716040)), stage(b, placeholder(b, 0x6a94060)), 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 002f761507..702f062df2 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,24 +5,24 @@
 
 Computation times
 =================
-**17:06.184** total execution time for **tutorial** files:
+**16:11.831** total execution time for **tutorial** files:
 
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 13:36.375 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)                 | 12:53.637 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:17.720 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:19.540 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 01:01.435 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)     | 00:58.069 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:42.828 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)                 | 00:40.390 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:25.773 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)               | 00:18.213 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.960 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)                               | 00:00.927 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:00.879 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)       | 00:00.858 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.213 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.197 | 0.0 MB |
 +------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_tutorial_uma.py` (``uma.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 c456ad5506..917ab6fb00 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: 0.000007
-    naive: 0.000009
+    Numpy running time: 0.000005
+    naive: 0.000006
 
 
 
@@ -389,7 +389,7 @@ compile and run this new schedule with the parallel operation applied:
 
  .. code-block:: none
 
-    parallel: 0.000009
+    parallel: 0.000006
 
 
 
@@ -444,7 +444,7 @@ factor to be the number of threads on your CPU.
 
  .. code-block:: none
 
-    vector: 0.000075
+    vector: 0.000038
     # 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    7.150609999371227e-06                    1.0
-                   naive              9.1824e-06      1.2841421921776512
-                parallel               9.496e-06      1.3279985904468306
-                  vector             7.54449e-05       10.55083412556888
+                   numpy    5.158529993423144e-06                    1.0
+                   naive              5.6415e-06      1.0936255109871644
+                parallel              5.8989e-06         1.1435234470907
+                  vector             3.78183e-05       7.331216460545223
 
 
 
@@ -922,7 +922,7 @@ matrix multiplication.
 
  .. code-block:: none
 
-    Numpy running time: 0.018709
+    Numpy running time: 0.013781
 
 
 
@@ -980,7 +980,7 @@ optimizations.
 
  .. code-block:: none
 
-    none: 3.458739
+    none: 3.353773
 
 
 
@@ -1080,7 +1080,7 @@ schedule.
 
  .. code-block:: none
 
-    blocking: 0.314947
+    blocking: 0.291754
 
 
 
@@ -1164,7 +1164,7 @@ already cache friendly from our previous optimizations.
 
  .. code-block:: none
 
-    vectorization: 0.304500
+    vectorization: 0.269348
     # 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: 0.119262
+    loop permutation: 0.108778
     # 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: 0.105823
+    array packing: 0.100840
     # 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: 0.111097
+    block caching: 0.093250
     # 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: 0.131945
+    parallelization: 0.110687
     # 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            3.4587386069                     1.0
-                blocking            0.3149468401     0.09105829491471192
-           vectorization            0.3044997029     0.08803778993085493
-        loop permutation     0.11926241010000001     0.03448147537431069
-           array packing     0.10582288200000001    0.030595802119561442
-           block caching             0.111097063      0.0321206878075051
-         parallelization     0.13194542530000003     0.03814842354284186
+                    none      3.3537726155999996                     1.0
+                blocking            0.2917537164     0.08699269444890628
+           vectorization             0.269347742     0.08031186752111187
+        loop permutation            0.1087780548     0.03243453485606665
+           array packing            0.1008404337    0.030067761073288908
+           block caching     0.09325043250000001    0.027804637698527226
+         parallelization     0.11068721919999999     0.03300379360399713
 
 
 
@@ -1594,11 +1594,6 @@ operations with tunable parameters that allows you to automatically optimize
 the computation for specific platforms.
 
 
-.. rst-class:: sphx-glr-timing
-
-   **Total running time of the script:** ( 1 minutes  1.435 seconds)
-
-
 .. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
 
 .. only:: html
diff --git a/docs/commit_hash b/docs/commit_hash
index 7839a91464..a136e59542 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-dd709412eb89b73e5bf41172b9d73360082816da
+40ec46970f7e1b94a0eec3b4da8868d1ec179d69
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index 737ea2e27e..2ebfb4f4f4 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  33.373 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  30.061 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 c09135cb49..1f8823b5dc 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -468,11 +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]
- 19%|#9        | 7.99M/41.5M [00:00&lt;00:00, 75.9MB/s]
- 39%|###8      | 16.0M/41.5M [00:00&lt;00:00, 47.8MB/s]
- 58%|#####7    | 24.0M/41.5M [00:00&lt;00:00, 53.0MB/s]
- 77%|#######7  | 32.0M/41.5M [00:00&lt;00:00, 58.5MB/s]
-100%|##########| 41.5M/41.5M [00:00&lt;00:00, 67.2MB/s]
+ 19%|#9        | 7.99M/41.5M [00:00&lt;00:00, 47.8MB/s]
+ 35%|###4      | 14.3M/41.5M [00:00&lt;00:00, 33.7MB/s]
+ 54%|#####3    | 22.3M/41.5M [00:00&lt;00:00, 44.2MB/s]
+ 65%|######5   | 27.0M/41.5M [00:00&lt;00:00, 44.9MB/s]
+ 77%|#######7  | 32.0M/41.5M [00:00&lt;00:00, 45.8MB/s]
+ 92%|#########2| 38.3M/41.5M [00:00&lt;00:00, 48.5MB/s]
+100%|##########| 41.5M/41.5M [00:00&lt;00:00, 45.0MB/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 f249d07208..12b26b40e5 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -503,7 +503,6 @@ To begin, we’ll install PaddlePaddle&gt;=2.1.3:</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>TVM prediction top-1 id: 282, class name:  282: &#39;tiger cat&#39;,
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  1.572 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 ae87b0d8c3..519cda72c1 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -451,11 +451,13 @@ be unstable.</p>
 Downloading: &quot;https://download.pytorch.org/models/resnet18-f37072fd.pth&quot; to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
 
   0%|          | 0.00/44.7M [00:00&lt;?, ?B/s]
- 18%|#7        | 7.99M/44.7M [00:00&lt;00:00, 59.1MB/s]
- 39%|###8      | 17.3M/44.7M [00:00&lt;00:00, 78.5MB/s]
- 56%|#####6    | 25.1M/44.7M [00:00&lt;00:00, 74.6MB/s]
- 82%|########1 | 36.4M/44.7M [00:00&lt;00:00, 90.3MB/s]
-100%|##########| 44.7M/44.7M [00:00&lt;00:00, 81.9MB/s]
+ 18%|#7        | 7.99M/44.7M [00:00&lt;00:00, 54.6MB/s]
+ 36%|###5      | 16.0M/44.7M [00:00&lt;00:00, 64.9MB/s]
+ 54%|#####3    | 24.0M/44.7M [00:00&lt;00:00, 61.8MB/s]
+ 68%|######7   | 30.3M/44.7M [00:00&lt;00:00, 57.2MB/s]
+ 80%|########  | 35.8M/44.7M [00:00&lt;00:00, 40.8MB/s]
+ 90%|########9 | 40.2M/44.7M [00:00&lt;00:00, 39.4MB/s]
+100%|##########| 44.7M/44.7M [00:00&lt;00:00, 50.6MB/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 92d34f62d2..a59aeb37fc 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)
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  30.855 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  26.508 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-tensorflow-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/7f1d3d1b878694c201c614c807cdebc8/from_tensorflow.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_tensorflow.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/sg_execution_times.html b/docs/how_to/compile_models/sg_execution_times.html
index f0cf83ba94..3302075ab8 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>06:35.654</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>06:19.158</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 81%" />
@@ -369,39 +369,39 @@
 </colgroup>
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="from_darknet.html#sphx-glr-how-to-compile-models-from-darknet-py"><span class="std std-ref">Compile YOLO-V2 and YOLO-V3 in DarkNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_darknet.py</span></code>)</p></td>
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+<td><p>00:59.315</p></td>
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 </tr>
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 <tr class="row-even"><td><p><a class="reference internal" href="from_tflite.html#sphx-glr-how-to-compile-models-from-tflite-py"><span class="std std-ref">Compile TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tflite.py</span></code>)</p></td>
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 <td><p>0.0 MB</p></td>
 </tr>
 <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>
-<td><p>00:02.887</p></td>
+<td><p>00:02.707</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 0733543790..a1656da809 100644
--- a/docs/how_to/deploy_models/deploy_model_on_adreno.html
+++ b/docs/how_to/deploy_models/deploy_model_on_adreno.html
@@ -850,10 +850,10 @@ Top5 predictions:
 Evaluate inference time cost...
 Execution time summary:
  mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)
- 4120.9131    4120.8228    4124.4875    4118.7590      1.7898
+ 3992.2676    3992.2148    4003.9555    3986.0833      4.8210
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  19.942 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  16.474 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-model-on-adreno-py">
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 <p><a class="reference download internal" download="" href="../../_downloads/2387d8448da213eb625e6b3d916327d4/deploy_model_on_adreno.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_model_on_adreno.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html b/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html
index b552381b59..2b04e5b282 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
@@ -458,21 +458,22 @@ 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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+ 60497920/102967424 [================&gt;.............] - ETA: 0s
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+ 99180544/102967424 [===========================&gt;..] - ETA: 0s
+102965248/102967424 [============================&gt;.] - ETA: 0s
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diff --git a/docs/how_to/deploy_models/deploy_model_on_android.html b/docs/how_to/deploy_models/deploy_model_on_android.html
index e9d26e2fa1..fe16467947 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...
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  mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)
-  15.5916      15.5247      16.1442      15.0202       0.2958
+  14.0519      13.7847      14.6994      13.7134       0.4063
 </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 4b79a5d74b..48e2b4ff9a 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -474,27 +474,31 @@ 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).
@@ -585,7 +589,7 @@ 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  37.507 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  19.059 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 24b32c372f..0025f4aacf 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -515,9 +515,9 @@ training. Other models require a full post training calibration.</p>
 Downloading: &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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@@ -608,7 +608,7 @@ output values are identical out of 1000 outputs from mobilenet v2.</p>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time summary:
  mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)
-  89.0116      88.9525      89.5557      88.6711       0.2051
+  85.9024      85.8525      94.0248      85.4598       0.8446
 </pre></div>
 </div>
 <div class="admonition note">
@@ -647,7 +647,7 @@ This includes support for the VNNI 8 bit dot product instruction (CascadeLake or
 <div class="section" id="deploy-a-quantized-tflite-model">
 <h2>Deploy a quantized TFLite Model<a class="headerlink" href="#deploy-a-quantized-tflite-model" title="Permalink to this headline">¶</a></h2>
 <p>TODO</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  28.912 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  23.893 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 411e98a75a..c28eb445d8 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -600,7 +600,7 @@ TFLite Top-5 labels: [387 102 386 341 349]
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time summary:
  mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)
-  110.0844     109.9932     117.5614     109.4831      0.7955
+  104.0844     103.7407     111.7406     102.8417      1.3186
 </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 2ef37b06b8..0f1fa25d25 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
+++ b/docs/how_to/deploy_models/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-deploy-models-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>09:55.389</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>09:17.971</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
 <table class="docutils align-default">
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@@ -369,39 +369,39 @@
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+<td><p>03:19.059</p></td>
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-<td><p>00:51.386</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_android.html#sphx-glr-how-to-deploy-models-deploy-model-on-android-py"><span class="std std-ref">Deploy the Pretrained Model on Android</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_android.py</span></code>)</p></td>
+<td><p>00:48.465</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_android.html#sphx-glr-how-to-deploy-models-deploy-model-on-android-py"><span class="std std-ref">Deploy the Pretrained Model on Android</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_android.py</span></code>)</p></td>
-<td><p>00:51.351</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="deploy_prequantized_tflite.html#sphx-glr-how-to-deploy-models-deploy-prequantized-tflite-py"><span class="std std-ref">Deploy a Framework-prequantized Model with TVM - Part 3 (TFLite)</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_prequantized_tflite.py</span></code>)</p></td>
+<td><p>00:48.277</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>00:46.699</p></td>
+<td><p>00:45.603</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>00:29.809</p></td>
+<td><p>00:28.112</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>00:29.772</p></td>
+<td><p>00:28.078</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>
-<td><p>00:00.010</p></td>
+<td><p>00:00.009</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/how_to/extend_tvm/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index 957b6182ca..28d58f6f93 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>00:04.129</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:04.029</strong> total execution time for <strong>how_to_extend_tvm</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="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>00:02.898</p></td>
+<td><p>00:02.840</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>00:01.223</p></td>
+<td><p>00:01.181</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>
-<td><p>00:00.008</p></td>
+<td><p>00:00.007</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 7adf050a47..c89d5150f1 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: 25251us [25251us] (48.11%; 48.11%)
-FoldScaleAxis: 27240us [8us] (51.89%; 51.89%)
-        FoldConstant: 27232us [1802us] (51.88%; 99.97%)
-                InferType: 25430us [25430us] (48.45%; 93.38%)
+InferType: 24147us [24147us] (48.13%; 48.13%)
+FoldScaleAxis: 26029us [8us] (51.87%; 51.87%)
+        FoldConstant: 26021us [1789us] (51.86%; 99.97%)
+                InferType: 24231us [24231us] (48.29%; 93.12%)
 </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: 25570us [25570us] (48.75%; 48.75%)
-FoldScaleAxis: 26881us [8us] (51.25%; 51.25%)
-        FoldConstant: 26873us [1923us] (51.23%; 99.97%)
-                InferType: 24950us [24950us] (47.57%; 92.84%)
+InferType: 24084us [24084us] (47.96%; 47.96%)
+FoldScaleAxis: 26134us [8us] (52.04%; 52.04%)
+        FoldConstant: 26126us [1835us] (52.02%; 99.97%)
+                InferType: 24290us [24290us] (48.37%; 92.98%)
 </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 22c739cfb6..8d82836501 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: 53.534080 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 53.516769 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 069ca8b2c9..15340e9e3f 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -877,7 +877,7 @@ be able to run on our build server</p>
     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;conv2d with tensor core: </span><span class="si">%f</span><span class="s2"> ms&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">* [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.273584 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.267178 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 abcdb6241b..1516491fe8 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: 0.018615
-Baseline: 3.445997
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.015412
+Baseline: 3.349918
 </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: 0.303034
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.280479
 </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: 0.274051
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.257398
 </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: 0.116609
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.110577
 </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: 0.107666
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.103413
 </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: 0.112580
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.094043
 </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: 0.135795
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.111092
 </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 46898bf616..d1c77557f7 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -360,7 +360,7 @@
             
