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Posted to commits@tvm.apache.org by tq...@apache.org on 2024/02/13 22:52:48 UTC
(tvm-site) branch asf-site updated: deploying docs (apache/tvm@3c5ee30630760b3e42202e622517a92c18f11889)
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 a0bd6428ea deploying docs (apache/tvm@3c5ee30630760b3e42202e622517a92c18f11889)
a0bd6428ea is described below
commit a0bd6428eafbd51ae573e951c27c225e5335da09
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Tue Feb 13 22:52:41 2024 +0000
deploying docs (apache/tvm@3c5ee30630760b3e42202e622517a92c18f11889)
---
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.../tutorials/frontend/deploy_classification.html | 3 +-
.../vta/tutorials/frontend/deploy_detection.html | 3 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 6 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 8 +-
docs/tutorial/autotvm_matmul_x86.html | 20 +-
docs/tutorial/autotvm_relay_x86.html | 268 ++--
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/sg_execution_times.html | 22 +-
docs/tutorial/tensor_expr_get_started.html | 44 +-
359 files changed, 13089 insertions(+), 13001 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 99c06af049..bd364fa652 100644
--- a/docs/_sources/how_to/compile_models/from_darknet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
@@ -318,7 +318,7 @@ The process is no different from other examples.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 37.289 seconds)
+ **Total running time of the script:** ( 1 minutes 34.407 seconds)
.. _sphx_glr_download_how_to_compile_models_from_darknet.py:
diff --git a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
index 709da75fa6..685ce3d241 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -122,7 +122,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipa9062fd2-e64e-4181-915c-8c8ee08d64c1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip26038214-edea-49df-a3f0-61027438943c from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
diff --git a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
index 3e60b659be..85f629f20a 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -121,7 +121,7 @@ Load a pretrained OneFlow model and save model
.. code-block:: none
Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
- 0%| | 0.00/41.5M [00:00<?, ?B/s] 15%|#5 | 6.33M/41.5M [00:00<00:00, 39.9MB/s] 24%|##4 | 10.1M/41.5M [00:00<00:00, 35.4MB/s] 35%|###4 | 14.3M/41.5M [00:00<00:01, 27.3MB/s] 41%|####1 | 17.0M/41.5M [00:00<00:01, 25.2MB/s] 54%|#####3 | 22.3M/41.5M [00:00<00:00, 30.7MB/s] 61%|######1 | 25.4M/41.5M [00:00<00:00, 28.0MB/s] 77%|#######7 | 32.0M/41.5M [00:01<00:00, 36.3MB/s] 89%|########8 | 36.9M/41.5M [00:01<00:00, 40.0MB/s] 98%|#########8| 40.9M/41.5M [00:01<00:00, 40.3MB/s] 100%|##########| 41.5M/41.5M [00:01<00:00, 35.1MB/s]
+ 0%| | 0.00/41.5M [00:00<?, ?B/s] 15%|#5 | 6.33M/41.5M [00:00<00:00, 56.5MB/s] 28%|##8 | 11.7M/41.5M [00:00<00:00, 50.0MB/s] 40%|###9 | 16.5M/41.5M [00:00<00:01, 24.7MB/s] 51%|#####1 | 21.2M/41.5M [00:00<00:00, 30.1MB/s] 60%|###### | 25.0M/41.5M [00:00<00:00, 22.1MB/s] 77%|#######7 | 32.0M/41.5M [00:01<00:00, 29.4MB/s] 92%|#########2| 38.3M/41.5M [00:01<00:00, 33.0MB/s] 100%|##########| 41.5M/41.5M [00:01<00:00, 32.1MB/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 7a9a1c28fe..1f6030ef7a 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -209,7 +209,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 4.282 seconds)
+ **Total running time of the script:** ( 1 minutes 0.271 seconds)
.. _sphx_glr_download_how_to_compile_models_from_paddle.py:
diff --git a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
index c4541f2fcd..9043d8b9f7 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] 14%|#4 | 6.34M/44.7M [00:00<00:00, 66.4MB/s] 28%|##8 | 12.7M/44.7M [00:00<00:00, 47.0MB/s] 39%|###9 | 17.5M/44.7M [00:00<00:00, 35.2MB/s] 54%|#####3 | 24.0M/44.7M [00:00<00:00, 43.5MB/s] 68%|######7 | 30.3M/44.7M [00:00<00:00, 45.3MB/s] 78%|#######8 | 34.9M/44.7M [00:00<00:00, 45.7MB/s] 90%|########9 | 40.0M/44.7M [00:01<00:00, 34.9MB/s] 100%|##########| 44.7M/44.7M [00:01<00:00, 43.9MB/s]
+ 0%| | 0.00/44.7M [00:00<?, ?B/s] 14%|#4 | 6.30M/44.7M [00:00<00:00, 63.8MB/s] 28%|##7 | 12.4M/44.7M [00:00<00:00, 57.1MB/s] 40%|#### | 17.9M/44.7M [00:00<00:00, 37.6MB/s] 54%|#####3 | 24.0M/44.7M [00:00<00:00, 41.3MB/s] 63%|######3 | 28.3M/44.7M [00:00<00:00, 38.7MB/s] 72%|#######2 | 32.2M/44.7M [00:00<00:00, 34.3MB/s] 90%|########9 | 40.0M/44.7M [00:01<00:00, 37.5MB/s] 100%|##########| 44.7M/44.7M [00:01<00:00, 42.8MB/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 0f954169a2..2f22c621dd 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 33.896 seconds)
+ **Total running time of the script:** ( 1 minutes 30.118 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 8f0558d209..586939d7aa 100644
--- a/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/compile_models/sg_execution_times.rst.txt
@@ -5,26 +5,26 @@
Computation times
=================
-**07:27.248** total execution time for **how_to_compile_models** files:
+**07:08.640** total execution time for **how_to_compile_models** files:
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:37.289 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:34.407 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:33.896 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:30.118 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:04.282 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:00.271 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:43.999 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:42.149 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:39.303 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:37.456 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:35.262 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:34.386 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:29.434 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:28.001 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:28.442 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:26.742 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:12.369 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:12.283 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.970 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.829 | 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 2c451de650..13f0587322 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)
- 4122.0436 4121.8198 4126.1778 4118.5481 2.0636
+ 4118.3687 4118.5281 4121.2484 4115.9894 1.6007
@@ -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 20.516 seconds)
+ **Total running time of the script:** ( 1 minutes 18.900 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 5b3a448162..2a3a5480f1 100644
--- a/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_model_on_adreno_tvmc.rst.txt
@@ -127,7 +127,7 @@ Make a Keras Resnet50 Model
.. code-block:: none
Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels.h5
- 8192/102967424 [..............................] - ETA: 0s 6635520/102967424 [>.............................] - ETA: 0s 8380416/102967424 [=>............................] - ETA: 1s 15024128/102967424 [===>..........................] - ETA: 1s 16769024/102967424 [===>..........................] - ETA: 1s 23412736/102967424 [=====>........................] - ETA: 1s 25157632/102967424 [======>.......................] - ETA: 1s 33546240/102967424 [========>.....................] - ETA: 1s
40189952/102967424 [==========>...................] - ETA: 1s 41934848/102967424 [===========>..................] - ETA: 1s 49897472/102967424 [=============>................] - ETA: 0s 50323456/102967424 [=============>................] - ETA: 1s 56967168/102967424 [===============>..............] - ETA: 0s 58712064/102967424 [================>.............] - ETA: 0s 65355776/102967424 [==================>...........] - ETA: 0s 67100672/102967424 [==================>...........] -
ETA: 0s 69296128/102967424 [===================>..........] - ETA: 0s 75489280/102967424 [====================>.........] - ETA: 0s 83394560/102967424 [=======================>......] - ETA: 0s 83877888/102967424 [=======================>......] - ETA: 0s 90521600/102967424 [=========================>....] - ETA: 0s 92266496/102967424 [=========================>....] - ETA: 0s 98910208/102967424 [===========================>..] - ETA: 0s 100646912/102967424
[============================>.] - ETA: 0s 102850560/102967424 [============================>.] - ETA: 0s 102967424/102967424 [==============================] - 2s 0us/step
+ 8192/102967424 [..............................] - ETA: 0s 458752/102967424 [..............................] - ETA: 11s 6635520/102967424 [>.............................] - ETA: 2s 13312000/102967424 [==>...........................] - ETA: 1s 17948672/102967424 [====>.........................] - ETA: 1s 25157632/102967424 [======>.......................] - ETA: 0s 29827072/102967424 [=======>......................] - ETA: 0s 30621696/102967424 [=======>......................] - ETA: 0s
33685504/102967424 [========>.....................] - ETA: 1s 40189952/102967424 [==========>...................] - ETA: 0s 42311680/102967424 [===========>..................] - ETA: 0s 49192960/102967424 [=============>................] - ETA: 0s 58712064/102967424 [================>.............] - ETA: 0s 64151552/102967424 [=================>............] - ETA: 0s 69296128/102967424 [===================>..........] - ETA: 0s 75489280/102967424 [====================>.........