   <div class="section" id="computation-times">
 <span id="sphx-glr-how-to-optimize-operators-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:34.281</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:31.515</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>00:31.199</p></td>
+<td><p>00:28.485</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>00:01.885</p></td>
+<td><p>00:01.837</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>00:01.196</p></td>
+<td><p>00:01.193</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 8df89fb9f5..00296d6d73 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>03:37.601</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>03:28.361</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>01:34.624</p></td>
+<td><p>01:31.417</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="tune_network_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-cuda-py"><span class="std std-ref">Auto-scheduling a Neural Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_cuda.py</span></code>)</p></td>
-<td><p>01:12.769</p></td>
+<td><p>01:09.919</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>00:17.598</p></td>
+<td><p>00:16.794</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="tune_conv2d_layer_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py"><span class="std std-ref">Auto-scheduling a Convolution Layer for GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_layer_cuda.py</span></code>)</p></td>
-<td><p>00:16.315</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
+<td><p>00:15.734</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
-<td><p>00:16.194</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_layer_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py"><span class="std std-ref">Auto-scheduling a Convolution Layer for GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_layer_cuda.py</span></code>)</p></td>
+<td><p>00:14.400</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
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--- a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
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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 97ea1aa8a2..e071640f8e 100644
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diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
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 ---------                                     ---                                           --------  -------  -----              ------  -------  ----------------
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+tvmgen_default_fused_layout_transform_1       tvmgen_default_fused_layout_transform_1       1.715     1.711    (1, 6, 10, 10)     1       1        [1.715]
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@@ -475,7 +475,7 @@ download a cat image and preprocess it to use as the model input.</p>
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 <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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+<tr class="row-even"><td><p><a class="reference internal" href="micro_autotune.html#sphx-glr-how-to-work-with-microtvm-micro-autotune-py"><span class="std std-ref">6. Model Tuning with microTVM</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_autotune.py</span></code>)</p></td>
+<td><p>01:26.204</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>01:25.345</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="micro_pytorch.html#sphx-glr-how-to-work-with-microtvm-micro-pytorch-py"><span class="std std-ref">4. microTVM PyTorch Tutorial</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_pytorch.py</span></code>)</p></td>
+<td><p>01:26.137</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>00:11.975</p></td>
+<td><p>00:11.407</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <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>
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 <td><p>0.0 MB</p></td>
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 <tr class="row-even"><td><p><a class="reference internal" href="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>
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+<td><p>00:07.702</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 a70750b39d..16d5ff9ba4 100644
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+++ b/docs/how_to/work_with_relay/sg_execution_times.html
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   <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>00:38.558</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:37.027</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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 <tr class="row-even"><td><p><a class="reference internal" href="using_external_lib.html#sphx-glr-how-to-work-with-relay-using-external-lib-py"><span class="std std-ref">Using External Libraries in Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_external_lib.py</span></code>)</p></td>
-<td><p>00:03.200</p></td>
+<td><p>00:03.089</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>00:01.843</p></td>
+<td><p>00:01.836</p></td>
 <td><p>0.0 MB</p></td>
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 <tr class="row-even"><td><p><a class="reference internal" href="using_relay_viz.html#sphx-glr-how-to-work-with-relay-using-relay-viz-py"><span class="std std-ref">Use Relay Visualizer to Visualize Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_relay_viz.py</span></code>)</p></td>
diff --git a/docs/how_to/work_with_schedules/intrin_math.html b/docs/how_to/work_with_schedules/intrin_math.html
index d657f0243b..3d6fde318e 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 0x7f3c49730940&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;function my_cuda_math_rule at 0x7ef7bf48cee0&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 5a95e75ae7..ab0d08eabe 100644
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+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
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 <span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:05.336</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:05.266</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
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 <tr class="row-even"><td><p><a class="reference internal" href="tensorize.html#sphx-glr-how-to-work-with-schedules-tensorize-py"><span class="std std-ref">Use Tensorize to Leverage Hardware Intrinsics</span></a> (<code class="docutils literal notranslate"><span class="pre">tensorize.py</span></code>)</p></td>
-<td><p>00:01.098</p></td>
+<td><p>00:01.062</p></td>
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 <tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
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+<td><p>00:00.707</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="scan.html#sphx-glr-how-to-work-with-schedules-scan-py"><span class="std std-ref">Scan and Recurrent Kernel</span></a> (<code class="docutils literal notranslate"><span class="pre">scan.py</span></code>)</p></td>
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+<td><p>00:00.699</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>00:00.119</p></td>
+<td><p>00:00.116</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="schedule_primitives.html#sphx-glr-how-to-work-with-schedules-schedule-primitives-py"><span class="std std-ref">Schedule Primitives in TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">schedule_primitives.py</span></code>)</p></td>
-<td><p>00:00.069</p></td>
+<td><p>00:00.067</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>00:00.066</p></td>
+<td><p>00:00.065</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="tuple_inputs.html#sphx-glr-how-to-work-with-schedules-tuple-inputs-py"><span class="std std-ref">Compute and Reduce with Tuple Inputs</span></a> (<code class="docutils literal notranslate"><span class="pre">tuple_inputs.py</span></code>)</p></td>
-<td><p>00:00.031</p></td>
+<td><p>00:00.033</p></td>
 <td><p>0.0 MB</p></td>
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diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index 223b71b762..a98fd5d0d7 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">
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+<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
 <dd><p>The search policy that searches in a hierarchical search space defined by sketches.
 The policy randomly samples programs from the space defined by sketches and use evolutionary
 search to fine-tune them.</p>
@@ -1921,7 +1921,7 @@ Candidates:
 
 <dl class="py function">
 <dt class="sig sig-object py" id="tvm.auto_scheduler.auto_schedule">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
 <dd><p>THIS API IS DEPRECATED.</p>
 <p>Run auto scheduling search for a task.</p>
 <dl class="field-list simple">
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index 1f306def50..23d03dbdee 100644
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index abb73a89e3..088aad118f 100644
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+<li><span class="target">ArtifactCache</span></li></ul></section>
+<section class="tsd-panel">
+<h4>Implements</h4>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html" class="tsd-signature-type tsd-kind-interface">ArtifactCacheTemplate</a></li></ul></section><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L991">runtime.ts:991</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L992">runtime.ts:992</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L996">runtime.ts:996</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="deleteInCache" class="tsd-anchor"></a>
+<h3 class="tsd-anchor-link"><span>delete<wbr/>In<wbr/>Cache</span><a href="#deleteInCache" 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">
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+<p>Implementation of <a href="../interfaces/_internal_.ArtifactCacheTemplate.html">ArtifactCacheTemplate</a>.<a href="../interfaces/_internal_.ArtifactCacheTemplate.html#deleteInCache">deleteInCache</a></p>
+<ul>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1026">runtime.ts:1026</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="fetchWithCache" class="tsd-anchor"></a>
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+<div class="tsd-comment tsd-typography"><p>fetch key url from cache</p>
+</div>
 <div class="tsd-parameters">
 <h4 class="tsd-parameters-title">Parameters</h4>
 <ul class="tsd-parameter-list">
 <li>
 <h5><span class="tsd-kind-parameter">url</span>: <span class="tsd-signature-type">string</span></h5></li></ul></div>
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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>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L999">runtime.ts:999</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1000">runtime.ts:1000</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 class="tsd-signatures">
 <li class="tsd-signature tsd-anchor-link" id="hasAllKeys.hasAllKeys-1"><span class="tsd-kind-call-signature">has<wbr/>All<wbr/>Keys</span><span class="tsd-signature-symbol">(</span><span class="tsd-kind-parameter">keys</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">boolean</span><span class="tsd-signature-symbol">&gt; [...]
 <li class="tsd-description">
+<div class="tsd-comment tsd-typography"><p>check if cache has all keys in Cache</p>
+</div>
 <div class="tsd-parameters">
 <h4 class="tsd-parameters-title">Parameters</h4>
 <ul class="tsd-parameter-list">
 <li>
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+<p>Implementation of <a href="../interfaces/_internal_.ArtifactCacheTemplate.html">ArtifactCacheTemplate</a>.<a href="../interfaces/_internal_.ArtifactCacheTemplate.html#hasAllKeys">hasAllKeys</a></p>
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1015">runtime.ts:1015</a></li></ul></aside></li></ul></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1016">runtime.ts:1016</a></li></ul></aside></li></ul></section></section></div>
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+<li><a href="#deleteInCache" class=""><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-2048-path"></use><use href="#icon-2048-text"></use></svg><span>delete<wbr/>In<wbr/>Cache</span></a></li>
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 <li><a href="_internal_.RuntimeContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>Runtime<wbr/>Context</span></a></li>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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index dd6a4ffce8..fef56cd6f9 100644
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L401">runtime.ts:401</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L402">runtime.ts:402</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L410">runtime.ts:410</a></li></ul></aside></li></ul></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/dd709412e/web/src/runtime.ts#L405">runtime.ts:405</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L406">runtime.ts:406</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L403">runtime.ts:403</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L404">runtime.ts:404</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L407">runtime.ts:407</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L408">runtime.ts:408</a></li></ul></aside></section></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L424">runtime.ts:424</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L425">runtime.ts:425</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="toString" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L416">runtime.ts:416</a></li></ul></aside></li></ul></section></section></div>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L342">runtime.ts:342</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L350">runtime.ts:350</a></li></ul></aside></li></ul></section></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L346">runtime.ts:346</a></li></ul></aside></section>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L343">runtime.ts:343</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L344">runtime.ts:344</a></li></ul></aside></section></section>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L368">runtime.ts:368</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L369">runtime.ts:369</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>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L376">runtime.ts:376</a></li></ul></aside></li></ul></section></section></div>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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index 71a98753d8..191ba6bfc8 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/dd709412e/web/src/runtime.ts#L1043">runtime.ts:1043</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1052">runtime.ts:1052</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
 <section class="tsd-panel tsd-index-panel">
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 <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/dd709412e/web/src/runtime.ts#L1072">runtime.ts:1072</a></li></ul></aside></li></ul></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1081">runtime.ts:1081</a></li></ul></aside></li></ul></section></section>
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 <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/dd709412e/web/src/runtime.ts#L1046">runtime.ts:1046</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1055">runtime.ts:1055</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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1045">runtime.ts:1045</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1054">runtime.ts:1054</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/dd709412e/web/src/runtime.ts#L1044">runtime.ts:1044</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1053">runtime.ts:1053</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>
@@ -193,7 +193,7 @@ 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/dd709412e/web/src/runtime.ts#L1772">runtime.ts:1772</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1784">runtime.ts:1784</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>
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@@ -218,7 +218,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">any</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1771">runtime.ts:1771</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">
@@ -239,7 +239,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">any</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1801">runtime.ts:1801</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">
@@ -256,7 +256,7 @@ 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/dd709412e/web/src/runtime.ts#L1947">runtime.ts:1947</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1959">runtime.ts:1959</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="attachToCurrentScope" class="tsd-anchor"></a>
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@@ -283,7 +283,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1204">runtime.ts:1204</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="beginScope" class="tsd-anchor"></a>
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@@ -293,7 +293,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1163">runtime.ts:1163</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="benchmark" class="tsd-anchor"></a>
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@@ -328,7 +328,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1122">runtime.ts:1122</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="bindCanvas" class="tsd-anchor"></a>
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@@ -345,7 +345,7 @@ token_freqs[i] is the frequency of token_ids[i], for all i. And all token_freqs
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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/dd709412e/web/src/runtime.ts#L1797">runtime.ts:1797</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1809">runtime.ts:1809</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">
@@ -355,7 +355,7 @@ 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/dd709412e/web/src/runtime.ts#L1828">runtime.ts:1828</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1840">runtime.ts:1840</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">
@@ -372,7 +372,7 @@ 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/dd709412e/web/src/runtime.ts#L1657">runtime.ts:1657</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1669">runtime.ts:1669</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">
@@ -390,7 +390,7 @@ 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/dd709412e/web/src/runtime.ts#L1373">runtime.ts:1373</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1382">runtime.ts:1382</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">
@@ -416,7 +416,7 @@ 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/dd709412e/web/src/runtime.ts#L1222">runtime.ts:1222</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1231">runtime.ts:1231</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">
@@ -438,7 +438,7 @@ 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/dd709412e/web/src/runtime.ts#L1649">runtime.ts:1649</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1661">runtime.ts:1661</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">
@@ -451,7 +451,7 @@ 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/dd709412e/web/src/runtime.ts#L1134">runtime.ts:1134</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1143">runtime.ts:1143</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">
@@ -477,7 +477,7 @@ 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/dd709412e/web/src/runtime.ts#L1677">runtime.ts:1677</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1689">runtime.ts:1689</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">
@@ -490,13 +490,13 @@ 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/dd709412e/web/src/runtime.ts#L1165">runtime.ts:1165</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1174">runtime.ts:1174</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">
 <li class="tsd-signature tsd-anchor-link" id="fetchNDArrayCache.fetchNDArrayCache-1"><span class="tsd-kind-call-signature">fetchNDArray<wbr/>Cache</span><span class="tsd-signature-symbol">(</span><span class="tsd-kind-parameter">ndarrayCacheUrl</span>, <span class="tsd-kind-parameter">device</span>, <span class="tsd-kind-parameter">cacheScope</span><span class="tsd-signature-symbol">?</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class [...]
 <li class="tsd-description">
-<div class="tsd-comment tsd-typography"><p>Fetch NDArray cache from url.</p>
+<div class="tsd-comment tsd-typography"><p>Given cacheUrl, search up items to fetch based on cacheUrl/ndarray-cache.json</p>
 </div>
 <div class="tsd-parameters">
 <h4 class="tsd-parameters-title">Parameters</h4>
@@ -516,7 +516,7 @@ 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/dd709412e/web/src/runtime.ts#L1464">runtime.ts:1464</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1473">runtime.ts:1473</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">
@@ -534,7 +534,7 @@ 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/dd709412e/web/src/runtime.ts#L1310">runtime.ts:1310</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1319">runtime.ts:1319</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">
@@ -555,7 +555,7 @@ a value to parent scope.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <a href="TVMObject.html" class="tsd-signature-type tsd-kind-class">TVMObject</a></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1401">runtime.ts:1401</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1410">runtime.ts:1410</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">
@@ -573,7 +573,7 @@ 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/dd709412e/web/src/runtime.ts#L1412">runtime.ts:1412</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1421">runtime.ts:1421</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">
@@ -590,7 +590,7 @@ 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/dd709412e/web/src/runtime.ts#L2012">runtime.ts:2012</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L2024">runtime.ts:2024</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">
@@ -608,7 +608,7 @@ 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/dd709412e/web/src/runtime.ts#L1345">runtime.ts:1345</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1354">runtime.ts:1354</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">
@@ -619,7 +619,7 @@ 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/dd709412e/web/src/runtime.ts#L1238">runtime.ts:1238</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1247">runtime.ts:1247</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">
@@ -637,7 +637,7 @@ 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/dd709412e/web/src/runtime.ts#L1862">runtime.ts:1862</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1874">runtime.ts:1874</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">
@@ -655,7 +655,7 @@ 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/dd709412e/web/src/runtime.ts#L1853">runtime.ts:1853</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1865">runtime.ts:1865</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">
@@ -675,7 +675,7 @@ and needs to b explicitly disposed.</p>
 <h4 class="tsd-returns-title">Returns <a href="TVMArray.html" class="tsd-signature-type tsd-kind-class">TVMArray</a></h4><p>The result array.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1841">runtime.ts:1841</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1853">runtime.ts:1853</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">
@@ -700,7 +700,7 @@ alive when exit the current scope.</p>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type tsd-kind-type-parameter">T</span></h4><p>The input obj.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1208">runtime.ts:1208</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1217">runtime.ts:1217</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">
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1461">runtime.ts:1461</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>
 <ul class="tsd-signatures">
@@ -728,7 +728,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1425">runtime.ts:1425</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1434">runtime.ts:1434</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">
@@ -746,7 +746,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1434">runtime.ts:1434</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1443">runtime.ts:1443</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>
 <ul class="tsd-signatures">
@@ -769,7 +769,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1443">runtime.ts:1443</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1452">runtime.ts:1452</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>
 <ul class="tsd-signatures">
@@ -796,7 +796,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1920">runtime.ts:1920</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1932">runtime.ts:1932</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="registerFunc" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>register<wbr/>Func</span><a href="#registerFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -819,7 +819,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1277">runtime.ts:1277</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1286">runtime.ts:1286</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>
 <ul class="tsd-signatures">
@@ -836,7 +836,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1390">runtime.ts:1390</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1399">runtime.ts:1399</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>
 <ul class="tsd-signatures">
@@ -861,7 +861,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1899">runtime.ts:1899</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1911">runtime.ts:1911</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>
 <ul class="tsd-signatures">
@@ -871,7 +871,7 @@ alive when exit the current scope.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1143">runtime.ts:1143</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1152">runtime.ts:1152</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="sampleTopPFromLogits" class="tsd-anchor"></a>
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 <ul class="tsd-signatures">
@@ -897,7 +897,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1749">runtime.ts:1749</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1761">runtime.ts:1761</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>
 <ul class="tsd-signatures">
@@ -919,7 +919,7 @@ alive when exit the current scope.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1639">runtime.ts:1639</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1651">runtime.ts:1651</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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@@ -949,7 +949,7 @@ 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/dd709412e/web/src/runtime.ts#L2145">runtime.ts:2145</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L2157">runtime.ts:2157</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">
@@ -966,7 +966,7 @@ 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/dd709412e/web/src/runtime.ts#L1806">runtime.ts:1806</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1818">runtime.ts:1818</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>
 <ul class="tsd-signatures">
@@ -978,7 +978,7 @@ System lib is a global module that contains self register functions in startup.<
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1231">runtime.ts:1231</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1240">runtime.ts:1240</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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@@ -996,7 +996,7 @@ System lib is a global module that contains self register functions in startup.<
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1593">runtime.ts:1593</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1605">runtime.ts:1605</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="toPackedFunc" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>to<wbr/>Packed<wbr/>Func</span><a href="#toPackedFunc" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -1014,7 +1014,7 @@ System lib is a global module that contains self register functions in startup.<
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1356">runtime.ts:1356</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1365">runtime.ts:1365</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="typeKey2Index" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>type<wbr/>Key2<wbr/>Index</span><a href="#typeKey2Index" 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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@@ -1032,7 +1032,7 @@ 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/dd709412e/web/src/runtime.ts#L1871">runtime.ts:1871</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1883">runtime.ts:1883</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="uniform" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>uniform</span><a href="#uniform" 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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@@ -1062,7 +1062,7 @@ System lib is a global module that contains self register functions in startup.<
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L1723">runtime.ts:1723</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L1735">runtime.ts:1735</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="webgpu" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>webgpu</span><a href="#webgpu" aria-label="Permalink" class="tsd-anchor-icon"><svg 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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@@ -1079,7 +1079,7 @@ 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/40ec46970/web/src/runtime.ts#L1677">runtime.ts:1677</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="withNewScope" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>with<wbr/>New<wbr/>Scope</span><a href="#withNewScope" aria-label="Permalink" class="tsd-anchor-icon"><svg 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">
@@ -1112,7 +1112,7 @@ 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/40ec46970/web/src/runtime.ts#L1188">runtime.ts:1188</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
 <div class="page-menu">
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+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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index fe9484c6db..ff28452bb0 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L695">runtime.ts:695</a></li></ul></aside></li></ul></section></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L704">runtime.ts:704</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L705">runtime.ts:705</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L733">runtime.ts:733</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L720">runtime.ts:720</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L767">runtime.ts:767</a></li></ul></aside></li></ul></section></section></div>
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@@ -134,7 +134,7 @@ The number of elements must match.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L552">runtime.ts:552</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L553">runtime.ts:553</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="copyFromRawBytes" class="tsd-anchor"></a>
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@@ -152,7 +152,7 @@ The number of elements must match.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L596">runtime.ts:596</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L597">runtime.ts:597</a></li></ul></aside></li></ul></section>
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@@ -165,7 +165,7 @@ only the first call will take effect.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L537">runtime.ts:537</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L538">runtime.ts:538</a></li></ul></aside></li></ul></section>
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 <h3 class="tsd-anchor-link"><span>get<wbr/>Data<wbr/>Ptr</span><a href="#getDataPtr" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -176,7 +176,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L530">runtime.ts:530</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L531">runtime.ts:531</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="getHandle" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -194,7 +194,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L518">runtime.ts:518</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L519">runtime.ts:519</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="toArray" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>to<wbr/>Array</span><a href="#toArray" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -206,7 +206,7 @@ the dtype of the NDArray.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L662">runtime.ts:662</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L663">runtime.ts:663</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="toRawBytes" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>to<wbr/>Raw<wbr/>Bytes</span><a href="#toRawBytes" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -217,7 +217,7 @@ the dtype of the NDArray.</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L631">runtime.ts:631</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L632">runtime.ts:632</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="view" class="tsd-anchor"></a>
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@@ -235,7 +235,7 @@ the dtype of the NDArray.</p>
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 <aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L508">runtime.ts:508</a></li></ul></aside></li></ul></section></section></div>
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@@ -284,7 +284,8 @@ the dtype of the NDArray.</p>
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diff --git a/docs/reference/api/typedoc/classes/RPCServer.html b/docs/reference/api/typedoc/classes/RPCServer.html
index 7b8276c32f..0266550e27 100644
--- a/docs/reference/api/typedoc/classes/RPCServer.html
+++ b/docs/reference/api/typedoc/classes/RPCServer.html
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L77">rpc_server.ts:77</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/rpc_server.ts#L100">rpc_server.ts:100</a></li></ul></aside></li></ul></section></section>
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 <section class="tsd-panel tsd-member"><a id="getImports" class="tsd-anchor"></a>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L83">rpc_server.ts:83</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L79">rpc_server.ts:79</a></li></ul></aside></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L82">rpc_server.ts:82</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="socket" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L80">rpc_server.ts:80</a></li></ul></aside></section>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/rpc_server.ts#L81">rpc_server.ts:81</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="url" class="tsd-anchor"></a>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/rpc_server.ts#L78">rpc_server.ts:78</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L282">runtime.ts:282</a></li></ul></aside></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L795">runtime.ts:795</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L818">runtime.ts:818</a></li></ul></aside></li></ul></section>
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@@ -178,6 +179,7 @@ only the first call will take effect.</p>
 <li><a href="../types/PackedFunc.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-4194304-path"></use><use href="#icon-4194304-text"></use></svg><span>Packed<wbr/>Func</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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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 e1596da594..0652b8f8ab 100644
--- a/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
+++ b/docs/reference/api/typedoc/classes/_internal_.CachedCallStack.html
@@ -36,7 +36,7 @@ can still call into storeXX</li>
 <ul class="tsd-hierarchy">
 <li><a href="../interfaces/Disposable.html" class="tsd-signature-type tsd-kind-interface">Disposable</a></li></ul></section><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/memory.ts#L206">memory.ts:206</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
 <section class="tsd-panel tsd-index-panel">
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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/dd709412e/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/40ec46970/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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 <section class="tsd-panel tsd-member"><a id="tempArgs" class="tsd-anchor"></a>
@@ -95,7 +95,7 @@ can still call into storeXX</li>
 <div class="tsd-comment tsd-typography"><p>List of temporay arguments that can be disposed during reset.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">number</span></h4><p>The allocated pointer array.</p>
 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
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@@ -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/dd709412e/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/40ec46970/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/dd709412e/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/40ec46970/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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 <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/dd709412e/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/40ec46970/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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 <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/dd709412e/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/40ec46970/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>
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@@ -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/dd709412e/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/40ec46970/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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/dd709412e/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/40ec46970/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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
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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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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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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 <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/dd709412e/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/40ec46970/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>
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@@ -330,7 +330,7 @@ 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/dd709412e/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/40ec46970/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>
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@@ -345,7 +345,7 @@ 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">
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/memory.ts#L334">memory.ts:334</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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index a1cde0a688..074f15398c 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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L168">webgpu.ts:168</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L168">webgpu.ts:168</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
 <section class="tsd-panel tsd-index-panel">
 <details class="tsd-index-content tsd-index-accordion" open><summary class="tsd-accordion-summary tsd-index-summary">
@@ -61,7 +61,7 @@ which needs to be explicitly disposed.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L177">webgpu.ts:177</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="clear" class="tsd-anchor"></a>
@@ -71,7 +71,7 @@ which needs to be explicitly disposed.</p>
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 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
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@@ -84,7 +84,7 @@ only the first call will take effect.</p>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L277">webgpu.ts:277</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
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@@ -140,7 +140,8 @@ only the first call will take effect.</p>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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@@ -168,6 +169,7 @@ only the first call will take effect.</p>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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index 592d7d48f9..3350f8bcbc 100644
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/environment.ts#L68">environment.ts:68</a></li></ul></aside>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/environment.ts#L88">environment.ts:88</a></li></ul></aside></li></ul></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/40ec46970/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/environment.ts#L69">environment.ts:69</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/environment.ts#L78">environment.ts:78</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/environment.ts#L84">environment.ts:84</a></li></ul></aside></section></section>
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@@ -139,7 +139,7 @@ of functions that do not maps to the address space.</p>
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/environment.ts#L105">environment.ts:105</a></li></ul></aside></li></ul></section></section></div>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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@@ -208,6 +209,7 @@ of functions that do not maps to the address space.</p>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 <li><a href="../functions/instantiate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>instantiate</span></a></li>
diff --git a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
index fe2411b617..94ed9bf7a7 100644
--- a/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
+++ b/docs/reference/api/typedoc/classes/_internal_.FFILibrary.html
@@ -28,7 +28,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L43">runtime.ts:43</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L44">runtime.ts:44</a></li></ul></aside>
 <section class="tsd-panel-group tsd-index-group">
 <section class="tsd-panel tsd-index-panel">
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 <h4 class="tsd-returns-title">Returns <a href="_internal_.FFILibrary.html" class="tsd-signature-type tsd-kind-class">FFILibrary</a></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L52">runtime.ts:52</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/dd709412e/web/src/runtime.ts#L46">runtime.ts:46</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L47">runtime.ts:47</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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L45">runtime.ts:45</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L46">runtime.ts:46</a></li></ul></aside></section>
 <section class="tsd-panel tsd-member"><a id="wasm32" class="tsd-anchor"></a>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L44">runtime.ts:44</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L45">runtime.ts:45</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/dd709412e/web/src/runtime.ts#L47">runtime.ts:47</a></li></ul></aside></section></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L48">runtime.ts:48</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="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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L77">runtime.ts:77</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L78">runtime.ts:78</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
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@@ -119,7 +119,7 @@ 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/dd709412e/web/src/runtime.ts#L66">runtime.ts:66</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L67">runtime.ts:67</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="getOrAllocCallStack" class="tsd-anchor"></a>
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@@ -127,7 +127,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/runtime.ts#L87">runtime.ts:87</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="recycleCallStack" class="tsd-anchor"></a>
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@@ -140,7 +140,7 @@ only the first call will take effect.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L97">runtime.ts:97</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L98">runtime.ts:98</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="sizeofPtr" class="tsd-anchor"></a>
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@@ -148,7 +148,7 @@ only the first call will take effect.</p>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L74">runtime.ts:74</a></li></ul></aside></li></ul></section></section></div>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/memory.ts#L31">memory.ts:31</a></li></ul></aside>
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@@ -70,19 +70,19 @@
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 <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/dd709412e/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/40ec46970/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>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/memory.ts#L32">memory.ts:32</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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/dd709412e/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/40ec46970/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 @@
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">string</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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/dd709412e/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/40ec46970/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>
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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/dd709412e/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/40ec46970/web/src/memory.ts#L97">memory.ts:97</a></li></ul></aside></li></ul></section>
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@@ -140,7 +140,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L74">memory.ts:74</a></li></ul></aside></li></ul></section>
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@@ -153,7 +153,7 @@
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
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@@ -166,7 +166,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L104">memory.ts:104</a></li></ul></aside></li></ul></section>
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@@ -187,7 +187,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L132">memory.ts:132</a></li></ul></aside></li></ul></section>
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@@ -204,7 +204,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L145">memory.ts:145</a></li></ul></aside></li></ul></section>
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@@ -217,7 +217,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L60">memory.ts:60</a></li></ul></aside></li></ul></section>
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@@ -230,7 +230,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/web/src/memory.ts#L67">memory.ts:67</a></li></ul></aside></li></ul></section>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/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/40ec46970/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>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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/40ec46970/web/src/runtime.ts#L212">runtime.ts:212</a></li></ul></aside></li></ul></section>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L247">runtime.ts:247</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L891">runtime.ts:891</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>
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 <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/dd709412e/web/src/runtime.ts#L794">runtime.ts:794</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L795">runtime.ts:795</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member tsd-is-inherited"><a id="getHandle" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>get<wbr/>Handle</span><a href="#getHandle" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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 <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/dd709412e/web/src/runtime.ts#L809">runtime.ts:809</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L810">runtime.ts:810</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>
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@@ -107,7 +107,7 @@ only the first call will take effect.</p>
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L901">runtime.ts:901</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L902">runtime.ts:902</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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 <ul class="tsd-signatures tsd-is-inherited">
@@ -118,7 +118,7 @@ only the first call will take effect.</p>
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 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L817">runtime.ts:817</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L818">runtime.ts:818</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>
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 <p>Inherited from <a href="TVMObject.html">TVMObject</a>.<a href="TVMObject.html#typeKey">typeKey</a></p>
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L838">runtime.ts:838</a></li></ul></aside></li></ul></section></section></div>
 <div class="col-sidebar">
 <div class="page-menu">
 <div class="tsd-navigation settings">
@@ -170,7 +170,8 @@ only the first call will take effect.</p>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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diff --git a/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html b/docs/reference/api/typedoc/classes/_internal_.WebGPUContext.html
index 271dd8c129..b2b897257f 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/dd709412e/web/src/webgpu.ts#L345">webgpu.ts:345</a></li></ul></aside>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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">
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 <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/dd709412e/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/40ec46970/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/dd709412e/web/src/webgpu.ts#L346">webgpu.ts:346</a></li></ul></aside></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
 <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/dd709412e/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/40ec46970/web/src/webgpu.ts#L347">webgpu.ts:347</a></li></ul></aside></section></section>
 <section class="tsd-panel-group tsd-member-group">
 <h2>Methods</h2>
 <section class="tsd-panel tsd-member"><a id="bindCanvas" class="tsd-anchor"></a>
@@ -100,7 +100,7 @@ Manages all the webgpu resources here.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L454">webgpu.ts:454</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L454">webgpu.ts:454</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="clearCanvas" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>clear<wbr/>Canvas</span><a href="#clearCanvas" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -110,7 +110,7 @@ Manages all the webgpu resources here.</p>
 </div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L446">webgpu.ts:446</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L446">webgpu.ts:446</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="copyRawBytesToBuffer" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>copy<wbr/>Raw<wbr/>Bytes<wbr/>To<wbr/>Buffer</span><a href="#copyRawBytesToBuffer" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -139,7 +139,7 @@ Manages all the webgpu resources here.</p>
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L428">webgpu.ts:428</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/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>
 <h3 class="tsd-anchor-link"><span>create<wbr/>Shader</span><a href="#createShader" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
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@@ -160,7 +160,7 @@ via createComputePipeline</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L466">webgpu.ts:466</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L466">webgpu.ts:466</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="createShaderAsync" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>create<wbr/>Shader<wbr/>Async</span><a href="#createShaderAsync" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -181,7 +181,7 @@ via createComputePipelineAsync</p>
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 <aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/webgpu.ts#L478">webgpu.ts:478</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L478">webgpu.ts:478</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="dispose" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>dispose</span><a href="#dispose" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures">
@@ -191,7 +191,7 @@ via createComputePipelineAsync</p>
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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/dd709412e/web/src/webgpu.ts#L378">webgpu.ts:378</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L378">webgpu.ts:378</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="drawImageFromBuffer" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>draw<wbr/>Image<wbr/>From<wbr/>Buffer</span><a href="#drawImageFromBuffer" 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">
@@ -216,7 +216,7 @@ via createComputePipelineAsync</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/dd709412e/web/src/webgpu.ts#L413">webgpu.ts:413</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L413">webgpu.ts:413</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member"><a id="getDeviceAPI" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>get<wbr/>DeviceAPI</span><a href="#getDeviceAPI" 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">
@@ -232,7 +232,7 @@ via createComputePipelineAsync</p>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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 <li><a href="assert.html" class="current"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-function)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-64-path"></rect><path d="M9.39 16V7.24H14.55V8.224H10.446V11.128H14.238V12.112H10.47V16H9.39Z" fill="var(--color-text)" id="icon-64-text"></path></svg><span>assert</span></a></li>
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+<li><a href="deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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index 926e87c337..ab7158f2c1 100644
--- a/docs/reference/api/typedoc/functions/createPolyfillWASI.html
+++ b/docs/reference/api/typedoc/functions/createPolyfillWASI.html
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/compact.ts#L55">compact.ts:55</a></li></ul></aside></li></ul></section></div>
 <div class="col-sidebar">
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 <div class="tsd-navigation settings">
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
 <li><a href="../interfaces/_internal_.NDArrayCacheEntry.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Cache<wbr/>Entry</span></a></li>
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 <li><a href="../types/_internal_.FObjectConstructor.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-type-alias)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-4194304-path"></rect><path d="M11.31 16V8.224H8.91V7.24H14.79V8.224H12.39V16H11.31Z" fill="var(--color-text)" id="icon-4194304-text"></path></svg><span>FObject<wbr/>Constructor</span></a></li>
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 <li><a href="assert.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-function)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-64-path"></rect><path d="M9.39 16V7.24H14.55V8.224H10.446V11.128H14.238V12.112H10.47V16H9.39Z" fill="var(--color-text)" id="icon-64-text"></path></svg><span>assert</span></a></li>
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+<li><a href="deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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diff --git a/docs/reference/api/typedoc/functions/createPolyfillWASI.html b/docs/reference/api/typedoc/functions/deleteNDArrayCache.html
similarity index 84%
copy from docs/reference/api/typedoc/functions/createPolyfillWASI.html
copy to docs/reference/api/typedoc/functions/deleteNDArrayCache.html
index 926e87c337..3f8041b2da 100644
--- a/docs/reference/api/typedoc/functions/createPolyfillWASI.html
+++ b/docs/reference/api/typedoc/functions/deleteNDArrayCache.html
@@ -1,4 +1,4 @@
-<!DOCTYPE html><html class="default" lang="en"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>createPolyfillWASI | tvmjs</title><meta name="description" content="Documentation for tvmjs"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script defer src="../assets/main.js"></script><script async src="../assets/search.js" [...]
+<!DOCTYPE html><html class="default" lang="en"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>deleteNDArrayCache | tvmjs</title><meta name="description" content="Documentation for tvmjs"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script defer src="../assets/main.js"></script><script async src="../assets/search.js" [...]
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@@ -13,18 +13,24 @@
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-<li><a href="createPolyfillWASI.html">createPolyfillWASI</a></li></ul>
-<h1>Function createPolyfillWASI</h1></div>
+<li><a href="deleteNDArrayCache.html">deleteNDArrayCache</a></li></ul>
+<h1>Function deleteNDArrayCache</h1></div>
 <section class="tsd-panel">
 <ul class="tsd-signatures">
-<li class="tsd-signature tsd-anchor-link" id="createPolyfillWASI"><span class="tsd-kind-call-signature">create<wbr/>PolyfillWASI</span><span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><a href="../interfaces/LibraryProvider.html" class="tsd-signature-type tsd-kind-interface">LibraryProvider</a><a href="#createPolyfillWASI" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler [...]
+<li class="tsd-signature tsd-anchor-link" id="deleteNDArrayCache"><span class="tsd-kind-call-signature">deleteNDArray<wbr/>Cache</span><span class="tsd-signature-symbol">(</span><span class="tsd-kind-parameter">cacheUrl</span>, <span class="tsd-kind-parameter">cacheScope</span><span class="tsd-signature-symbol">?</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type ">Promise</span><span class="tsd-signature-symbol">& [...]
 <li class="tsd-description">
-<div class="tsd-comment tsd-typography"><p>Create a WASI based on current environment.</p>
+<div class="tsd-comment tsd-typography"><p>Given cacheUrl, search up items to delete based on cacheUrl/ndarray-cache.json</p>
 </div>
-<h4 class="tsd-returns-title">Returns <a href="../interfaces/LibraryProvider.html" class="tsd-signature-type tsd-kind-interface">LibraryProvider</a></h4><p>A wasi that can run on broswer or local.</p>
-<aside class="tsd-sources">
+<div class="tsd-parameters">
+<h4 class="tsd-parameters-title">Parameters</h4>
+<ul class="tsd-parameter-list">
+<li>
+<h5><span class="tsd-kind-parameter">cacheUrl</span>: <span class="tsd-signature-type">string</span></h5></li>
+<li>
+<h5><span class="tsd-kind-parameter">cacheScope</span>: <span class="tsd-signature-type">string</span><span class="tsd-signature-symbol"> = &quot;tvmjs&quot;</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">void</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L2478">runtime.ts:2478</a></li></ul></aside></li></ul></section></div>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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-<li><a href="createPolyfillWASI.html" class="current"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>create<wbr/>PolyfillWASI</span></a></li>
+<li><a href="createPolyfillWASI.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>create<wbr/>PolyfillWASI</span></a></li>
+<li><a href="deleteNDArrayCache.html" class="current"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 <li><a href="hasNDArrayInCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>hasNDArray<wbr/>In<wbr/>Cache</span></a></li>
 <li><a href="instantiate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>instantiate</span></a></li>
diff --git a/docs/reference/api/typedoc/functions/detectGPUDevice.html b/docs/reference/api/typedoc/functions/detectGPUDevice.html
index 0c58a7066d..f5f0653fb0 100644
--- a/docs/reference/api/typedoc/functions/detectGPUDevice.html
+++ b/docs/reference/api/typedoc/functions/detectGPUDevice.html
@@ -23,7 +23,7 @@
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 <ul>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L36">webgpu.ts:36</a></li></ul></aside></li></ul></section></div>
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+<li><a href="deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
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diff --git a/docs/reference/api/typedoc/index.html b/docs/reference/api/typedoc/index.html
index 3e2286ce71..968b10e821 100644
--- a/docs/reference/api/typedoc/index.html
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+<a href="functions/deleteNDArrayCache.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a>
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+<li><a href="interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Artifact<wbr/>Cache<wbr/>Template</span></a></li>
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+<li><a href="functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 <ul>
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 <section class="tsd-panel-group tsd-index-group">
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/types.ts#L52">types.ts:52</a></li></ul></aside></section></section></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/types.ts#L52">types.ts:52</a></li></ul></aside></section></section></div>
 <div class="col-sidebar">
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+<li><a href="_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span></a></li>
+<li><a href="_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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@@ -20,7 +20,7 @@
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/webgpu.ts#L30">webgpu.ts:30</a></li></ul></aside></section></section></div>
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+<li><a href="_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span></a></li>
+<li><a href="_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<!DOCTYPE html><html class="default" lang="en"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>ArtifactCacheTemplate | tvmjs</title><meta name="description" content="Documentation for tvmjs"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script defer src="../assets/main.js"></script><script async src="../assets/search. [...]
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+<section class="tsd-panel tsd-member"><a id="hasAllKeys" class="tsd-anchor"></a>
+<h3 class="tsd-anchor-link"><span>has<wbr/>All<wbr/>Keys</span><a href="#hasAllKeys" aria-label="Permalink" class="tsd-anchor-icon"><svg 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/40ec46970/web/src/artifact_cache.ts#L13">artifact_cache.ts:13</a></li></ul></aside></li></ul></section></section></div>
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+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L966">runtime.ts:966</a></li></ul></aside></section></section></div>
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 <li><a href="../classes/_internal_.TVMString.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>TVMString</span></a></li>
 <li><a href="../classes/_internal_.WebGPUContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>WebGPUContext</span></a></li>
-<li><a href="_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Function<wbr/>Info</span></a></li>
+<li><a href="_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span></a></li>
+<li><a href="_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
 <li><a href="_internal_.NDArrayCacheEntry.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Cache<wbr/>Entry</span></a></li>
 <li><a href="_internal_.NDArrayShardEntry.html" class="current"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Shard<wbr/>Entry</span></a></li>
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@@ -122,6 +123,7 @@
 <li><a href="../types/PackedFunc.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-4194304-path"></use><use href="#icon-4194304-text"></use></svg><span>Packed<wbr/>Func</span></a></li>
 <li><a href="../functions/assert.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-function)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-64-path"></rect><path d="M9.39 16V7.24H14.55V8.224H10.446V11.128H14.238V12.112H10.47V16H9.39Z" fill="var(--color-text)" id="icon-64-text"></path></svg><span>assert</span></a></li>
 <li><a href="../functions/createPolyfillWASI.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>create<wbr/>PolyfillWASI</span></a></li>
+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
 <li><a href="../functions/detectGPUDevice.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>detectGPUDevice</span></a></li>
 <li><a href="../functions/hasNDArrayInCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>hasNDArray<wbr/>In<wbr/>Cache</span></a></li>
 <li><a href="../functions/instantiate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>instantiate</span></a></li>
diff --git a/docs/reference/api/typedoc/modules/_internal_.html b/docs/reference/api/typedoc/modules/_internal_.html
index adaafa3d26..a6d1052ee7 100644
--- a/docs/reference/api/typedoc/modules/_internal_.html
+++ b/docs/reference/api/typedoc/modules/_internal_.html
@@ -36,7 +36,8 @@
 </div></section>
 <section class="tsd-index-section">
 <h3 class="tsd-index-heading">Interfaces</h3>
-<div class="tsd-index-list"><a href="../interfaces/_internal_.FunctionInfo.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>F [...]
+<div class="tsd-index-list"><a href="../interfaces/_internal_.ArtifactCacheTemplate.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></sv [...]
+<a href="../interfaces/_internal_.FunctionInfo.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a>
 <a href="../interfaces/_internal_.NDArrayCacheEntry.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Cache<wbr/>Entry</span></a>
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@@ -79,6 +80,7 @@
 <li><a href="../classes/_internal_.RuntimeContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>Runtime<wbr/>Context</span></a></li>
 <li><a href="../classes/_internal_.TVMString.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>TVMString</span></a></li>
 <li><a href="../classes/_internal_.WebGPUContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>WebGPUContext</span></a></li>
+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Artifact<wbr/>Cache<wbr/>Template</span></a></li>
 <li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
 <li><a href="../interfaces/_internal_.NDArrayCacheEntry.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Cache<wbr/>Entry</span></a></li>
 <li><a href="../interfaces/_internal_.NDArrayShardEntry.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>NDArray<wbr/>Shard<wbr/>Entry</span></a></li>
@@ -107,6 +109,7 @@
 <li><a href="../types/PackedFunc.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-4194304-path"></use><use href="#icon-4194304-text"></use></svg><span>Packed<wbr/>Func</span></a></li>
 <li><a href="../functions/assert.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-function)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-64-path"></rect><path d="M9.39 16V7.24H14.55V8.224H10.446V11.128H14.238V12.112H10.47V16H9.39Z" fill="var(--color-text)" id="icon-64-text"></path></svg><span>assert</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 <li><a href="../functions/instantiate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>instantiate</span></a></li>
diff --git a/docs/reference/api/typedoc/types/InitProgressCallback.html b/docs/reference/api/typedoc/types/InitProgressCallback.html
index 31849cfb9d..c5103ca320 100644
--- a/docs/reference/api/typedoc/types/InitProgressCallback.html
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@@ -30,7 +30,7 @@
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-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L986">runtime.ts:986</a></li></ul></aside></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L987">runtime.ts:987</a></li></ul></aside></div>
 <div class="col-sidebar">
 <div class="page-menu">
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@@ -61,7 +61,8 @@
 <li><a href="../classes/_internal_.RuntimeContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>Runtime<wbr/>Context</span></a></li>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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@@ -89,6 +90,7 @@
 <li><a href="PackedFunc.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-4194304-path"></use><use href="#icon-4194304-text"></use></svg><span>Packed<wbr/>Func</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 <li><a href="../functions/instantiate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>instantiate</span></a></li>
diff --git a/docs/reference/api/typedoc/types/PackedFunc.html b/docs/reference/api/typedoc/types/PackedFunc.html
index d1183dd467..813d1373f5 100644
--- a/docs/reference/api/typedoc/types/PackedFunc.html
+++ b/docs/reference/api/typedoc/types/PackedFunc.html
@@ -19,7 +19,7 @@
 <div class="tsd-comment tsd-typography"><p>Type for PackedFunc inthe TVMRuntime.</p>
 </div><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/apache/tvm/blob/dd709412e/web/src/runtime.ts#L36">runtime.ts:36</a></li></ul></aside></div>
+<li>Defined in <a href="https://github.com/apache/tvm/blob/40ec46970/web/src/runtime.ts#L37">runtime.ts:37</a></li></ul></aside></div>
 <div class="col-sidebar">
 <div class="page-menu">
 <div class="tsd-navigation settings">
@@ -50,7 +50,8 @@
 <li><a href="../classes/_internal_.RuntimeContext.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-128-path"></use><use href="#icon-128-text"></use></svg><span>Runtime<wbr/>Context</span></a></li>
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+<li><a href="../interfaces/_internal_.ArtifactCacheTemplate.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Artifact<wbr/>Cache<wbr/>Template</span [...]
+<li><a href="../interfaces/_internal_.FunctionInfo.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-256-path"></use><use href="#icon-256-text"></use></svg><span>Function<wbr/>Info</span></a></li>
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+<li><a href="../functions/deleteNDArrayCache.html"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-64-path"></use><use href="#icon-64-text"></use></svg><span>deleteNDArray<wbr/>Cache</span></a></li>
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 </tbody>
diff --git a/docs/tutorial/auto_scheduler_matmul_x86.html b/docs/tutorial/auto_scheduler_matmul_x86.html
index 6107ebee79..f40706848f 100644
--- a/docs/tutorial/auto_scheduler_matmul_x86.html
+++ b/docs/tutorial/auto_scheduler_matmul_x86.html
@@ -589,7 +589,7 @@ class Module:
 <span class="p">)</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 93.449 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 93.042 ms
 </pre></div>
 </div>
 </div>
@@ -661,7 +661,7 @@ 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  17.720 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  19.540 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorial-auto-scheduler-matmul-x86-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/eac4389b114db015e95cb3cdf8b86b83/auto_scheduler_matmul_x86.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">auto_scheduler_matmul_x86.py</span></code></a></p>
diff --git a/docs/tutorial/autotvm_matmul_x86.html b/docs/tutorial/autotvm_matmul_x86.html
index 07535b67f3..26e727a7e5 100644
--- a/docs/tutorial/autotvm_matmul_x86.html
+++ b/docs/tutorial/autotvm_matmul_x86.html
@@ -700,16 +700,16 @@ reduce variance, we take 5 measurements and average them.</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>waiting for device...
 device available
 Get devices for measurement successfully!
-No: 1   GFLOPS: 10.32/10.32     result: MeasureResult(costs=(0.0260187832,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7063686847686768, timestamp=1708338659.9917269)       [(&#39;tile_y&#39;, [-1, 32]), (&#39;tile_x&#39;, [-1, 256])],None,85
-No: 2   GFLOPS: 0.51/10.32      result: MeasureResult(costs=(0.5255900928,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.666619539260864, timestamp=1708338668.6665368)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 1])],None,8
-No: 3   GFLOPS: 10.35/10.35     result: MeasureResult(costs=(0.025931175600000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6999287605285645, timestamp=1708338669.3384058)       [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 64])],None,63
-No: 4   GFLOPS: 9.73/10.35      result: MeasureResult(costs=(0.027588438799999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7359044551849365, timestamp=1708338670.0366158)       [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 64])],None,62
-No: 5   GFLOPS: 3.61/10.35      result: MeasureResult(costs=(0.0743391898,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.452099323272705, timestamp=1708338671.6099627)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 8])],None,38
-No: 6   GFLOPS: 2.02/10.35      result: MeasureResult(costs=(0.1330904792,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3837616443634033, timestamp=1708338673.9933755)       [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 4])],None,28
-No: 7   GFLOPS: 1.98/10.35      result: MeasureResult(costs=(0.135604258,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.427419424057007, timestamp=1708338676.4230852) [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 1])],None,3
-No: 8   GFLOPS: 13.98/13.98     result: MeasureResult(costs=(0.019206590000000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5729765892028809, timestamp=1708338676.9917262)       [(&#39;tile_y&#39;, [-1, 16]), (&#39;tile_x&#39;, [-1, 32])],None,54
-No: 9   GFLOPS: 12.10/13.98     result: MeasureResult(costs=(0.0221877238,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5923464298248291, timestamp=1708338677.6931167)       [(&#39;tile_y&#39;, [-1, 32]), (&#39;tile_x&#39;, [-1, 128])],None,75
-No: 10  GFLOPS: 4.48/13.98      result: MeasureResult(costs=(0.059951310599999995,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.1851580142974854, timestamp=1708338678.9165745)       [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 2])],None,12
+No: 1   GFLOPS: 13.52/13.52     result: MeasureResult(costs=(0.019855878200000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5977396965026855, timestamp=1708403749.1573048)       [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 256])],None,82
+No: 2   GFLOPS: 12.43/13.52     result: MeasureResult(costs=(0.0215930482,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.644538402557373, timestamp=1708403749.7606938)        [(&#39;tile_y&#39;, [-1, 4]), (&#39;tile_x&#39;, [-1, 128])],None,72
+No: 3   GFLOPS: 13.40/13.52     result: MeasureResult(costs=(0.020025174200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6629865169525146, timestamp=1708403750.3400686)       [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 128])],None,78
+No: 4   GFLOPS: 7.10/13.52      result: MeasureResult(costs=(0.0378319892,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8453638553619385, timestamp=1708403751.1921952)       [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 4])],None,21
+No: 5   GFLOPS: 1.06/13.52      result: MeasureResult(costs=(0.2536294136,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.310134172439575, timestamp=1708403755.6260414)        [(&#39;tile_y&#39;, [-1, 256]), (&#39;tile_x&#39;, [-1, 2])],None,18
+No: 6   GFLOPS: 12.10/13.52     result: MeasureResult(costs=(0.0221792298,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6235024929046631, timestamp=1708403756.2389832)       [(&#39;tile_y&#39;, [-1, 64]), (&#39;tile_x&#39;, [-1, 256])],None,86
+No: 7   GFLOPS: 2.07/13.52      result: MeasureResult(costs=(0.1297528456,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.3157236576080322, timestamp=1708403758.5657632)       [(&#39;tile_y&#39;, [-1, 8]), (&#39;tile_x&#39;, [-1, 1])],None,3
+No: 8   GFLOPS: 7.47/13.52      result: MeasureResult(costs=(0.0359419954,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8336803913116455, timestamp=1708403759.3992014)       [(&#39;tile_y&#39;, [-1, 2]), (&#39;tile_x&#39;, [-1, 8])],None,31
+No: 9   GFLOPS: 9.14/13.52      result: MeasureResult(costs=(0.0293813112,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6828923225402832, timestamp=1708403760.195342)        [(&#39;tile_y&#39;, [-1, 1]), (&#39;tile_x&#39;, [-1, 32])],None,50
+No: 10  GFLOPS: 8.41/13.52      result: MeasureResult(costs=(0.0319117384,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7190907001495361, timestamp=1708403760.954458)        [(&#39;tile_y&#39;, [-1, 1]), (&#39;tile_x&#39;, [-1, 16])],None,40
 </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 ceb9618f60..89d425bebf 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;: 493.17011977997026, &#39;median&#39;: 493.14711975002865, &#39;std&#39;: 2.4254435877078127}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{&#39;mean&#39;: 465.3329487299925, &#39;median&#39;: 465.1625409499957, &#39;std&#39;: 1.8629931775089623}
 </pre></div>
 </div>
 </div>
@@ -767,179 +767,177 @@ 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:   17.59/  20.14 GFLOPS | Progress: (4/20) | 9.29 s
-[Task  1/25]  Current/Best:   19.37/  20.39 GFLOPS | Progress: (8/20) | 12.56 s
-[Task  1/25]  Current/Best:   13.77/  21.43 GFLOPS | Progress: (12/20) | 14.99 s
-[Task  1/25]  Current/Best:   14.32/  21.43 GFLOPS | Progress: (16/20) | 18.61 s
-[Task  1/25]  Current/Best:   12.53/  21.43 GFLOPS | Progress: (20/20) | 21.68 s Done.
+[Task  1/25]  Current/Best:   13.07/  20.46 GFLOPS | Progress: (4/20) | 7.76 s
+[Task  1/25]  Current/Best:    3.56/  23.29 GFLOPS | Progress: (8/20) | 11.02 s
+[Task  1/25]  Current/Best:    5.75/  23.29 GFLOPS | Progress: (12/20) | 14.04 s
+[Task  1/25]  Current/Best:   11.49/  23.29 GFLOPS | Progress: (16/20) | 16.55 s
+[Task  1/25]  Current/Best:   16.23/  23.29 GFLOPS | Progress: (20/20) | 18.98 s Done.
 