] - ETA: 0s 83877888/102967424 [=======================>......] - ETA: 0s 92266496/102967424 [=========================>....] - ETA: 0s 100646912/102967424 [============================>.] - ETA: 0s 102967424/102967424 [==============================] - 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 8d126ca9e5..f75bbca40f 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)
- 15.4306 15.3590 16.2163 14.8317 0.4306
+ 14.8581 14.8115 15.3361 14.6018 0.1976
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 3818881a08..6ded027131 100644
--- a/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_object_detection_pytorch.rst.txt
@@ -130,7 +130,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=MaskRCNN_ResNet50_FPN_Weights.COCO_V1`. You can also use `weights=MaskRCNN_ResNet50_FPN_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
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] 71%|####### | 120M/170M [00:02<00:00, 56.3MB/s] 74%|#######4 | 126M/170M [00:02<00:00, 55.6MB/s] 78%|#######7 | 132M/170M [00:02<00:00, 54.2MB/s] 81%|######## | 137M/170M [00:03<00:01, 31.9MB/s] 85%|########4 | 144M/170M [00:03<00:00, 34.8MB/s] 88%|########8 | 150M/170M [00:03<00:00, 38.1MB/s] 93%|#########3| 158M/170M [00:03<00:00, 41.0MB/s] 96%|#########5| 163M/170M [00:03<00:00, 39.4MB/s] 99%|#########8| 168M/170M [00:03<00:00, 38.6MB/s] 100%|##########| 170M/170M [00:03<00:00, 44.8MB/s]
+ 0%| | 0.00/170M [00:00<?, ?B/s] 4%|3 | 6.30M/170M [00:00<00:04, 41.5MB/s] 6%|6 | 10.3M/170M [00:00<00:06, 26.9MB/s] 9%|9 | 16.0M/170M [00:00<00:04, 32.6MB/s] 13%|#3 | 22.3M/170M [00:00<00:03, 40.9MB/s] 16%|#5 | 26.6M/170M [00:00<00:03, 38.2MB/s] 18%|#7 | 30.5M/170M [00:00<00:04, 33.1MB/s] 20%|#9 | 33.8M/170M [00:01<00:05, 27.5MB/s] 24%|##3 | 40.0M/170M [00:01<00:03, 35.3MB/s] 28%|##8 | 48.0M/170M [00:01<00:03, 39.0MB/s] 33%|###2 | 56.0M/170M [00:01<00:02, 46.5MB/s] 37%|###6 | 62.3M/170M [00:01<00:02, 39.6MB/s] 39%|###9 | 66.4M/170M [00:01<00:02, 38.3MB/s] 42%|####2 | 72.0M/170M [00:02<00:02, 39.8MB/s] 47%|####7 | 80.0M/170M [00:02<00:02, 44.4MB/s] 52%|#####1 | 88.0M/170M [00:02<00:02, 41.8MB/s] 56%|#####5 | 94.3M/170M [00:02<00:02, 36.3MB/s] 58%|#####7 | 98.0M/170M [00:02<00:02, 28.9MB/
s] 60%|###### | 102M/170M [00:03<00:02, 27.6MB/s] 62%|######1 | 105M/170M [00:03<00:03, 22.6MB/s] 66%|######5 | 112M/170M [00:03<00:02, 29.6MB/s] 71%|####### | 120M/170M [00:03<00:01, 39.5MB/s] 74%|#######4 | 126M/170M [00:03<00:01, 35.4MB/s] 77%|#######6 | 130M/170M [00:03<00:01, 34.9MB/s] 80%|#######9 | 136M/170M [00:03<00:00, 39.5MB/s] 83%|########2 | 140M/170M [00:04<00:00, 39.4MB/s] 85%|########4 | 144M/170M [00:04<00:00, 38.5MB/s] 88%|########8 | 150M/170M [00:04<00:00, 38.3MB/s] 91%|######### | 154M/170M [00:04<00:00, 37.0MB/s] 94%|#########4| 160M/170M [00:04<00:00, 36.3MB/s] 98%|#########7| 166M/170M [00:05<00:00, 27.4MB/s] 100%|##########| 170M/170M [00:05<00:00, 34.7MB/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 42.993 seconds)
+ **Total running time of the script:** ( 3 minutes 31.957 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 c21c98b575..abb67ed89c 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -227,7 +227,7 @@ training. Other models require a full post training calibration.
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=MobileNet_V2_Weights.IMAGENET1K_V1`. You can also use `weights=MobileNet_V2_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
- 0%| | 0.00/13.6M [00:00<?, ?B/s] 59%|#####8 | 7.99M/13.6M [00:00<00:00, 49.7MB/s] 100%|##########| 13.6M/13.6M [00:00<00:00, 57.8MB/s]
+ 0%| | 0.00/13.6M [00:00<?, ?B/s] 47%|####6 | 6.30M/13.6M [00:00<00:00, 38.0MB/s] 73%|#######3 | 9.94M/13.6M [00:00<00:00, 29.3MB/s] 94%|#########3| 12.7M/13.6M [00:00<00:00, 27.8MB/s] 100%|##########| 13.6M/13.6M [00:00<00:00, 31.0MB/s]
@@ -409,7 +409,7 @@ Here we give an example of how to measure performance of TVM compiled models.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 89.0513 88.9712 90.9339 88.6984 0.3292
+ 88.9296 88.8443 92.6071 88.4699 0.4610
@@ -457,7 +457,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 30.964 seconds)
+ **Total running time of the script:** ( 1 minutes 27.193 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 28455c6336..af319535f1 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)
- 111.4260 111.3542 113.3218 110.6454 0.4494
+ 108.9672 108.6613 115.6633 107.3984 1.2400
diff --git a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
index 7f2e5aa88c..18249ac613 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -263,7 +263,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 7.828 seconds)
+ **Total running time of the script:** ( 2 minutes 16.574 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_quantized.py:
diff --git a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
index dedd459f46..74967ae3b7 100644
--- a/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/deploy_models/sg_execution_times.rst.txt
@@ -5,26 +5,26 @@
Computation times
=================
-**12:18.499** total execution time for **how_to_deploy_models** files:
+**12:01.721** 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``) | 03:42.993 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:31.957 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 02:07.828 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 02:16.574 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:30.964 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:27.193 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 01:20.516 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno.py` (``deploy_model_on_adreno.py``) | 01:18.900 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 00:53.289 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 00:51.254 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:52.057 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:49.931 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``) | 00:48.574 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_adreno_tvmc.py` (``deploy_model_on_adreno_tvmc.py``) | 00:45.610 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:31.415 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_nano.py` (``deploy_model_on_nano.py``) | 00:30.289 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:30.856 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:30.006 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.007 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
index 83a2341b84..6b083fb176 100644
--- a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
@@ -469,7 +469,7 @@ First let us define two helper functions to get the mobilenet model and a cat im
.. code-block:: none
- Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip6ee3b7ce-d372-42c1-8095-40002972f8a9 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip4e2bb27b-1d34-4100-bd7d-258a4ee40519 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
diff --git a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
index 5f274f43fe..57c256e6db 100644
--- a/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
Computation times
=================
-**00:59.989** total execution time for **how_to_extend_tvm** files:
+**00:57.202** total execution time for **how_to_extend_tvm** files:
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:55.898 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:53.204 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.872 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.793 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.211 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:01.197 | 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 87bb564d93..eb90b03a45 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: 25280us [25280us] (48.39%; 48.39%)
- FoldScaleAxis: 26967us [9us] (51.61%; 51.61%)
- FoldConstant: 26958us [1829us] (51.60%; 99.97%)
- InferType: 25129us [25129us] (48.10%; 93.21%)
+ InferType: 25596us [25596us] (49.18%; 49.18%)
+ FoldScaleAxis: 26448us [7us] (50.82%; 50.82%)
+ FoldConstant: 26441us [1816us] (50.80%; 99.97%)
+ InferType: 24625us [24625us] (47.32%; 93.13%)
@@ -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: 25185us [25185us] (48.02%; 48.02%)
- FoldScaleAxis: 27266us [9us] (51.98%; 51.98%)
- FoldConstant: 27257us [2024us] (51.97%; 99.97%)
- InferType: 25233us [25233us] (48.11%; 92.57%)
+ InferType: 24514us [24514us] (48.48%; 48.48%)
+ FoldScaleAxis: 26048us [7us] (51.52%; 51.52%)
+ FoldConstant: 26042us [1774us] (51.50%; 99.97%)
+ InferType: 24268us [24268us] (48.00%; 93.19%)
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 f4702ee570..e1ca027d59 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: 43.692832 ms
+ Convolution: 36.099391 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 512eb67a2c..2c35069836 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: 12.266087 ms
+ conv2d with tensor core: 12.267693 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 5d9e226a12..6e0cbd7944 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: 0.019720
- Baseline: 3.505645
+ Numpy running time: 0.018058
+ Baseline: 3.527402
@@ -227,7 +227,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.296518
+ Opt1: 0.296422
@@ -318,7 +318,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.284328
+ Opt2: 0.272153
@@ -406,7 +406,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.116417
+ Opt3: 0.114605
@@ -523,7 +523,7 @@ flattening.
.. code-block:: none
- Opt4: 0.107504
+ Opt4: 0.107752
@@ -635,7 +635,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.116506
+ Opt5: 0.111886
@@ -748,7 +748,7 @@ Furthermore, we can also utilize multi-core processors to do the thread-level pa
.. code-block:: none
- Opt6: 0.138231
+ Opt6: 0.133158
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 2d7a2c48d4..e0c3797b2a 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
=================
-**00:35.033** total execution time for **how_to_optimize_operators** files:
+**00:34.236** total execution time for **how_to_optimize_operators** files:
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:31.651 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:31.057 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:02.002 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.906 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.379 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.274 | 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 36b901bdd8..0cc1af4b20 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
=================
-**03:41.637** total execution time for **how_to_tune_with_autoscheduler** files:
+**03:34.761** total execution time for **how_to_tune_with_autoscheduler** files:
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:35.371 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:32.410 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:13.848 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 01:12.004 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:18.270 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:17.621 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:17.396 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 00:16.662 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:16.649 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:15.958 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:00.103 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:00.105 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.rst.txt
index fb06a4677d..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: 0.346 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 f20cb04fe8..f0fc208952 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
@@ -651,7 +651,7 @@ 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)
- 3.2416 3.2403 3.2458 3.2386 0.0031
+ 3.2038 3.2001 3.2121 3.1992 0.0059
@@ -678,7 +678,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 13.848 seconds)
+ **Total running time of the script:** ( 1 minutes 12.004 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 d9a090dfe5..fb39c1a6c0 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
@@ -672,7 +672,7 @@ 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)
- 766.3748 764.5378 772.7261 761.8605 4.6222
+ 755.0353 754.5271 757.6595 752.9192 1.9683
@@ -699,7 +699,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 35.371 seconds)
+ **Total running time of the script:** ( 1 minutes 32.410 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 acec146133..c5530ba332 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
=================
-**00:24.066** total execution time for **how_to_tune_with_autotvm** files:
+**00:23.665** 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``) | 00:24.029 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:23.617 | 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``) | 00:00.032 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``) | 00:00.006 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
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 8b9415ed0a..1fd3cdc1ec 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: 0.037336
+ Time cost of this operator: 0.037309
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 2e78b6d913..76eaf1fe44 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 307.2 98.721 (1, 2, 10, 10, 3) 2 1 [307.2]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.978 0.957 (1, 6, 10, 10) 1 1 [2.978]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 1.002 0.322 (1, 1, 10, 10, 3) 1 1 [1.002]
- Total_time - 311.18 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 304.8 98.717 (1, 2, 10, 10, 3) 2 1 [304.8]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.985 0.967 (1, 6, 10, 10) 1 1 [2.985]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.316 (1, 1, 10, 10, 3) 1 1 [0.976]
+ Total_time - 308.761 - - - - -
@@ -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 101.3 97.313 (1, 6, 10, 10, 1) 2 1 [101.3]
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.809 1.737 (1, 6, 10, 10) 1 1 [1.809]
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.988 0.949 (1, 1, 10, 10, 3) 1 1 [0.988]
- Total_time - 104.097 - - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 102.2 97.444 (1, 6, 10, 10, 1) 2 1 [102.2]
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.827 1.742 (1, 6, 10, 10) 1 1 [1.827]
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.853 0.813 (1, 3, 10, 10, 1) 1 1 [0.853]
+ Total_time - 104.88 - - - - -
@@ -439,7 +439,7 @@ Timing the tuned program
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 28.555 seconds)
+ **Total running time of the script:** ( 1 minutes 24.642 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 fee8b5902c..26b5118d63 100644
--- a/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/micro_pytorch.rst.txt
@@ -118,7 +118,7 @@ download a cat image and preprocess it to use as the model input.