 [Task  2/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  2/25]  Current/Best:   12.78/  20.71 GFLOPS | Progress: (4/20) | 4.14 s
-[Task  2/25]  Current/Best:    4.71/  20.71 GFLOPS | Progress: (8/20) | 5.77 s
-[Task  2/25]  Current/Best:    9.26/  20.71 GFLOPS | Progress: (12/20) | 7.40 s
-[Task  2/25]  Current/Best:    6.77/  20.71 GFLOPS | Progress: (16/20) | 9.05 s
-[Task  2/25]  Current/Best:   14.08/  20.71 GFLOPS | Progress: (20/20) | 10.68 s Done.
+[Task  2/25]  Current/Best:    8.13/  14.83 GFLOPS | Progress: (4/20) | 4.25 s
+[Task  2/25]  Current/Best:   14.42/  17.69 GFLOPS | Progress: (8/20) | 5.99 s
+[Task  2/25]  Current/Best:   21.94/  21.94 GFLOPS | Progress: (12/20) | 7.23 s
+[Task  2/25]  Current/Best:   16.55/  21.94 GFLOPS | Progress: (16/20) | 8.73 s
+[Task  2/25]  Current/Best:    7.48/  22.21 GFLOPS | Progress: (20/20) | 9.97 s Done.
 
 [Task  3/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  3/25]  Current/Best:   18.56/  19.63 GFLOPS | Progress: (4/20) | 4.55 s
-[Task  3/25]  Current/Best:   13.80/  19.63 GFLOPS | Progress: (8/20) | 7.31 s
-[Task  3/25]  Current/Best:   10.15/  19.81 GFLOPS | Progress: (12/20) | 10.80 s
-[Task  3/25]  Current/Best:   15.67/  19.81 GFLOPS | Progress: (16/20) | 13.30 s
-[Task  3/25]  Current/Best:    9.83/  23.70 GFLOPS | Progress: (20/20) | 16.18 s Done.
+[Task  3/25]  Current/Best:    3.28/  15.98 GFLOPS | Progress: (4/20) | 6.02 s
+[Task  3/25]  Current/Best:   23.91/  23.91 GFLOPS | Progress: (8/20) | 8.44 s
+[Task  3/25]  Current/Best:   20.44/  23.91 GFLOPS | Progress: (12/20) | 12.14 s
+[Task  3/25]  Current/Best:   15.18/  23.91 GFLOPS | Progress: (16/20) | 14.26 s
+[Task  3/25]  Current/Best:   12.34/  23.91 GFLOPS | Progress: (20/20) | 16.60 s Done.
 