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/ao/quantization/utils.py:310: UserWarning: must run observer before calling calculate_qparams. Returning default values.
warnings.warn(
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
- 0%| | 0.00/3.42M [00:00<?, ?B/s] 61%|###### | 2.09M/3.42M [00:00<00:00, 4.09MB/s] 100%|##########| 3.42M/3.42M [00:00<00:00, 6.62MB/s]
+ 0%| | 0.00/3.42M [00:00<?, ?B/s] 61%|###### | 2.09M/3.42M [00:00<00:00, 12.8MB/s] 100%|##########| 3.42M/3.42M [00:00<00:00, 20.5MB/s]
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/_utils.py:314: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
device=storage.device,
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -326,7 +326,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 31.132 seconds)
+ **Total running time of the script:** ( 1 minutes 28.641 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 b7fd96ed56..ea0c575ea0 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/tmph6yqhz09/images/random'
+ '/tmp/tmptx_a_q0x/images/random'
@@ -317,8 +317,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. code-block:: none
- /tmp/tmph6yqhz09/images/target contains 8144 images
- /tmp/tmph6yqhz09/images/random contains 5000 images
+ /tmp/tmptx_a_q0x/images/target contains 8144 images
+ /tmp/tmptx_a_q0x/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: 0.2721 - accuracy: 0.9157 - val_loss: 0.1259 - val_accuracy: 0.9577 - 39s/epoch - 119ms/step
+ 328/328 - 40s - loss: 0.2298 - accuracy: 0.9227 - val_loss: 0.1226 - val_accuracy: 0.9622 - 40s/epoch - 121ms/step
Epoch 2/3
- 328/328 - 36s - loss: 0.1119 - accuracy: 0.9590 - val_loss: 0.1075 - val_accuracy: 0.9634 - 36s/epoch - 109ms/step
+ 328/328 - 35s - loss: 0.1031 - accuracy: 0.9634 - val_loss: 0.0945 - val_accuracy: 0.9675 - 35s/epoch - 108ms/step
Epoch 3/3
- 328/328 - 35s - loss: 0.0739 - accuracy: 0.9719 - val_loss: 0.1007 - val_accuracy: 0.9739 - 35s/epoch - 108ms/step
+ 328/328 - 35s - loss: 0.0635 - accuracy: 0.9760 - val_loss: 0.1514 - val_accuracy: 0.9475 - 35s/epoch - 107ms/step
- <keras.callbacks.History object at 0x7f46aa3b7160>
+ <keras.callbacks.History object at 0x7f5d2956fe80>
@@ -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 44.721 seconds)
+ **Total running time of the script:** ( 4 minutes 45.827 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 ab4a50c029..60038f328f 100644
--- a/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_microtvm/sg_execution_times.rst.txt
@@ -5,20 +5,20 @@
Computation times
=================
-**08:13.809** total execution time for **how_to_work_with_microtvm** files:
+**08:07.891** total execution time for **how_to_work_with_microtvm** files:
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:44.721 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:45.827 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:31.132 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_pytorch.py` (``micro_pytorch.py``) | 01:28.641 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 01:28.555 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 01:24.642 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:12.254 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_aot.py` (``micro_aot.py``) | 00:12.045 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:09.267 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_custom_ide.py` (``micro_custom_ide.py``) | 00:08.817 | 0.0 MB |
+-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:07.880 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:07.920 | 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 814336122f..e5e43e60fe 100644
--- a/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/work_with_relay/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
Computation times
=================
-**00:39.448** total execution time for **how_to_work_with_relay** files:
+**00:38.622** 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``) | 00:34.106 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_pipeline_executor.py` (``using_pipeline_executor.py``) | 00:33.345 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:03.238 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:03.138 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:02.098 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:02.132 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``) | 00:00.006 | 0.0 MB |
+----------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt b/docs/_sources/how_to/work_with_schedules/intrin_math.rst.txt
index b49bde44ee..8d63f9c04f 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 0x7f46ae046280>
+ <function my_cuda_math_rule at 0x7f5d2ccdb310>
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 1bc6f87dd0..49b20a70c7 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
=================
-**00:05.582** total execution time for **how_to_work_with_schedules** files:
+**00:05.774** total execution time for **how_to_work_with_schedules** files:
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:02.655 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:02.663 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.142 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:01.336 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.753 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.748 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.747 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.746 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.118 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.115 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.070 | 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_tedd.py` (``tedd.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_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.031 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
index 343d81f7eb..2d14e14cd2 100644
--- a/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/autotvm/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**00:36.329** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:34.960** total execution time for **topic_vta_tutorials_autotvm** files:
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:36.321 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:34.952 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``) | 00:00.008 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
index 7ac592c1cd..00f2f8a083 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -298,7 +298,7 @@ The compilation steps are:
warnings.warn(
/workspace/vta/tutorials/frontend/deploy_classification.py:217: DeprecationWarning: legacy graph executor behavior of producing json / lib / params will be removed in the next release. Please see documents of tvm.contrib.graph_executor.GraphModule for the new recommended usage.
graph, lib, params = relay.build(
- resnet18_v1 inference graph built in 39.16s!
+ resnet18_v1 inference graph built in 37.45s!
@@ -419,11 +419,6 @@ and an input test image.
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 0.223 seconds)
-
-
.. _sphx_glr_download_topic_vta_tutorials_frontend_deploy_classification.py:
.. only:: html
diff --git a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
index 75a7d5f3dd..01d94729de 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -337,7 +337,7 @@ The compilation steps are:
/workspace/python/tvm/relay/build_module.py:345: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
warnings.warn(
- yolov3-tiny inference graph built in 26.60s!
+ yolov3-tiny inference graph built in 25.24s!
@@ -445,11 +445,6 @@ Download test image
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 0.394 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 42032ade52..536e0ff1db 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**02:00.617** total execution time for **topic_vta_tutorials_frontend** files:
+**01:56.994** total execution time for **topic_vta_tutorials_frontend** files:
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 01:00.394 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:58.630 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 01:00.223 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:58.364 | 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 672f652143..b5d65408cc 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
=================
-**00:03.389** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.341** total execution time for **topic_vta_tutorials_optimize** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.850 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.802 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.539 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.538 | 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 2f26b0731a..98b78f7224 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
=================
-**00:00.901** total execution time for **topic_vta_tutorials** files:
+**00:00.877** total execution time for **topic_vta_tutorials** files:
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.464 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.448 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.437 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.428 | 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 4feb1d46ba..ffb2fd89e2 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -207,13 +207,6 @@ trials, we can load the best schedule from the log file and apply it.
-.. rst-class:: sphx-glr-script-out
-
- .. code-block:: none
-
- .T*E
-
-
@@ -325,7 +318,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 95.791 ms
+ Execution time of this operator: 96.241 ms
@@ -423,7 +416,7 @@ resume the status and do more 5 trials.
.. code-block:: none
Resume search:
- *E
+
@@ -441,7 +434,7 @@ operations.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 56.580 seconds)
+ **Total running time of the script:** ( 1 minutes 20.458 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 1158806004..3816c4050e 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: 0.50/0.50 result: MeasureResult(costs=(0.5415342676,), error_no=MeasureErrorNo.NO_ERROR, all_cost=8.900280952453613, timestamp=1707842379.9796524) [('tile_y', [-1, 32]), ('tile_x', [-1, 1])],None,5
- No: 2 GFLOPS: 11.01/11.01 result: MeasureResult(costs=(0.0243768612,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7153768539428711, timestamp=1707842380.6417263) [('tile_y', [-1, 128]), ('tile_x', [-1, 256])],None,87
- No: 3 GFLOPS: 11.32/11.32 result: MeasureResult(costs=(0.0237200704,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6539103984832764, timestamp=1707842381.2892015) [('tile_y', [-1, 128]), ('tile_x', [-1, 512])],None,97
- No: 4 GFLOPS: 7.05/11.32 result: MeasureResult(costs=(0.03809675,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8840732574462891, timestamp=1707842382.180941) [('tile_y', [-1, 512]), ('tile_x', [-1, 256])],None,89
- No: 5 GFLOPS: 9.66/11.32 result: MeasureResult(costs=(0.027787566399999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7509024143218994, timestamp=1707842383.0495658) [('tile_y', [-1, 4]), ('tile_x', [-1, 128])],None,72
- No: 6 GFLOPS: 0.98/11.32 result: MeasureResult(costs=(0.2738819286,), error_no=MeasureErrorNo.NO_ERROR, all_cost=4.653416395187378, timestamp=1707842387.699404) [('tile_y', [-1, 256]), ('tile_x', [-1, 2])],None,18
- No: 7 GFLOPS: 8.47/11.32 result: MeasureResult(costs=(0.031708317,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7796268463134766, timestamp=1707842388.4728563) [('tile_y', [-1, 8]), ('tile_x', [-1, 8])],None,33
- No: 8 GFLOPS: 3.04/11.32 result: MeasureResult(costs=(0.0883820042,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.677720308303833, timestamp=1707842390.151096) [('tile_y', [-1, 4]), ('tile_x', [-1, 2])],None,12
- No: 9 GFLOPS: 0.86/11.32 result: MeasureResult(costs=(0.3135914256,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.266503810882568, timestamp=1707842395.5392048) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
- No: 10 GFLOPS: 8.81/11.32 result: MeasureResult(costs=(0.030476074399999997,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.7307851314544678, timestamp=1707842396.2956712) [('tile_y', [-1, 128]), ('tile_x', [-1, 16])],None,47
+ No: 1 GFLOPS: 10.03/10.03 result: MeasureResult(costs=(0.0267658634,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6827800273895264, timestamp=1707862008.1295912) [('tile_y', [-1, 1]), ('tile_x', [-1, 512])],None,90
+ No: 2 GFLOPS: 10.46/10.46 result: MeasureResult(costs=(0.0256690174,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6972086429595947, timestamp=1707862008.7933965) [('tile_y', [-1, 8]), ('tile_x', [-1, 32])],None,53
+ No: 3 GFLOPS: 11.68/11.68 result: MeasureResult(costs=(0.0229763756,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.651644229888916, timestamp=1707862009.4195952) [('tile_y', [-1, 64]), ('tile_x', [-1, 512])],None,96
+ No: 4 GFLOPS: 13.57/13.57 result: MeasureResult(costs=(0.0197778346,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5804543495178223, timestamp=1707862009.9930716) [('tile_y', [-1, 16]), ('tile_x', [-1, 128])],None,74
+ No: 5 GFLOPS: 3.66/13.57 result: MeasureResult(costs=(0.07336765799999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.435431718826294, timestamp=1707862011.5584044) [('tile_y', [-1, 128]), ('tile_x', [-1, 8])],None,37
+ No: 6 GFLOPS: 1.95/13.57 result: MeasureResult(costs=(0.137691141,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4519200325012207, timestamp=1707862014.01836) [('tile_y', [-1, 8]), ('tile_x', [-1, 1])],None,3
+ No: 7 GFLOPS: 7.80/13.57 result: MeasureResult(costs=(0.034402408,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.8006339073181152, timestamp=1707862014.8229809) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
+ No: 8 GFLOPS: 11.64/13.57 result: MeasureResult(costs=(0.0230559738,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6515002250671387, timestamp=1707862015.4520254) [('tile_y', [-1, 8]), ('tile_x', [-1, 256])],None,83
+ No: 9 GFLOPS: 1.44/13.57 result: MeasureResult(costs=(0.18675270780000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=3.1986024379730225, timestamp=1707862018.7707002) [('tile_y', [-1, 1]), ('tile_x', [-1, 1])],None,0
+ No: 10 GFLOPS: 10.97/13.57 result: MeasureResult(costs=(0.024461741000000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.6106967926025391, timestamp=1707862019.4188282) [('tile_y', [-1, 2]), ('tile_x', [-1, 32])],None,51
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index b73d55665b..343f3202e0 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': 503.0455810299827, 'median': 503.0315536001581, 'std': 3.3010465330462697}
+ {'mean': 494.2683718200715, 'median': 493.55235119983263, 'std': 3.9869056543511348}
@@ -582,31 +582,31 @@ the tuning data to.