 [Task  4/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  4/25]  Current/Best:   15.08/  16.30 GFLOPS | Progress: (4/20) | 5.34 s
-[Task  4/25]  Current/Best:   18.23/  18.23 GFLOPS | Progress: (8/20) | 9.75 s
-[Task  4/25]  Current/Best:    7.90/  19.27 GFLOPS | Progress: (12/20) | 12.29 s
-[Task  4/25]  Current/Best:   17.07/  21.60 GFLOPS | Progress: (16/20) | 14.05 s
-[Task  4/25]  Current/Best:    6.16/  21.60 GFLOPS | Progress: (20/20) | 18.67 s Done.
+[Task  4/25]  Current/Best:   17.56/  17.56 GFLOPS | Progress: (4/20) | 4.48 s
+[Task  4/25]  Current/Best:    6.34/  22.46 GFLOPS | Progress: (8/20) | 6.28 s
+[Task  4/25]  Current/Best:   11.15/  22.46 GFLOPS | Progress: (12/20) | 9.44 s
+[Task  4/25]  Current/Best:    5.33/  22.46 GFLOPS | Progress: (16/20) | 11.20 s
+[Task  4/25]  Current/Best:   15.50/  22.46 GFLOPS | Progress: (20/20) | 14.10 s Done.
 
 [Task  5/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  5/25]  Current/Best:    5.83/  17.07 GFLOPS | Progress: (4/20) | 5.07 s
-[Task  5/25]  Current/Best:   20.25/  20.25 GFLOPS | Progress: (8/20) | 7.17 s
-[Task  5/25]  Current/Best:   10.93/  20.25 GFLOPS | Progress: (12/20) | 9.61 s
-[Task  5/25]  Current/Best:   11.24/  20.25 GFLOPS | Progress: (16/20) | 11.77 s
-[Task  5/25]  Current/Best:   15.74/  20.25 GFLOPS | Progress: (20/20) | 13.87 s Done.
+[Task  5/25]  Current/Best:   12.05/  18.44 GFLOPS | Progress: (4/20) | 4.44 s
+[Task  5/25]  Current/Best:   19.58/  23.15 GFLOPS | Progress: (8/20) | 6.19 s
+[Task  5/25]  Current/Best:   18.73/  23.15 GFLOPS | Progress: (12/20) | 8.29 s
+[Task  5/25]  Current/Best:   16.60/  23.15 GFLOPS | Progress: (16/20) | 10.00 s
+[Task  5/25]  Current/Best:   15.56/  23.15 GFLOPS | Progress: (20/20) | 12.42 s Done.
 
 [Task  6/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  6/25]  Current/Best:   15.96/  15.96 GFLOPS | Progress: (4/20) | 5.00 s
-[Task  6/25]  Current/Best:   13.59/  15.96 GFLOPS | Progress: (8/20) | 8.12 s
-[Task  6/25]  Current/Best:    3.44/  15.96 GFLOPS | Progress: (12/20) | 12.20 s
-[Task  6/25]  Current/Best:   11.39/  15.96 GFLOPS | Progress: (16/20) | 14.66 s
-[Task  6/25]  Current/Best:   20.40/  20.40 GFLOPS | Progress: (20/20) | 16.81 s Done.
+[Task  6/25]  Current/Best:   20.52/  20.52 GFLOPS | Progress: (4/20) | 6.48 s
+[Task  6/25]  Current/Best:   12.04/  20.52 GFLOPS | Progress: (8/20) | 8.66 s
+[Task  6/25]  Current/Best:   13.76/  20.52 GFLOPS | Progress: (12/20) | 12.36 s
+[Task  6/25]  Current/Best:   16.60/  20.52 GFLOPS | Progress: (16/20) | 15.00 s
+[Task  6/25]  Current/Best:   14.32/  20.52 GFLOPS | Progress: (20/20) | 19.65 s Done.
 
 [Task  7/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  7/25]  Current/Best:    5.78/  17.67 GFLOPS | Progress: (4/20) | 5.43 s
-[Task  7/25]  Current/Best:    9.54/  17.67 GFLOPS | Progress: (8/20) | 8.08 s
-[Task  7/25]  Current/Best:    9.43/  17.67 GFLOPS | Progress: (12/20) | 10.65 s
-[Task  7/25]  Current/Best:   22.65/  22.65 GFLOPS | Progress: (16/20) | 13.02 s
-[Task  7/25]  Current/Best:   17.97/  22.65 GFLOPS | Progress: (20/20) | 15.09 s Done.
+[Task  7/25]  Current/Best:    6.48/  19.67 GFLOPS | Progress: (4/20) | 4.73 s
+[Task  7/25]  Current/Best:   14.22/  19.67 GFLOPS | Progress: (8/20) | 7.80 s
+[Task  7/25]  Current/Best:    6.47/  19.67 GFLOPS | Progress: (12/20) | 10.18 s
+[Task  7/25]  Current/Best:   11.18/  21.97 GFLOPS | Progress: (16/20) | 12.32 s
+[Task  7/25]  Current/Best:   18.90/  21.97 GFLOPS | Progress: (20/20) | 14.80 s Done.
 
 [Task  8/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  8/25]  Current/Best:    6.62/  15.49 GFLOPS | Progress: (4/20) | 8.89 s
-[Task  8/25]  Current/Best:   15.75/  15.75 GFLOPS | Progress: (8/20) | 11.29 s
-[Task  8/25]  Current/Best:   11.57/  15.75 GFLOPS | Progress: (12/20) | 22.77 s
-[Task  8/25]  Current/Best:    5.22/  15.75 GFLOPS | Progress: (16/20) | 28.82 s
-[Task  8/25]  Current/Best:    4.00/  15.75 GFLOPS | Progress: (20/20) | 31.45 s
+[Task  8/25]  Current/Best:   13.38/  17.30 GFLOPS | Progress: (4/20) | 5.11 s
+[Task  8/25]  Current/Best:   11.30/  17.30 GFLOPS | Progress: (8/20) | 9.69 s
+[Task  8/25]  Current/Best:   11.76/  17.30 GFLOPS | Progress: (12/20) | 12.07 s
+[Task  8/25]  Current/Best:   12.98/  19.98 GFLOPS | Progress: (16/20) | 17.26 s
+[Task  8/25]  Current/Best:   15.63/  19.98 GFLOPS | Progress: (20/20) | 28.62 s
 [Task  9/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task  9/25]  Current/Best:   10.65/  17.62 GFLOPS | Progress: (4/20) | 8.71 s
-[Task  9/25]  Current/Best:   11.02/  17.81 GFLOPS | Progress: (8/20) | 13.17 s
-[Task  9/25]  Current/Best:   15.42/  17.81 GFLOPS | Progress: (12/20) | 24.62 s
-[Task  9/25]  Current/Best:   11.55/  17.81 GFLOPS | Progress: (16/20) | 27.65 s
-[Task  9/25]  Current/Best:    3.41/  22.82 GFLOPS | Progress: (20/20) | 36.84 s Done.
+[Task  9/25]  Current/Best:    8.93/  16.75 GFLOPS | Progress: (4/20) | 10.74 s
+[Task  9/25]  Current/Best:   19.15/  19.78 GFLOPS | Progress: (8/20) | 13.48 s
+[Task  9/25]  Current/Best:   11.05/  21.49 GFLOPS | Progress: (12/20) | 17.05 s
+[Task  9/25]  Current/Best:    9.89/  21.49 GFLOPS | Progress: (16/20) | 22.11 s
+[Task  9/25]  Current/Best:   13.20/  21.49 GFLOPS | Progress: (20/20) | 26.35 s Done.
 
 [Task 10/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 10/25]  Current/Best:   14.81/  14.81 GFLOPS | Progress: (4/20) | 5.35 s
-[Task 10/25]  Current/Best:   13.13/  20.22 GFLOPS | Progress: (8/20) | 7.51 s
-[Task 10/25]  Current/Best:    9.58/  20.22 GFLOPS | Progress: (12/20) | 9.54 s
-[Task 10/25]  Current/Best:    5.06/  21.13 GFLOPS | Progress: (16/20) | 11.71 s
-[Task 10/25]  Current/Best:   14.28/  21.13 GFLOPS | Progress: (20/20) | 13.68 s Done.
+[Task 10/25]  Current/Best:   14.48/  18.02 GFLOPS | Progress: (4/20) | 5.43 s
+[Task 10/25]  Current/Best:    6.22/  18.02 GFLOPS | Progress: (8/20) | 7.33 s
+[Task 10/25]  Current/Best:   14.69/  18.02 GFLOPS | Progress: (12/20) | 9.35 s
+[Task 10/25]  Current/Best:   16.65/  18.02 GFLOPS | Progress: (16/20) | 12.43 s
+[Task 10/25]  Current/Best:   14.87/  18.86 GFLOPS | Progress: (20/20) | 14.31 s Done.
 
 [Task 11/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 11/25]  Current/Best:   11.16/  12.39 GFLOPS | Progress: (4/20) | 5.74 s
-[Task 11/25]  Current/Best:   23.49/  23.49 GFLOPS | Progress: (8/20) | 7.58 s
-[Task 11/25]  Current/Best:   11.67/  23.49 GFLOPS | Progress: (12/20) | 11.43 s
-[Task 11/25]  Current/Best:   15.87/  23.49 GFLOPS | Progress: (16/20) | 15.22 s
-[Task 11/25]  Current/Best:    3.10/  23.49 GFLOPS | Progress: (20/20) | 18.07 s Done.
+[Task 11/25]  Current/Best:   15.06/  19.53 GFLOPS | Progress: (4/20) | 4.87 s
+[Task 11/25]  Current/Best:   14.75/  21.10 GFLOPS | Progress: (8/20) | 8.58 s
+[Task 11/25]  Current/Best:    9.88/  22.72 GFLOPS | Progress: (12/20) | 10.63 s
+[Task 11/25]  Current/Best:    1.63/  22.72 GFLOPS | Progress: (16/20) | 15.06 s
+[Task 11/25]  Current/Best:    7.89/  22.72 GFLOPS | Progress: (20/20) | 17.25 s Done.
 
 [Task 12/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 12/25]  Current/Best:    9.08/  15.88 GFLOPS | Progress: (4/20) | 5.26 s
-[Task 12/25]  Current/Best:   17.75/  17.75 GFLOPS | Progress: (8/20) | 8.82 s
-[Task 12/25]  Current/Best:   13.40/  17.75 GFLOPS | Progress: (12/20) | 12.40 s
-[Task 12/25]  Current/Best:   13.44/  17.75 GFLOPS | Progress: (16/20) | 14.80 s
-[Task 12/25]  Current/Best:   15.49/  17.75 GFLOPS | Progress: (20/20) | 17.25 s Done.
+[Task 12/25]  Current/Best:    5.53/  14.93 GFLOPS | Progress: (4/20) | 9.81 s
+[Task 12/25]  Current/Best:   12.90/  16.03 GFLOPS | Progress: (8/20) | 12.10 s
+[Task 12/25]  Current/Best:    6.18/  17.06 GFLOPS | Progress: (12/20) | 15.00 s
+[Task 12/25]  Current/Best:    5.30/  17.06 GFLOPS | Progress: (16/20) | 18.38 s
+[Task 12/25]  Current/Best:    3.43/  17.06 GFLOPS | Progress: (20/20) | 22.29 s Done.
 
 [Task 13/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 13/25]  Current/Best:   21.00/  21.00 GFLOPS | Progress: (4/20) | 4.77 s
-[Task 13/25]  Current/Best:    6.98/  21.00 GFLOPS | Progress: (8/20) | 7.87 s
-[Task 13/25]  Current/Best:    3.10/  21.00 GFLOPS | Progress: (12/20) | 12.29 s
-[Task 13/25]  Current/Best:   20.13/  21.00 GFLOPS | Progress: (16/20) | 14.27 s
-[Task 13/25]  Current/Best:    5.51/  21.00 GFLOPS | Progress: (20/20) | 16.97 s Done.
+[Task 13/25]  Current/Best:   12.58/  15.63 GFLOPS | Progress: (4/20) | 4.88 s
+[Task 13/25]  Current/Best:   10.98/  20.34 GFLOPS | Progress: (8/20) | 8.54 s
+[Task 13/25]  Current/Best:   17.06/  20.34 GFLOPS | Progress: (12/20) | 11.22 s
+[Task 13/25]  Current/Best:   17.19/  20.34 GFLOPS | Progress: (16/20) | 13.63 s
+[Task 13/25]  Current/Best:    8.80/  20.41 GFLOPS | Progress: (20/20) | 16.73 s Done.
 
 [Task 14/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 14/25]  Current/Best:    6.38/  13.78 GFLOPS | Progress: (4/20) | 14.45 s
-[Task 14/25]  Current/Best:    5.59/  15.88 GFLOPS | Progress: (8/20) | 21.74 s
-[Task 14/25]  Current/Best:   12.34/  15.88 GFLOPS | Progress: (12/20) | 25.82 s
-[Task 14/25]  Current/Best:    4.72/  15.88 GFLOPS | Progress: (16/20) | 28.75 s
-[Task 14/25]  Current/Best:   14.45/  15.88 GFLOPS | Progress: (20/20) | 31.28 s Done.
+[Task 14/25]  Current/Best:   12.16/  12.16 GFLOPS | Progress: (4/20) | 8.91 s
+[Task 14/25]  Current/Best:   22.00/  22.00 GFLOPS | Progress: (8/20) | 16.51 s
+[Task 14/25]  Current/Best:   12.95/  22.00 GFLOPS | Progress: (12/20) | 22.79 s
+[Task 14/25]  Current/Best:    3.73/  22.00 GFLOPS | Progress: (16/20) | 30.83 s
+[Task 14/25]  Current/Best:   14.06/  22.00 GFLOPS | Progress: (20/20) | 35.45 s Done.
 
 [Task 15/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 15/25]  Current/Best:   18.59/  18.59 GFLOPS | Progress: (4/20) | 6.47 s
-[Task 15/25]  Current/Best:   20.40/  21.16 GFLOPS | Progress: (8/20) | 13.28 s
-[Task 15/25]  Current/Best:   13.37/  21.16 GFLOPS | Progress: (12/20) | 15.81 s
-[Task 15/25]  Current/Best:   17.87/  21.16 GFLOPS | Progress: (16/20) | 26.89 s
-[Task 15/25]  Current/Best:   10.24/  21.16 GFLOPS | Progress: (20/20) | 32.17 s
+[Task 15/25]  Current/Best:    9.25/  20.55 GFLOPS | Progress: (4/20) | 4.99 s
+[Task 15/25]  Current/Best:   16.05/  20.55 GFLOPS | Progress: (8/20) | 12.45 s
+[Task 15/25]  Current/Best:   13.85/  21.64 GFLOPS | Progress: (12/20) | 14.50 s
+[Task 15/25]  Current/Best:   17.65/  21.64 GFLOPS | Progress: (16/20) | 19.06 s
+[Task 15/25]  Current/Best:   13.92/  21.64 GFLOPS | Progress: (20/20) | 21.27 s Done.
+
 [Task 16/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 16/25]  Current/Best:   16.41/  16.41 GFLOPS | Progress: (4/20) | 4.78 s
-[Task 16/25]  Current/Best:    8.70/  16.41 GFLOPS | Progress: (8/20) | 7.69 s
-[Task 16/25]  Current/Best:   14.56/  16.41 GFLOPS | Progress: (12/20) | 10.11 s
-[Task 16/25]  Current/Best:   10.89/  20.41 GFLOPS | Progress: (16/20) | 13.58 s
-[Task 16/25]  Current/Best:    7.38/  20.41 GFLOPS | Progress: (20/20) | 15.62 s Done.
+[Task 16/25]  Current/Best:   15.61/  19.39 GFLOPS | Progress: (4/20) | 5.51 s
+[Task 16/25]  Current/Best:   11.59/  19.39 GFLOPS | Progress: (8/20) | 7.34 s
+[Task 16/25]  Current/Best:   13.81/  19.44 GFLOPS | Progress: (12/20) | 9.38 s
+[Task 16/25]  Current/Best:   10.25/  19.44 GFLOPS | Progress: (16/20) | 12.41 s
+[Task 16/25]  Current/Best:   18.73/  19.44 GFLOPS | Progress: (20/20) | 14.23 s Done.
 
 [Task 17/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 17/25]  Current/Best:   12.84/  22.36 GFLOPS | Progress: (4/20) | 4.80 s
-[Task 17/25]  Current/Best:    8.22/  22.36 GFLOPS | Progress: (8/20) | 7.72 s
-[Task 17/25]  Current/Best:   12.19/  22.36 GFLOPS | Progress: (12/20) | 10.63 s Done.
- Done.
-
-[Task 17/25]  Current/Best:    9.49/  22.36 GFLOPS | Progress: (16/20) | 13.94 s
-[Task 17/25]  Current/Best:   21.32/  22.36 GFLOPS | Progress: (20/20) | 17.51 s Done.
+[Task 17/25]  Current/Best:   24.07/  24.07 GFLOPS | Progress: (4/20) | 5.57 s
+[Task 17/25]  Current/Best:   10.21/  24.07 GFLOPS | Progress: (8/20) | 8.89 s
+[Task 17/25]  Current/Best:   21.40/  24.07 GFLOPS | Progress: (12/20) | 12.39 s
+[Task 17/25]  Current/Best:   14.19/  24.07 GFLOPS | Progress: (16/20) | 15.26 s
+[Task 17/25]  Current/Best:   22.78/  24.07 GFLOPS | Progress: (20/20) | 17.94 s Done.
 
 [Task 18/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 18/25]  Current/Best:   18.26/  21.13 GFLOPS | Progress: (4/20) | 5.09 s
-[Task 18/25]  Current/Best:   16.44/  21.13 GFLOPS | Progress: (8/20) | 8.79 s
-[Task 18/25]  Current/Best:   19.59/  21.13 GFLOPS | Progress: (12/20) | 11.27 s
-[Task 18/25]  Current/Best:   11.40/  21.80 GFLOPS | Progress: (16/20) | 16.12 s
-[Task 18/25]  Current/Best:   13.90/  21.96 GFLOPS | Progress: (20/20) | 18.87 s Done.
+[Task 18/25]  Current/Best:   19.47/  23.23 GFLOPS | Progress: (4/20) | 4.61 s
+[Task 18/25]  Current/Best:   17.31/  23.23 GFLOPS | Progress: (8/20) | 9.68 s
+[Task 18/25]  Current/Best:    6.34/  23.23 GFLOPS | Progress: (12/20) | 13.71 s
+[Task 18/25]  Current/Best:   13.06/  23.23 GFLOPS | Progress: (16/20) | 16.79 s
+[Task 18/25]  Current/Best:    8.57/  23.23 GFLOPS | Progress: (20/20) | 19.19 s Done.
 
 [Task 19/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 19/25]  Current/Best:    9.22/  21.90 GFLOPS | Progress: (4/20) | 6.46 s
-[Task 19/25]  Current/Best:   12.15/  21.90 GFLOPS | Progress: (8/20) | 10.64 s
-[Task 19/25]  Current/Best:   11.30/  21.90 GFLOPS | Progress: (12/20) | 15.36 s
-[Task 19/25]  Current/Best:   19.04/  21.90 GFLOPS | Progress: (16/20) | 19.46 s
-[Task 19/25]  Current/Best:   12.19/  21.98 GFLOPS | Progress: (20/20) | 23.25 s Done.
+[Task 19/25]  Current/Best:    9.87/  22.46 GFLOPS | Progress: (4/20) | 5.58 s
+[Task 19/25]  Current/Best:    1.60/  22.46 GFLOPS | Progress: (8/20) | 9.53 s
+[Task 19/25]  Current/Best:   12.54/  22.46 GFLOPS | Progress: (12/20) | 15.31 s
+[Task 19/25]  Current/Best:   10.68/  22.46 GFLOPS | Progress: (16/20) | 18.61 s
+[Task 19/25]  Current/Best:    5.53/  22.46 GFLOPS | Progress: (20/20) | 21.88 s Done.
 