.. code-block:: none
- [Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 1/25] Current/Best: 11.32/ 12.79 GFLOPS | Progress: (4/20) | 9.26 s [Task 1/25] Current/Best: 12.92/ 16.26 GFLOPS | Progress: (8/20) | 12.75 s [Task 1/25] Current/Best: 10.90/ 16.26 GFLOPS | Progress: (12/20) | 17.16 s [Task 1/25] Current/Best: 12.38/ 16.26 GFLOPS | Progress: (16/20) | 21.53 s [Task 1/25] Current/Best: 22.56/ 22.56 GFLOPS | Progress: (20/20) | 25.54 s Done.
- [Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 2/25] Current/Best: 10.97/ 17.48 GFLOPS | Progress: (4/20) | 4.62 s [Task 2/25] Current/Best: 13.56/ 21.01 GFLOPS | Progress: (8/20) | 6.24 s [Task 2/25] Current/Best: 18.53/ 21.01 GFLOPS | Progress: (12/20) | 7.81 s [Task 2/25] Current/Best: 16.99/ 21.01 GFLOPS | Progress: (16/20) | 9.66 s [Task 2/25] Current/Best: 11.38/ 21.01 GFLOPS | Progress: (20/20) | 11.12 s Done.
- [Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 3/25] Current/Best: 13.11/ 20.36 GFLOPS | Progress: (4/20) | 4.97 s [Task 3/25] Current/Best: 9.26/ 23.17 GFLOPS | Progress: (8/20) | 7.10 s [Task 3/25] Current/Best: 7.00/ 23.17 GFLOPS | Progress: (12/20) | 9.79 s [Task 3/25] Current/Best: 18.22/ 23.17 GFLOPS | Progress: (16/20) | 12.16 s [Task 3/25] Current/Best: 23.48/ 23.48 GFLOPS | Progress: (20/20) | 14.06 s Done.
- [Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 4/25] Current/Best: 16.49/ 16.49 GFLOPS | Progress: (4/20) | 4.69 s [Task 4/25] Current/Best: 13.52/ 20.29 GFLOPS | Progress: (8/20) | 6.78 s [Task 4/25] Current/Best: 10.99/ 20.29 GFLOPS | Progress: (12/20) | 9.00 s [Task 4/25] Current/Best: 12.45/ 20.29 GFLOPS | Progress: (16/20) | 11.95 s [Task 4/25] Current/Best: 7.44/ 20.29 GFLOPS | Progress: (20/20) | 14.83 s Done.
- [Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 5/25] Current/Best: 5.92/ 17.87 GFLOPS | Progress: (4/20) | 4.86 s [Task 5/25] Current/Best: 14.10/ 17.87 GFLOPS | Progress: (8/20) | 7.11 s [Task 5/25] Current/Best: 22.79/ 22.79 GFLOPS | Progress: (12/20) | 9.04 s [Task 5/25] Current/Best: 17.98/ 22.79 GFLOPS | Progress: (16/20) | 11.02 s [Task 5/25] Current/Best: 17.83/ 22.79 GFLOPS | Progress: (20/20) | 13.21 s Done.
- [Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 6/25] Current/Best: 16.89/ 16.89 GFLOPS | Progress: (4/20) | 5.00 s [Task 6/25] Current/Best: 17.45/ 17.45 GFLOPS | Progress: (8/20) | 7.15 s [Task 6/25] Current/Best: 9.21/ 17.45 GFLOPS | Progress: (12/20) | 9.34 s [Task 6/25] Current/Best: 14.46/ 19.82 GFLOPS | Progress: (16/20) | 11.51 s [Task 6/25] Current/Best: 13.75/ 19.82 GFLOPS | Progress: (20/20) | 14.11 s Done.
- [Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 7/25] Current/Best: 7.11/ 18.67 GFLOPS | Progress: (4/20) | 5.56 s [Task 7/25] Current/Best: 17.34/ 18.74 GFLOPS | Progress: (8/20) | 7.75 s [Task 7/25] Current/Best: 16.77/ 18.87 GFLOPS | Progress: (12/20) | 9.85 s [Task 7/25] Current/Best: 14.23/ 18.87 GFLOPS | Progress: (16/20) | 12.21 s [Task 7/25] Current/Best: 10.45/ 20.61 GFLOPS | Progress: (20/20) | 16.08 s Done.
- [Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 8/25] Current/Best: 7.60/ 12.57 GFLOPS | Progress: (4/20) | 7.57 s [Task 8/25] Current/Best: 11.85/ 13.86 GFLOPS | Progress: (8/20) | 12.39 s [Task 8/25] Current/Best: 11.61/ 15.63 GFLOPS | Progress: (12/20) | 16.13 s [Task 8/25] Current/Best: 12.31/ 15.63 GFLOPS | Progress: (16/20) | 20.14 s [Task 8/25] Current/Best: 13.45/ 15.63 GFLOPS | Progress: (20/20) | 26.35 s Done.
- [Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 9/25] Current/Best: 16.83/ 16.83 GFLOPS | Progress: (4/20) | 4.95 s [Task 9/25] Current/Best: 7.88/ 16.83 GFLOPS | Progress: (8/20) | 16.11 s [Task 9/25] Current/Best: 12.95/ 16.83 GFLOPS | Progress: (12/20) | 20.16 s [Task 9/25] Current/Best: 11.75/ 16.83 GFLOPS | Progress: (16/20) | 31.56 s [Task 9/25] Current/Best: 11.22/ 18.67 GFLOPS | Progress: (20/20) | 39.52 s [Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 10/25] Current/Best: 17.95/ 17.95 GFLOPS | Progress: (4/20) | 4.27 s [Task 10/25] Current/Best: 14.71/ 17.95 GFLOPS | Progress: (8/20) | 6.94 s [Task 10/25] Current/Best: 4.48/ 17.95 GFLOPS | Progress: (12/20) | 8.87 s [Task 10/25] Current/Best: 10.33/ 18.43 GFLOPS | Progress: (16/20) | 12.05 s [Task 10/25] Current/Best: 2.70/ 18.66 GFLOPS | Progress: (20/20
) | 13.91 s Done.
- [Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 11/25] Current/Best: 1.58/ 22.40 GFLOPS | Progress: (4/20) | 6.65 s [Task 11/25] Current/Best: 19.45/ 22.40 GFLOPS | Progress: (8/20) | 9.03 s [Task 11/25] Current/Best: 10.66/ 22.40 GFLOPS | Progress: (12/20) | 11.40 s [Task 11/25] Current/Best: 17.49/ 22.40 GFLOPS | Progress: (16/20) | 13.76 s [Task 11/25] Current/Best: 12.81/ 22.40 GFLOPS | Progress: (20/20) | 16.22 s Done.
- [Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 12/25] Current/Best: 9.84/ 21.60 GFLOPS | Progress: (4/20) | 6.06 s [Task 12/25] Current/Best: 10.95/ 21.60 GFLOPS | Progress: (8/20) | 9.65 s [Task 12/25] Current/Best: 4.98/ 21.60 GFLOPS | Progress: (12/20) | 12.71 s [Task 12/25] Current/Best: 11.72/ 21.60 GFLOPS | Progress: (16/20) | 15.01 s [Task 12/25] Current/Best: 4.44/ 21.60 GFLOPS | Progress: (20/20) | 17.41 s Done.
- [Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 13/25] Current/Best: 17.34/ 22.19 GFLOPS | Progress: (4/20) | 6.04 s [Task 13/25] Current/Best: 10.84/ 22.19 GFLOPS | Progress: (8/20) | 9.04 s [Task 13/25] Current/Best: 3.11/ 22.19 GFLOPS | Progress: (12/20) | 12.37 s [Task 13/25] Current/Best: 18.73/ 22.19 GFLOPS | Progress: (16/20) | 15.30 s [Task 13/25] Current/Best: 3.08/ 22.19 GFLOPS | Progress: (20/20) | 19.04 s Done.
- [Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 14/25] Current/Best: 8.59/ 9.31 GFLOPS | Progress: (4/20) | 12.55 s [Task 14/25] Current/Best: 18.87/ 18.87 GFLOPS | Progress: (8/20) | 16.47 s [Task 14/25] Current/Best: 9.28/ 18.87 GFLOPS | Progress: (12/20) | 20.09 s [Task 14/25] Current/Best: 4.21/ 20.22 GFLOPS | Progress: (16/20) | 23.06 s [Task 14/25] Current/Best: 14.46/ 20.22 GFLOPS | Progress: (20/20) | 25.84 s Done.
- [Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 15/25] Current/Best: 9.88/ 18.49 GFLOPS | Progress: (4/20) | 5.06 s [Task 15/25] Current/Best: 12.14/ 19.16 GFLOPS | Progress: (8/20) | 6.86 s [Task 15/25] Current/Best: 11.95/ 20.44 GFLOPS | Progress: (12/20) | 17.90 s [Task 15/25] Current/Best: 19.86/ 20.44 GFLOPS | Progress: (16/20) | 24.91 s [Task 15/25] Current/Best: 10.43/ 20.44 GFLOPS | Progress: (20/20) | 28.84 s [Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 16/25] Current/Best: 14.44/ 14.44 GFLOPS | Progress: (4/20) | 4.95 s [Task 16/25] Current/Best: 10.69/ 18.96 GFLOPS | Progress: (8/20) | 7.43 s [Task 16/25] Current/Best: 11.69/ 21.56 GFLOPS | Progress: (12/20) | 9.42 s [Task 16/25] Current/Best: 15.35/ 21.56 GFLOPS | Progress: (16/20) | 11.43 s [Task 16/25] Current/Best: 8.90/ 21.56 GFLOPS | Progress: (20/20)
| 13.89 s Done.
- [Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 17/25] Current/Best: 20.48/ 23.71 GFLOPS | Progress: (4/20) | 5.19 s [Task 17/25] Current/Best: 3.06/ 23.71 GFLOPS | Progress: (8/20) | 9.57 s [Task 17/25] Current/Best: 11.33/ 23.71 GFLOPS | Progress: (12/20) | 12.33 s [Task 17/25] Current/Best: 10.76/ 23.71 GFLOPS | Progress: (16/20) | 16.46 s Done.
+ [Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 1/25] Current/Best: 20.24/ 22.71 GFLOPS | Progress: (4/20) | 9.12 s [Task 1/25] Current/Best: 13.03/ 22.71 GFLOPS | Progress: (8/20) | 15.68 s [Task 1/25] Current/Best: 7.24/ 22.71 GFLOPS | Progress: (12/20) | 17.99 s [Task 1/25] Current/Best: 7.56/ 22.71 GFLOPS | Progress: (16/20) | 20.72 s [Task 1/25] Current/Best: 13.65/ 22.71 GFLOPS | Progress: (20/20) | 29.18 s Done.
+ [Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 2/25] Current/Best: 13.19/ 17.15 GFLOPS | Progress: (4/20) | 4.13 s [Task 2/25] Current/Best: 13.93/ 17.15 GFLOPS | Progress: (8/20) | 5.82 s [Task 2/25] Current/Best: 12.59/ 20.05 GFLOPS | Progress: (12/20) | 7.33 s [Task 2/25] Current/Best: 10.85/ 20.26 GFLOPS | Progress: (16/20) | 8.92 s [Task 2/25] Current/Best: 17.06/ 20.31 GFLOPS | Progress: (20/20) | 10.24 s Done.
+ [Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 3/25] Current/Best: 20.46/ 20.46 GFLOPS | Progress: (4/20) | 5.12 s [Task 3/25] Current/Best: 17.28/ 20.46 GFLOPS | Progress: (8/20) | 7.69 s [Task 3/25] Current/Best: 23.57/ 23.57 GFLOPS | Progress: (12/20) | 9.62 s [Task 3/25] Current/Best: 19.47/ 23.57 GFLOPS | Progress: (16/20) | 13.69 s [Task 3/25] Current/Best: 3.16/ 23.57 GFLOPS | Progress: (20/20) | 16.42 s Done.
+ [Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 4/25] Current/Best: 16.66/ 16.66 GFLOPS | Progress: (4/20) | 4.59 s [Task 4/25] Current/Best: 13.31/ 20.80 GFLOPS | Progress: (8/20) | 8.12 s [Task 4/25] Current/Best: 12.11/ 20.80 GFLOPS | Progress: (12/20) | 11.16 s [Task 4/25] Current/Best: 21.16/ 21.16 GFLOPS | Progress: (16/20) | 12.75 s [Task 4/25] Current/Best: 12.03/ 21.16 GFLOPS | Progress: (20/20) | 18.72 s Done.
+ [Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 5/25] Current/Best: 16.45/ 18.08 GFLOPS | Progress: (4/20) | 4.65 s [Task 5/25] Current/Best: 15.02/ 18.08 GFLOPS | Progress: (8/20) | 6.47 s [Task 5/25] Current/Best: 1.60/ 19.27 GFLOPS | Progress: (12/20) | 8.84 s [Task 5/25] Current/Best: 2.99/ 19.27 GFLOPS | Progress: (16/20) | 11.28 s [Task 5/25] Current/Best: 5.65/ 19.27 GFLOPS | Progress: (20/20) | 13.16 s Done.
+ [Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 6/25] Current/Best: 22.98/ 22.98 GFLOPS | Progress: (4/20) | 5.04 s [Task 6/25] Current/Best: 5.16/ 22.98 GFLOPS | Progress: (8/20) | 10.30 s [Task 6/25] Current/Best: 17.65/ 22.98 GFLOPS | Progress: (12/20) | 12.75 s [Task 6/25] Current/Best: 19.64/ 22.98 GFLOPS | Progress: (16/20) | 16.63 s [Task 6/25] Current/Best: 15.39/ 22.98 GFLOPS | Progress: (20/20) | 18.83 s Done.
+ [Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 7/25] Current/Best: 18.29/ 18.29 GFLOPS | Progress: (4/20) | 5.35 s [Task 7/25] Current/Best: 17.96/ 18.29 GFLOPS | Progress: (8/20) | 7.70 s [Task 7/25] Current/Best: 3.06/ 18.60 GFLOPS | Progress: (12/20) | 10.88 s [Task 7/25] Current/Best: 5.53/ 23.32 GFLOPS | Progress: (16/20) | 13.65 s [Task 7/25] Current/Best: 20.59/ 23.32 GFLOPS | Progress: (20/20) | 15.69 s Done.
+ [Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 8/25] Current/Best: 11.84/ 17.16 GFLOPS | Progress: (4/20) | 7.22 s [Task 8/25] Current/Best: 5.21/ 17.16 GFLOPS | Progress: (8/20) | 14.76 s [Task 8/25] Current/Best: 10.22/ 18.02 GFLOPS | Progress: (12/20) | 17.25 s [Task 8/25] Current/Best: 14.10/ 18.02 GFLOPS | Progress: (16/20) | 22.03 s [Task 8/25] Current/Best: 16.10/ 18.02 GFLOPS | Progress: (20/20) | 28.39 s Done.
+ [Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 9/25] Current/Best: 7.06/ 17.06 GFLOPS | Progress: (4/20) | 13.70 s [Task 9/25] Current/Best: 11.32/ 21.00 GFLOPS | Progress: (8/20) | 18.72 s [Task 9/25] Current/Best: 12.75/ 21.00 GFLOPS | Progress: (12/20) | 22.07 s [Task 9/25] Current/Best: 7.61/ 21.00 GFLOPS | Progress: (16/20) | 27.58 s [Task 9/25] Current/Best: 12.75/ 21.00 GFLOPS | Progress: (20/20) | 35.08 s [Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 10/25] Current/Best: 12.38/ 15.84 GFLOPS | Progress: (4/20) | 4.62 s [Task 10/25] Current/Best: 6.21/ 15.84 GFLOPS | Progress: (8/20) | 6.62 s [Task 10/25] Current/Best: 6.96/ 15.84 GFLOPS | Progress: (12/20) | 10.11 s [Task 10/25] Current/Best: 7.49/ 15.84 GFLOPS | Progress: (16/20) | 12.09 s [Task 10/25] Current/Best: 12.49/ 16.76 GFLOPS | Progress: (20/
20) | 14.63 s Done.
+ [Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 11/25] Current/Best: 12.32/ 23.21 GFLOPS | Progress: (4/20) | 4.76 s [Task 11/25] Current/Best: 11.16/ 23.21 GFLOPS | Progress: (8/20) | 8.57 s [Task 11/25] Current/Best: 20.45/ 23.21 GFLOPS | Progress: (12/20) | 11.80 s [Task 11/25] Current/Best: 9.93/ 23.21 GFLOPS | Progress: (16/20) | 13.82 s [Task 11/25] Current/Best: 19.75/ 23.21 GFLOPS | Progress: (20/20) | 16.20 s Done.
+ [Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 12/25] Current/Best: 9.59/ 15.50 GFLOPS | Progress: (4/20) | 5.69 s [Task 12/25] Current/Best: 5.83/ 15.50 GFLOPS | Progress: (8/20) | 8.57 s [Task 12/25] Current/Best: 5.08/ 18.60 GFLOPS | Progress: (12/20) | 14.71 s [Task 12/25] Current/Best: 20.50/ 20.50 GFLOPS | Progress: (16/20) | 16.60 s [Task 12/25] Current/Best: 13.43/ 20.50 GFLOPS | Progress: (20/20) | 19.08 s Done.
+ [Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 13/25] Current/Best: 19.90/ 19.90 GFLOPS | Progress: (4/20) | 6.59 s [Task 13/25] Current/Best: 18.88/ 19.90 GFLOPS | Progress: (8/20) | 10.70 s [Task 13/25] Current/Best: 8.21/ 19.90 GFLOPS | Progress: (12/20) | 15.34 s [Task 13/25] Current/Best: 18.73/ 22.17 GFLOPS | Progress: (16/20) | 17.44 s [Task 13/25] Current/Best: 12.99/ 22.17 GFLOPS | Progress: (20/20) | 19.81 s Done.
+ [Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 14/25] Current/Best: 18.21/ 18.21 GFLOPS | Progress: (4/20) | 6.10 s [Task 14/25] Current/Best: 15.86/ 18.21 GFLOPS | Progress: (8/20) | 9.81 s [Task 14/25] Current/Best: 15.80/ 18.21 GFLOPS | Progress: (12/20) | 12.22 s [Task 14/25] Current/Best: 12.78/ 18.21 GFLOPS | Progress: (16/20) | 14.80 s [Task 14/25] Current/Best: 19.30/ 19.30 GFLOPS | Progress: (20/20) | 18.83 s Done.
+ [Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 15/25] Current/Best: 14.87/ 18.42 GFLOPS | Progress: (4/20) | 4.57 s [Task 15/25] Current/Best: 9.07/ 18.42 GFLOPS | Progress: (8/20) | 8.27 s [Task 15/25] Current/Best: 12.24/ 21.58 GFLOPS | Progress: (12/20) | 17.03 s [Task 15/25] Current/Best: 10.12/ 21.58 GFLOPS | Progress: (16/20) | 20.16 s [Task 15/25] Current/Best: 19.04/ 21.58 GFLOPS | Progress: (20/20) | 24.45 s Done.
+ [Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 16/25] Current/Best: 8.34/ 18.12 GFLOPS | Progress: (4/20) | 4.19 s [Task 16/25] Current/Best: 18.66/ 18.66 GFLOPS | Progress: (8/20) | 6.83 s [Task 16/25] Current/Best: 15.36/ 18.66 GFLOPS | Progress: (12/20) | 9.93 s [Task 16/25] Current/Best: 5.91/ 18.66 GFLOPS | Progress: (16/20) | 11.73 s [Task 16/25] Current/Best: 18.18/ 20.01 GFLOPS | Progress: (20/20) | 14.50 s Done.
+ [Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 17/25] Current/Best: 6.21/ 19.76 GFLOPS | Progress: (4/20) | 5.80 s [Task 17/25] Current/Best: 12.34/ 19.76 GFLOPS | Progress: (8/20) | 8.52 s [Task 17/25] Current/Best: 9.58/ 19.76 GFLOPS | Progress: (12/20) | 11.41 s [Task 17/25] Current/Best: 4.44/ 19.94 GFLOPS | Progress: (16/20) | 15.25 s [Task 17/25] Current/Best: 5.38/ 20.86 GFLOPS | Progress: (20/20) | 18.25 s Done.