 [Task 20/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 20/25]  Current/Best:   17.53/  17.53 GFLOPS | Progress: (4/20) | 10.61 s
-[Task 20/25]  Current/Best:   10.51/  18.25 GFLOPS | Progress: (8/20) | 19.76 s
-[Task 20/25]  Current/Best:   12.15/  18.25 GFLOPS | Progress: (12/20) | 22.96 s
-[Task 20/25]  Current/Best:   14.85/  18.25 GFLOPS | Progress: (16/20) | 30.22 s
-[Task 20/25]  Current/Best:   12.00/  18.25 GFLOPS | Progress: (20/20) | 42.01 s
+[Task 20/25]  Current/Best:   12.64/  19.32 GFLOPS | Progress: (4/20) | 4.57 s
+[Task 20/25]  Current/Best:    5.34/  22.45 GFLOPS | Progress: (8/20) | 7.01 s
+[Task 20/25]  Current/Best:   12.61/  22.45 GFLOPS | Progress: (12/20) | 18.85 s
+[Task 20/25]  Current/Best:    9.68/  22.45 GFLOPS | Progress: (16/20) | 27.79 s
+[Task 20/25]  Current/Best:    7.97/  22.45 GFLOPS | Progress: (20/20) | 36.18 s
 [Task 21/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 21/25]  Current/Best:   13.05/  18.11 GFLOPS | Progress: (4/20) | 6.18 s
-[Task 21/25]  Current/Best:    5.62/  18.95 GFLOPS | Progress: (8/20) | 13.64 s
-[Task 21/25]  Current/Best:   17.34/  19.82 GFLOPS | Progress: (12/20) | 15.89 s
-[Task 21/25]  Current/Best:   15.71/  19.82 GFLOPS | Progress: (16/20) | 17.77 s
-[Task 21/25]  Current/Best:    6.54/  19.82 GFLOPS | Progress: (20/20) | 27.56 s Done.
+[Task 21/25]  Current/Best:   10.53/  17.00 GFLOPS | Progress: (4/20) | 6.91 s Done.
+ Done.
 
+[Task 21/25]  Current/Best:   15.12/  19.49 GFLOPS | Progress: (8/20) | 18.03 s
+[Task 21/25]  Current/Best:    2.82/  19.49 GFLOPS | Progress: (12/20) | 29.46 s
+[Task 21/25]  Current/Best:   11.08/  19.49 GFLOPS | Progress: (16/20) | 32.55 s
+[Task 21/25]  Current/Best:   18.43/  20.81 GFLOPS | Progress: (20/20) | 34.63 s
 [Task 22/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 22/25]  Current/Best:   11.03/  19.48 GFLOPS | Progress: (4/20) | 5.16 s
-[Task 22/25]  Current/Best:    5.10/  19.48 GFLOPS | Progress: (8/20) | 7.06 s
-[Task 22/25]  Current/Best:    5.31/  19.48 GFLOPS | Progress: (12/20) | 9.10 s
-[Task 22/25]  Current/Best:   12.81/  19.48 GFLOPS | Progress: (16/20) | 12.41 s
-[Task 22/25]  Current/Best:    9.27/  19.48 GFLOPS | Progress: (20/20) | 15.12 s Done.
+[Task 22/25]  Current/Best:   11.27/  11.27 GFLOPS | Progress: (4/20) | 6.19 s
+[Task 22/25]  Current/Best:   11.39/  22.90 GFLOPS | Progress: (8/20) | 7.94 s
+[Task 22/25]  Current/Best:    6.35/  22.90 GFLOPS | Progress: (12/20) | 9.82 s
+[Task 22/25]  Current/Best:   15.11/  22.90 GFLOPS | Progress: (16/20) | 12.14 s
+[Task 22/25]  Current/Best:    6.65/  22.90 GFLOPS | Progress: (20/20) | 14.74 s Done.
 
 [Task 23/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 23/25]  Current/Best:    5.33/  22.29 GFLOPS | Progress: (4/20) | 5.04 s
-[Task 23/25]  Current/Best:    8.32/  22.29 GFLOPS | Progress: (8/20) | 9.11 s
-[Task 23/25]  Current/Best:    9.60/  22.29 GFLOPS | Progress: (12/20) | 14.89 s
-[Task 23/25]  Current/Best:   14.55/  22.37 GFLOPS | Progress: (16/20) | 18.50 s
-[Task 23/25]  Current/Best:    6.11/  22.37 GFLOPS | Progress: (20/20) | 20.98 s Done.
+[Task 23/25]  Current/Best:   13.08/  20.07 GFLOPS | Progress: (4/20) | 5.96 s
+[Task 23/25]  Current/Best:   10.19/  21.42 GFLOPS | Progress: (8/20) | 8.83 s
+[Task 23/25]  Current/Best:   14.87/  21.42 GFLOPS | Progress: (12/20) | 11.56 s
+[Task 23/25]  Current/Best:   20.64/  21.42 GFLOPS | Progress: (16/20) | 13.64 s
+[Task 23/25]  Current/Best:    6.39/  21.42 GFLOPS | Progress: (20/20) | 18.70 s Done.
 
 [Task 24/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 24/25]  Current/Best:    5.74/   5.74 GFLOPS | Progress: (4/20) | 13.65 s
-[Task 24/25]  Current/Best:    5.20/   5.74 GFLOPS | Progress: (8/20) | 18.61 s
-[Task 24/25]  Current/Best:    2.20/   5.74 GFLOPS | Progress: (12/20) | 29.65 s
-[Task 24/25]  Current/Best:    7.97/   7.97 GFLOPS | Progress: (16/20) | 41.81 s
-[Task 24/25]  Current/Best:    0.62/   9.37 GFLOPS | Progress: (20/20) | 46.67 s
+[Task 24/25]  Current/Best:    7.12/   7.12 GFLOPS | Progress: (4/20) | 13.52 s
+[Task 24/25]  Current/Best:    4.41/  10.60 GFLOPS | Progress: (8/20) | 24.48 s
+[Task 24/25]  Current/Best:    4.54/  10.71 GFLOPS | Progress: (12/20) | 27.69 s
+[Task 24/25]  Current/Best:    6.25/  10.71 GFLOPS | Progress: (16/20) | 34.57 s
+[Task 24/25]  Current/Best:    5.23/  10.71 GFLOPS | Progress: (20/20) | 45.58 s
 [Task 25/25]  Current/Best:    0.00/   0.00 GFLOPS | Progress: (0/20) | 0.00 s
-[Task 25/25]  Current/Best:    1.54/   5.74 GFLOPS | Progress: (4/20) | 5.90 s
-[Task 25/25]  Current/Best:    5.92/   7.92 GFLOPS | Progress: (8/20) | 7.28 s Done.
- Done.
-
-[Task 25/25]  Current/Best:    1.55/   7.92 GFLOPS | Progress: (12/20) | 18.26 s
-[Task 25/25]  Current/Best:    9.20/   9.26 GFLOPS | Progress: (16/20) | 20.71 s
-[Task 25/25]  Current/Best:    1.55/   9.26 GFLOPS | Progress: (20/20) | 24.22 s
+[Task 25/25]  Current/Best:    8.52/   9.12 GFLOPS | Progress: (4/20) | 5.91 s
+[Task 25/25]  Current/Best:    8.60/   9.39 GFLOPS | Progress: (8/20) | 10.66 s
+[Task 25/25]  Current/Best:    7.43/   9.39 GFLOPS | Progress: (12/20) | 14.67 s
+[Task 25/25]  Current/Best:    8.41/   9.39 GFLOPS | Progress: (16/20) | 15.98 s
+[Task 25/25]  Current/Best:    6.54/   9.39 GFLOPS | Progress: (20/20) | 26.92 s
 </pre></div>
 </div>
 <p>The output from this tuning process will look something like this:</p>
@@ -987,6 +985,7 @@ model using optimized operators to speed up our computations.</p>
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Done.
+Done.
 </pre></div>
 </div>
 <p>Verify that the optimized model runs and produces the same results:</p>
@@ -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;: 417.7346471299825, &#39;median&#39;: 417.1831609999572, &#39;std&#39;: 2.554834312181736}
-unoptimized: {&#39;mean&#39;: 493.17011977997026, &#39;median&#39;: 493.14711975002865, &#39;std&#39;: 2.4254435877078127}
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>optimized: {&#39;mean&#39;: 378.17025628999545, &#39;median&#39;: 377.43049289997543, &#39;std&#39;: 2.9727689047893278}
+unoptimized: {&#39;mean&#39;: 465.3329487299925, &#39;median&#39;: 465.1625409499957, &#39;std&#39;: 1.8629931775089623}
 </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  36.375 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 12 minutes  53.637 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 2bb7ca8723..78a3270d7e 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>1.193e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.179e-07 secs/op
 </pre></div>
 </div>
 </div>
diff --git a/docs/tutorial/intro_topi.html b/docs/tutorial/intro_topi.html
index 3f6136cd7e..09ccc6a1e8 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, 0x10d6a5d0)), stage(b, placeholder(b, 0x76ebd20)), 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, attrs [...]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[stage(a, placeholder(a, 0x20716040)), stage(b, placeholder(b, 0x6a94060)), 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, attrs [...]
 </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 faa30a5005..cdf37c0229 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>17:06.184</strong> total execution time for <strong>tutorial</strong> files:</p>
+<p><strong>16:11.831</strong> total execution time for <strong>tutorial</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 83%" />
@@ -369,35 +369,35 @@
 </colgroup>
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="autotvm_relay_x86.html#sphx-glr-tutorial-autotvm-relay-x86-py"><span class="std std-ref">Compiling and Optimizing a Model with the Python Interface (AutoTVM)</span></a> (<code class="docutils literal notranslate"><span class="pre">autotvm_relay_x86.py</span></code>)</p></td>
-<td><p>13:36.375</p></td>
+<td><p>12:53.637</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>01:17.720</p></td>
+<td><p>01:19.540</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>01:01.435</p></td>
+<td><p>00:58.069</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>00:42.828</p></td>
+<td><p>00:40.390</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>00:25.773</p></td>
+<td><p>00:18.213</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>00:00.960</p></td>
+<td><p>00:00.927</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>00:00.879</p></td>
+<td><p>00:00.858</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="cross_compilation_and_rpc.html#sphx-glr-tutorial-cross-compilation-and-rpc-py"><span class="std std-ref">Cross Compilation and RPC</span></a> (<code class="docutils literal notranslate"><span class="pre">cross_compilation_and_rpc.py</span></code>)</p></td>
-<td><p>00:00.213</p></td>
+<td><p>00:00.197</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="uma.html#sphx-glr-tutorial-uma-py"><span class="std std-ref">Making your Hardware Accelerator TVM-ready with UMA</span></a> (<code class="docutils literal notranslate"><span class="pre">uma.py</span></code>)</p></td>
diff --git a/docs/tutorial/tensor_expr_get_started.html b/docs/tutorial/tensor_expr_get_started.html
index 8826f33854..c4190a7dbf 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: 0.000007
-naive: 0.000009
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.000005
+naive: 0.000006
 </pre></div>
 </div>
 </div>
@@ -625,7 +625,7 @@ compile and run this new schedule with the parallel operation applied:</p>
 <span class="n">evaluate_addition</span><span class="p">(</span><span class="n">fadd_parallel</span><span class="p">,</span> <a href="../reference/api/python/target.html#tvm.target.Target" title="tvm.target.Target" class="sphx-glr-backref-module-tvm-target sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">tgt</span></a><span class="p">,</span> <span class="s2">&quot;parallel&quot;</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.h [...]
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallel: 0.000009
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallel: 0.000006
 </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: 0.000075
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector: 0.000038
 # 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    7.150609999371227e-06                    1.0
-   naive              9.1824e-06      1.2841421921776512
-parallel               9.496e-06      1.3279985904468306
-  vector             7.54449e-05       10.55083412556888
+   numpy    5.158529993423144e-06                    1.0
+   naive              5.6415e-06      1.0936255109871644
+parallel              5.8989e-06         1.1435234470907
+  vector             3.78183e-05       7.331216460545223
 </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: 0.018709
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.013781
 </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: 3.458739
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>none: 3.353773
 </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: 0.314947
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>blocking: 0.291754
 </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: 0.304500
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vectorization: 0.269348
 # 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: 0.119262
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>loop permutation: 0.108778
 # 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: 0.105823
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array packing: 0.100840
 # 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: 0.111097
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>block caching: 0.093250
 # 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: 0.131945
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>parallelization: 0.110687
 # 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            3.4587386069                     1.0
-        blocking            0.3149468401     0.09105829491471192
-   vectorization            0.3044997029     0.08803778993085493
-loop permutation     0.11926241010000001     0.03448147537431069
-   array packing     0.10582288200000001    0.030595802119561442
-   block caching             0.111097063      0.0321206878075051
- parallelization     0.13194542530000003     0.03814842354284186
+            none      3.3537726155999996                     1.0
+        blocking            0.2917537164     0.08699269444890628
+   vectorization             0.269347742     0.08031186752111187
+loop permutation            0.1087780548     0.03243453485606665
+   array packing            0.1008404337    0.030067761073288908
+   block caching     0.09325043250000001    0.027804637698527226
+ parallelization     0.11068721919999999     0.03300379360399713
 </pre></div>
 </div>
 <p>Note that the outputs on the web page reflect the running times on a
@@ -1507,7 +1507,6 @@ is</p>
 you can build generic templates of the matrix multiplication and other
 operations with tunable parameters that allows you to automatically optimize
 the computation for specific platforms.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  1.435 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>