+ [Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 18/25] Current/Best: 18.52/ 18.52 GFLOPS | Progress: (4/20) | 4.97 s [Task 18/25] Current/Best: 16.81/ 18.52 GFLOPS | Progress: (8/20) | 7.19 s [Task 18/25] Current/Best: 12.94/ 18.52 GFLOPS | Progress: (12/20) | 10.26 s [Task 18/25] Current/Best: 17.08/ 21.82 GFLOPS | Progress: (16/20) | 14.18 s [Task 18/25] Current/Best: 16.28/ 21.82 GFLOPS | Progress: (20/20) | 18.53 s Done.
+ [Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 19/25] Current/Best: 12.00/ 13.18 GFLOPS | Progress: (4/20) | 5.53 s [Task 19/25] Current/Best: 11.92/ 13.18 GFLOPS | Progress: (8/20) | 10.73 s [Task 19/25] Current/Best: 8.97/ 13.18 GFLOPS | Progress: (12/20) | 15.10 s [Task 19/25] Current/Best: 18.17/ 18.17 GFLOPS | Progress: (16/20) | 19.21 s [Task 19/25] Current/Best: 18.37/ 18.37 GFLOPS | Progress: (20/20) | 22.16 s Done.
+ [Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 20/25] Current/Best: 7.51/ 15.99 GFLOPS | Progress: (4/20) | 6.13 s [Task 20/25] Current/Best: 8.81/ 15.99 GFLOPS | Progress: (8/20) | 17.75 s [Task 20/25] Current/Best: 12.15/ 18.66 GFLOPS | Progress: (12/20) | 29.21 s [Task 20/25] Current/Best: 11.63/ 18.66 GFLOPS | Progress: (16/20) | 40.73 s Done.
+ [Task 20/25] Current/Best: 16.41/ 18.66 GFLOPS | Progress: (20/20) | 44.88 s Done.
+ [Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 21/25] Current/Best: 3.73/ 20.73 GFLOPS | Progress: (4/20) | 4.30 s [Task 21/25] Current/Best: 13.02/ 20.73 GFLOPS | Progress: (8/20) | 16.05 s [Task 21/25] Current/Best: 12.43/ 20.73 GFLOPS | Progress: (12/20) | 18.88 s [Task 21/25] Current/Best: 14.60/ 20.73 GFLOPS | Progress: (16/20) | 20.67 s [Task 21/25] Current/Best: 17.95/ 20.73 GFLOPS | Progress: (20/20) | 23.01 s [Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 22/25] Current/Best: 15.72/ 17.73 GFLOPS | Progress: (4/20) | 4.18 s [Task 22/25] Current/Best: 6.56/ 17.73 GFLOPS | Progress: (8/20) | 6.00 s [Task 22/25] Current/Best: 17.29/ 17.73 GFLOPS | Progress: (12/20) | 7.93 s [Task 22/25] Current/Best: 14.32/ 17.73 GFLOPS | Progress: (16/20) | 11.03 s [Task 22/25] Current/Best: 17.82/ 21.98 GFLOPS | Progress: (20/20
) | 13.61 s Done.
+ [Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 23/25] Current/Best: 10.22/ 19.02 GFLOPS | Progress: (4/20) | 6.89 s [Task 23/25] Current/Best: 18.55/ 22.93 GFLOPS | Progress: (8/20) | 9.09 s [Task 23/25] Current/Best: 9.19/ 22.93 GFLOPS | Progress: (12/20) | 15.74 s [Task 23/25] Current/Best: 20.92/ 22.93 GFLOPS | Progress: (16/20) | 17.81 s [Task 23/25] Current/Best: 6.15/ 22.93 GFLOPS | Progress: (20/20) | 20.30 s Done.
+ [Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 24/25] Current/Best: 0.58/ 10.71 GFLOPS | Progress: (4/20) | 13.28 s [Task 24/25] Current/Best: 3.61/ 10.71 GFLOPS | Progress: (8/20) | 25.57 s [Task 24/25] Current/Best: 2.84/ 10.71 GFLOPS | Progress: (12/20) | 38.00 s [Task 24/25] Current/Best: 7.23/ 10.71 GFLOPS | Progress: (16/20) | 45.87 s [Task 24/25] Current/Best: 2.94/ 10.71 GFLOPS | Progress: (20/20) | 56.86 s [Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
Done.
- [Task 17/25] Current/Best: 9.16/ 23.71 GFLOPS | Progress: (20/20) | 19.36 s Done.
- [Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 18/25] Current/Best: 20.93/ 20.93 GFLOPS | Progress: (4/20) | 5.03 s [Task 18/25] Current/Best: 14.55/ 20.93 GFLOPS | Progress: (8/20) | 14.78 s [Task 18/25] Current/Best: 17.39/ 20.93 GFLOPS | Progress: (12/20) | 19.74 s [Task 18/25] Current/Best: 12.38/ 20.93 GFLOPS | Progress: (16/20) | 22.35 s [Task 18/25] Current/Best: 20.49/ 20.93 GFLOPS | Progress: (20/20) | 24.56 s Done.
- [Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 19/25] Current/Best: 10.53/ 20.44 GFLOPS | Progress: (4/20) | 5.51 s [Task 19/25] Current/Best: 5.35/ 21.02 GFLOPS | Progress: (8/20) | 8.86 s [Task 19/25] Current/Best: 14.94/ 21.02 GFLOPS | Progress: (12/20) | 12.71 s [Task 19/25] Current/Best: 6.47/ 21.02 GFLOPS | Progress: (16/20) | 17.20 s [Task 19/25] Current/Best: 18.88/ 21.02 GFLOPS | Progress: (20/20) | 22.05 s Done.
- [Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 20/25] Current/Best: 11.78/ 18.33 GFLOPS | Progress: (4/20) | 13.50 s [Task 20/25] Current/Best: 19.15/ 19.15 GFLOPS | Progress: (8/20) | 25.13 s [Task 20/25] Current/Best: 13.41/ 19.15 GFLOPS | Progress: (12/20) | 36.11 s [Task 20/25] Current/Best: 17.48/ 19.15 GFLOPS | Progress: (16/20) | 42.80 s [Task 20/25] Current/Best: 19.67/ 20.68 GFLOPS | Progress: (20/20) | 45.52 s [Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 21/25] Current/Best: 2.76/ 11.65 GFLOPS | Progress: (4/20) | 5.73 s [Task 21/25] Current/Best: 13.23/ 16.06 GFLOPS | Progress: (8/20) | 7.63 s [Task 21/25] Current/Best: 18.25/ 18.42 GFLOPS | Progress: (12/20) | 9.72 s [Task 21/25] Current/Best: 5.37/ 18.42 GFLOPS | Progress: (16/20) | 12.06 s [Task 21/25] Current/Best: 11.34/ 18.42 GFLOPS | Progress: (20/2
0) | 14.45 s Done.
- [Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 22/25] Current/Best: 11.54/ 12.09 GFLOPS | Progress: (4/20) | 5.16 s [Task 22/25] Current/Best: 13.63/ 17.71 GFLOPS | Progress: (8/20) | 6.92 s [Task 22/25] Current/Best: 6.79/ 17.71 GFLOPS | Progress: (12/20) | 12.36 s [Task 22/25] Current/Best: 9.68/ 18.17 GFLOPS | Progress: (16/20) | 14.14 s [Task 22/25] Current/Best: 7.32/ 19.47 GFLOPS | Progress: (20/20) | 17.24 s Done.
- [Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 23/25] Current/Best: 7.03/ 12.28 GFLOPS | Progress: (4/20) | 9.08 s [Task 23/25] Current/Best: 3.08/ 19.15 GFLOPS | Progress: (8/20) | 12.82 s [Task 23/25] Current/Best: 4.64/ 22.21 GFLOPS | Progress: (12/20) | 18.53 s [Task 23/25] Current/Best: 23.45/ 23.45 GFLOPS | Progress: (16/20) | 21.66 s [Task 23/25] Current/Best: 10.76/ 23.45 GFLOPS | Progress: (20/20) | 24.42 s Done.
- [Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s [Task 24/25] Current/Best: 6.72/ 10.07 GFLOPS | Progress: (4/20) | 4.67 s [Task 24/25] Current/Best: 2.06/ 10.07 GFLOPS | Progress: (8/20) | 15.42 s [Task 24/25] Current/Best: 0.94/ 10.07 GFLOPS | Progress: (12/20) | 28.04 s [Task 24/25] Current/Best: 3.21/ 10.07 GFLOPS | Progress: (16/20) | 40.94 s [Task 24/25] Current/Best: 3.12/ 10.07 GFLOPS | Progress: (20/20) | 51.83 s [Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s Done.
- Done.
- [Task 25/25] Current/Best: 5.91/ 8.88 GFLOPS | Progress: (4/20) | 4.36 s [Task 25/25] Current/Best: 5.42/ 8.88 GFLOPS | Progress: (8/20) | 7.61 s [Task 25/25] Current/Best: 2.87/ 8.88 GFLOPS | Progress: (12/20) | 18.67 s [Task 25/25] Current/Best: 1.55/ 8.88 GFLOPS | Progress: (16/20) | 26.02 s [Task 25/25] Current/Best: 9.18/ 9.18 GFLOPS | Progress: (20/20) | 37.01 s
+ [Task 25/25] Current/Best: 7.46/ 9.10 GFLOPS | Progress: (4/20) | 4.98 s [Task 25/25] Current/Best: 5.47/ 9.63 GFLOPS | Progress: (8/20) | 10.53 s [Task 25/25] Current/Best: 8.04/ 9.63 GFLOPS | Progress: (12/20) | 14.23 s [Task 25/25] Current/Best: 5.95/ 9.63 GFLOPS | Progress: (16/20) | 25.18 s [Task 25/25] Current/Best: 4.93/ 9.63 GFLOPS | Progress: (20/20) | 36.12 s
@@ -708,8 +708,8 @@ Verify that the optimized model runs and produces the same results:
.. code-block:: none
- class='n02123045 tabby, tabby cat' with probability=0.621104
- class='n02123159 tiger cat' with probability=0.356378
+ class='n02123045 tabby, tabby cat' with probability=0.621103
+ class='n02123159 tiger cat' with probability=0.356379
class='n02124075 Egyptian cat' with probability=0.019712
class='n02129604 tiger, Panthera tigris' with probability=0.001215
class='n04040759 radiator' with probability=0.000262
@@ -766,8 +766,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 419.9001278101059, 'median': 419.0085646499938, 'std': 3.0695088603576712}
- unoptimized: {'mean': 503.0455810299827, 'median': 503.0315536001581, 'std': 3.3010465330462697}
+ optimized: {'mean': 415.66954584002815, 'median': 414.8363615002381, 'std': 3.6258798258921097}
+ unoptimized: {'mean': 494.2683718200715, 'median': 493.55235119983263, 'std': 3.9869056543511348}
@@ -790,7 +790,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 13 minutes 46.797 seconds)
+ **Total running time of the script:** ( 13 minutes 36.376 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 eb63e9efc8..4dcd192771 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
- 1.236e-07 secs/op
+ 1.242e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index f4d1c7342c..ba8d138ed5 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, 0x28500200)), stage(b, placeholder(b, 0x620b4a0)), 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, 0x1868f010)), stage(b, placeholder(b, 0x2cad6db0)), 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 9640b81ef1..6c4ab6c1cf 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,31 +5,31 @@
Computation times
=================
-**18:02.764** total execution time for **tutorial** files:
+**16:59.789** total execution time for **tutorial** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 13:46.797 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 13:36.376 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:56.580 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 01:20.458 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:02.442 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:01.213 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:43.402 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:41.718 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:31.463 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:17.979 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.978 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.948 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.887 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.884 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.215 | 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_uma.py` (``uma.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``) | 00:00.000 | 0.0 MB |
-+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``) | 00:00.000 | 0.0 MB |
++------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``) | 00:00.000 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_install.py` (``install.py``) | 00:00.000 | 0.0 MB |
diff --git a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
index a9681bcfe3..46a0bca973 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: 0.000008
+ Numpy running time: 0.000008
+ naive: 0.000007
@@ -498,10 +498,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 7.113589999789838e-06 1.0
- naive 7.604500000000001e-06 1.0690101622703398
- parallel 8.3124e-06 1.168523909902817
- vector 3.90622e-05 5.4912076744870095
+ numpy 8.18609998532338e-06 1.0
+ naive 6.7127999999999995e-06 0.8200241888121551
+ parallel 8.206900000000001e-06 1.002540894285913
+ vector 3.90764e-05 4.773506318034099
@@ -922,7 +922,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.020493
+ Numpy running time: 0.018576
@@ -980,7 +980,7 @@ optimizations.
.. code-block:: none
- none: 3.505038
+ none: 3.511499
@@ -1080,7 +1080,7 @@ schedule.
.. code-block:: none
- blocking: 0.319902
+ blocking: 0.289229
@@ -1164,7 +1164,7 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- vectorization: 0.309665
+ vectorization: 0.266724
# 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: 0.118751
+ loop permutation: 0.114887
# 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: 0.105645
+ array packing: 0.106243
# 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: 0.115305
+ block caching: 0.111139
# 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: 0.137269
+ parallelization: 0.131560
# 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 3.5050377468000002 1.0
- blocking 0.31990181419999997 0.09126914952401333
- vectorization 0.3096646502 0.08834844945185398
- loop permutation 0.1187506674 0.03387999672996845
- array packing 0.10564480750000001 0.030140847297992927
- block caching 0.11530460740000001 0.03289682329534677
- parallelization 0.137269419 0.0391634638244119
+ none 3.5114988771999998 1.0
+ blocking 0.2892291554 0.08236629585102577
+ vectorization 0.2667237806 0.07595724501916411
+ loop permutation 0.1148865586 0.032717242014785514
+ array packing 0.1062425853 0.0302556227455541
+ block caching 0.1111391638 0.03165006388628556
+ parallelization 0.1315603297 0.0374655764677059
@@ -1596,7 +1596,7 @@ the computation for specific platforms.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 2.442 seconds)
+ **Total running time of the script:** ( 1 minutes 1.213 seconds)
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
diff --git a/docs/commit_hash b/docs/commit_hash
index 54d85c1e93..403830263d 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-bb2adbfc4abaad4608ad7dd6bd66248472dfc173
+3c5ee30630760b3e42202e622517a92c18f11889
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index 19433b08a3..75435abfed 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -605,7 +605,7 @@ class:['truck 0.9266'] left:471 top:83 right:689 bottom:169
class:['bicycle 0.9984'] left:111 top:113 right:577 bottom:447
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 37.289 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 34.407 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-darknet-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7716f96385bd5abb6e822041e285be54/from_darknet.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">from_darknet.py</span></code></a></p>
diff --git a/docs/how_to/compile_models/from_mxnet.html b/docs/how_to/compile_models/from_mxnet.html
index 1ef1a6c5f2..a39423c93e 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -465,7 +465,7 @@
<span class="nb">print</span><span class="p">(</span><span class="s2">"x"</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#tuple" title="builtins.tuple" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span><span class="o">.</span><span class="n">shape</span></a><span class="p">)</span>
</pre></div>
</div>
-<img src="../../_images/sphx_glr_from_mxnet_001.png" srcset="../../_images/sphx_glr_from_mxnet_001.png" alt="from mxnet" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipa9062fd2-e64e-4181-915c-8c8ee08d64c1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+<img src="../../_images/sphx_glr_from_mxnet_001.png" srcset="../../_images/sphx_glr_from_mxnet_001.png" alt="from mxnet" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip26038214-edea-49df-a3f0-61027438943c from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
x (1, 3, 224, 224)
</pre></div>
</div>
diff --git a/docs/how_to/compile_models/from_oneflow.html b/docs/how_to/compile_models/from_oneflow.html
index b8b120b750..94ec296a93 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -469,16 +469,14 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://oneflow-public.oss-cn-beijing.aliyuncs.com/model_zoo/flowvision/classification/ResNet/resnet18.zip" to /workspace/.oneflow/flowvision_cache/resnet18.zip
0%| | 0.00/41.5M [00:00<?, ?B/s]
- 15%|#5 | 6.33M/41.5M [00:00<00:00, 39.9MB/s]
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- 35%|###4 | 14.3M/41.5M [00:00<00:01, 27.3MB/s]
- 41%|####1 | 17.0M/41.5M [00:00<00:01, 25.2MB/s]
- 54%|#####3 | 22.3M/41.5M [00:00<00:00, 30.7MB/s]
- 61%|######1 | 25.4M/41.5M [00:00<00:00, 28.0MB/s]
- 77%|#######7 | 32.0M/41.5M [00:01<00:00, 36.3MB/s]
- 89%|########8 | 36.9M/41.5M [00:01<00:00, 40.0MB/s]
- 98%|#########8| 40.9M/41.5M [00:01<00:00, 40.3MB/s]
-100%|##########| 41.5M/41.5M [00:01<00:00, 35.1MB/s]
+ 15%|#5 | 6.33M/41.5M [00:00<00:00, 56.5MB/s]
+ 28%|##8 | 11.7M/41.5M [00:00<00:00, 50.0MB/s]
+ 40%|###9 | 16.5M/41.5M [00:00<00:01, 24.7MB/s]
+ 51%|#####1 | 21.2M/41.5M [00:00<00:00, 30.1MB/s]
+ 60%|###### | 25.0M/41.5M [00:00<00:00, 22.1MB/s]
+ 77%|#######7 | 32.0M/41.5M [00:01<00:00, 29.4MB/s]
+ 92%|#########2| 38.3M/41.5M [00:01<00:00, 33.0MB/s]
+100%|##########| 41.5M/41.5M [00:01<00:00, 32.1MB/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 c9d3919248..ca2edcc217 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -504,7 +504,7 @@ To begin, we’ll install PaddlePaddle>=2.1.3:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>TVM prediction top-1 id: 282, class name: 282: 'tiger cat',
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 4.282 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 0.271 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 57b942aa1c..2de6256efc 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -452,14 +452,14 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
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- 78%|#######8 | 34.9M/44.7M [00:00<00:00, 45.7MB/s]
- 90%|########9 | 40.0M/44.7M [00:01<00:00, 34.9MB/s]
-100%|##########| 44.7M/44.7M [00:01<00:00, 43.9MB/s]
+ 14%|#4 | 6.30M/44.7M [00:00<00:00, 63.8MB/s]
+ 28%|##7 | 12.4M/44.7M [00:00<00:00, 57.1MB/s]
+ 40%|#### | 17.9M/44.7M [00:00<00:00, 37.6MB/s]
+ 54%|#####3 | 24.0M/44.7M [00:00<00:00, 41.3MB/s]
+ 63%|######3 | 28.3M/44.7M [00:00<00:00, 38.7MB/s]
+ 72%|#######2 | 32.2M/44.7M [00:00<00:00, 34.3MB/s]
+ 90%|########9 | 40.0M/44.7M [00:01<00:00, 37.5MB/s]
+100%|##########| 44.7M/44.7M [00:01<00:00, 42.8MB/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 7b23c5f4d2..0465b79f47 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -672,7 +672,7 @@ banana (score = 0.00022)
desk (score = 0.00019)
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 33.896 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 30.118 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 a03dff6442..b983789ef0 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-compile-models-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>07:27.248</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>07:08.640</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -369,43 +369,43 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="from_darknet.html#sphx-glr-how-to-compile-models-from-darknet-py"><span class="std std-ref">Compile YOLO-V2 and YOLO-V3 in DarkNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_darknet.py</span></code>)</p></td>
-<td><p>01:37.289</p></td>
+<td><p>01:34.407</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_tensorflow.html#sphx-glr-how-to-compile-models-from-tensorflow-py"><span class="std std-ref">Compile Tensorflow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tensorflow.py</span></code>)</p></td>
-<td><p>01:33.896</p></td>
+<td><p>01:30.118</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_paddle.html#sphx-glr-how-to-compile-models-from-paddle-py"><span class="std std-ref">Compile PaddlePaddle Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_paddle.py</span></code>)</p></td>
-<td><p>01:04.282</p></td>
+<td><p>01:00.271</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_oneflow.html#sphx-glr-how-to-compile-models-from-oneflow-py"><span class="std std-ref">Compile OneFlow Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_oneflow.py</span></code>)</p></td>
-<td><p>00:43.999</p></td>
+<td><p>00:42.149</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_coreml.html#sphx-glr-how-to-compile-models-from-coreml-py"><span class="std std-ref">Compile CoreML Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_coreml.py</span></code>)</p></td>
-<td><p>00:39.303</p></td>
+<td><p>00:37.456</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_mxnet.html#sphx-glr-how-to-compile-models-from-mxnet-py"><span class="std std-ref">Compile MXNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_mxnet.py</span></code>)</p></td>
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+<td><p>00:34.386</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="from_pytorch.html#sphx-glr-how-to-compile-models-from-pytorch-py"><span class="std std-ref">Compile PyTorch Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_pytorch.py</span></code>)</p></td>
-<td><p>00:29.434</p></td>
+<td><p>00:28.001</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_keras.html#sphx-glr-how-to-compile-models-from-keras-py"><span class="std std-ref">Compile Keras Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_keras.py</span></code>)</p></td>
-<td><p>00:28.442</p></td>
+<td><p>00:26.742</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="from_tflite.html#sphx-glr-how-to-compile-models-from-tflite-py"><span class="std std-ref">Compile TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_tflite.py</span></code>)</p></td>
-<td><p>00:12.369</p></td>
+<td><p>00:12.283</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_onnx.html#sphx-glr-how-to-compile-models-from-onnx-py"><span class="std std-ref">Compile ONNX Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_onnx.py</span></code>)</p></td>
-<td><p>00:02.970</p></td>
+<td><p>00:02.829</p></td>
<td><p>0.0 MB</p></td>
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diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno.html b/docs/how_to/deploy_models/deploy_model_on_adreno.html
index dd345580d6..1a324a2226 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)
- 4122.0436 4121.8198 4126.1778 4118.5481 2.0636
+ 4118.3687 4118.5281 4121.2484 4115.9894 1.6007
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 20.516 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 18.900 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-model-on-adreno-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/2387d8448da213eb625e6b3d916327d4/deploy_model_on_adreno.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_model_on_adreno.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html b/docs/how_to/deploy_models/deploy_model_on_adreno_tvmc.html
index ac29f29ade..f0419a3521 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
@@ -458,31 +458,25 @@ to run this tutorial with a real device over rpc.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels.h5
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diff --git a/docs/how_to/deploy_models/deploy_model_on_android.html b/docs/how_to/deploy_models/deploy_model_on_android.html
index a89de3da29..d53db3e4c7 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -682,7 +682,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 15.4306 15.3590 16.2163 14.8317 0.4306
+ 14.8581 14.8115 15.3361 14.6018 0.1976
</pre></div>
</div>
</div>
diff --git a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
index e7fc184b7d..37f94a4f15 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -474,33 +474,37 @@ be unstable.</p>
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
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/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/nn/functional.py:3912: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
(torch.floor((input.size(i + 2).float() * torch.tensor(scale_factors[i], dtype=torch.float32)).float()))
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torchvision/ops/boxes.py:157: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
@@ -591,7 +595,7 @@ torchvision rcnn models.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get 9 valid boxes
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 42.993 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 31.957 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 477227bc5e..00df4fb916 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -515,8 +515,10 @@ training. Other models require a full post training calibration.</p>
Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
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</pre></div>
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@@ -607,7 +609,7 @@ 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)
- 89.0513 88.9712 90.9339 88.6984 0.3292
+ 88.9296 88.8443 92.6071 88.4699 0.4610
</pre></div>
</div>
<div class="admonition note">
@@ -646,7 +648,7 @@ This includes support for the VNNI 8 bit dot product instruction (CascadeLake or
<div class="section" id="deploy-a-quantized-tflite-model">
<h2>Deploy a quantized TFLite Model<a class="headerlink" href="#deploy-a-quantized-tflite-model" title="Permalink to this headline">¶</a></h2>
<p>TODO</p>
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<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-prequantized-py">
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<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 f989b93789..cab6732382 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)
- 111.4260 111.3542 113.3218 110.6454 0.4494
+ 108.9672 108.6613 115.6633 107.3984 1.2400
</pre></div>
</div>
<div class="admonition note">
diff --git a/docs/how_to/deploy_models/deploy_quantized.html b/docs/how_to/deploy_models/deploy_quantized.html
index 9c728c782f..942248b2d0 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -548,7 +548,7 @@ for calibration. But the accuracy might be impacted.</p>
warnings.warn(
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 7.828 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 16.574 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-quantized-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/7810ecf51bfc05f7d5e8a400ac3e815d/deploy_quantized.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_quantized.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/sg_execution_times.html b/docs/how_to/deploy_models/sg_execution_times.html
index 83f53b6875..99ac467cb4 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>12:18.499</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>12:01.721</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 86%" />
@@ -369,39 +369,39 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_object_detection_pytorch.html#sphx-glr-how-to-deploy-models-deploy-object-detection-pytorch-py"><span class="std std-ref">Compile PyTorch Object Detection Models</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_object_detection_pytorch.py</span></code>)</p></td>
-<td><p>03:42.993</p></td>
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<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_quantized.html#sphx-glr-how-to-deploy-models-deploy-quantized-py"><span class="std std-ref">Deploy a Quantized Model on Cuda</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_quantized.py</span></code>)</p></td>
-<td><p>02:07.828</p></td>
+<td><p>02:16.574</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_prequantized.html#sphx-glr-how-to-deploy-models-deploy-prequantized-py"><span class="std std-ref">Deploy a Framework-prequantized Model with TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_prequantized.py</span></code>)</p></td>
-<td><p>01:30.964</p></td>
+<td><p>01:27.193</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_adreno.html#sphx-glr-how-to-deploy-models-deploy-model-on-adreno-py"><span class="std std-ref">Deploy the Pretrained Model on Adreno™</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_adreno.py</span></code>)</p></td>
-<td><p>01:20.516</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="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>00:53.289</p></td>
+<td><p>00:51.254</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_android.html#sphx-glr-how-to-deploy-models-deploy-model-on-android-py"><span class="std std-ref">Deploy the Pretrained Model on Android</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_android.py</span></code>)</p></td>
-<td><p>00:52.057</p></td>
+<td><p>00:49.931</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_adreno_tvmc.html#sphx-glr-how-to-deploy-models-deploy-model-on-adreno-tvmc-py"><span class="std std-ref">Deploy the Pretrained Model on Adreno™ with tvmc Interface</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_adreno_tvmc.py</span></code>)</p></td>
-<td><p>00:48.574</p></td>
+<td><p>00:45.610</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_model_on_nano.html#sphx-glr-how-to-deploy-models-deploy-model-on-nano-py"><span class="std std-ref">Deploy the Pretrained Model on Jetson Nano</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_nano.py</span></code>)</p></td>
-<td><p>00:31.415</p></td>
+<td><p>00:30.289</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_model_on_rasp.html#sphx-glr-how-to-deploy-models-deploy-model-on-rasp-py"><span class="std std-ref">Deploy the Pretrained Model on Raspberry Pi</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_model_on_rasp.py</span></code>)</p></td>
-<td><p>00:30.856</p></td>
+<td><p>00:30.006</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_sparse.html#sphx-glr-how-to-deploy-models-deploy-sparse-py"><span class="std std-ref">Deploy a Hugging Face Pruned Model on CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_sparse.py</span></code>)</p></td>
diff --git a/docs/how_to/extend_tvm/bring_your_own_datatypes.html b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
index 399441dcd1..f177b14cdd 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -645,7 +645,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
<a href="https://docs.python.org/3/library/sys.html#sys.exit" title="sys.exit" class="sphx-glr-backref-module-sys sphx-glr-backref-type-py-function"><span class="n">sys</span><span class="o">.</span><span class="n">exit</span></a><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip6ee3b7ce-d372-42c1-8095-40002972f8a9 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip4e2bb27b-1d34-4100-bd7d-258a4ee40519 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
</pre></div>
</div>
<p>It’s easy to execute MobileNet with native TVM:</p>
diff --git a/docs/how_to/extend_tvm/sg_execution_times.html b/docs/how_to/extend_tvm/sg_execution_times.html
index 1ef67ab642..f91d5a94d4 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-extend-tvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:59.989</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:57.202</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -369,19 +369,19 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="bring_your_own_datatypes.html#sphx-glr-how-to-extend-tvm-bring-your-own-datatypes-py"><span class="std std-ref">Bring Your Own Datatypes to TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">bring_your_own_datatypes.py</span></code>)</p></td>
-<td><p>00:55.898</p></td>
+<td><p>00:53.204</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="use_pass_instrument.html#sphx-glr-how-to-extend-tvm-use-pass-instrument-py"><span class="std std-ref">How to Use TVM Pass Instrument</span></a> (<code class="docutils literal notranslate"><span class="pre">use_pass_instrument.py</span></code>)</p></td>
-<td><p>00:02.872</p></td>
+<td><p>00:02.793</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="use_pass_infra.html#sphx-glr-how-to-extend-tvm-use-pass-infra-py"><span class="std std-ref">How to Use TVM Pass Infra</span></a> (<code class="docutils literal notranslate"><span class="pre">use_pass_infra.py</span></code>)</p></td>
-<td><p>00:01.211</p></td>
+<td><p>00:01.197</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="low_level_custom_pass.html#sphx-glr-how-to-extend-tvm-low-level-custom-pass-py"><span class="std std-ref">Writing a Customized Pass</span></a> (<code class="docutils literal notranslate"><span class="pre">low_level_custom_pass.py</span></code>)</p></td>
-<td><p>00:00.008</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 e6db0bfc9c..e95d568af9 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -546,10 +546,10 @@ profile the execution time of each passes.</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 25280us [25280us] (48.39%; 48.39%)
-FoldScaleAxis: 26967us [9us] (51.61%; 51.61%)
- FoldConstant: 26958us [1829us] (51.60%; 99.97%)
- InferType: 25129us [25129us] (48.10%; 93.21%)
+InferType: 25596us [25596us] (49.18%; 49.18%)
+FoldScaleAxis: 26448us [7us] (50.82%; 50.82%)
+ FoldConstant: 26441us [1816us] (50.80%; 99.97%)
+ InferType: 24625us [24625us] (47.32%; 93.13%)
</pre></div>
</div>
</div>
@@ -571,10 +571,10 @@ Refer to following sections and <a class="reference internal" href="../../refere
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 25185us [25185us] (48.02%; 48.02%)
-FoldScaleAxis: 27266us [9us] (51.98%; 51.98%)
- FoldConstant: 27257us [2024us] (51.97%; 99.97%)
- InferType: 25233us [25233us] (48.11%; 92.57%)
+InferType: 24514us [24514us] (48.48%; 48.48%)
+FoldScaleAxis: 26048us [7us] (51.52%; 51.52%)
+ FoldConstant: 26042us [1774us] (51.50%; 99.97%)
+ InferType: 24268us [24268us] (48.00%; 93.19%)
</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 ef92380567..0f7013003b 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -595,7 +595,7 @@ latency of convolution.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Convolution: </span><span class="si">%f</span><span class="s2"> ms"</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">*</span> <span cl [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 43.692832 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 36.099391 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 ae23e11d40..aedca37f86 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -877,7 +877,7 @@ be able to run on our build server</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"conv2d with tensor core: </span><span class="si">%f</span><span class="s2"> ms"</span> <span class="o">%</span> <span class="p">(</span><span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span> <span class="o">* [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.266087 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 12.267693 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 e5c266ca5a..4716b4c4f0 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -492,8 +492,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
<span class="nb">print</span><span class="p">(</span><span class="s2">"Baseline: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.019720
-Baseline: 3.505645
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.018058
+Baseline: 3.527402
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -552,7 +552,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt1: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.296518
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.296422
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -609,7 +609,7 @@ vastly.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt2: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.284328
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.272153
</pre></div>
</div>
<p>Here is the generated IR after vectorization.</p>
@@ -664,7 +664,7 @@ the access pattern for A matrix is more cache friendly.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt3: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.116417
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.114605
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -741,7 +741,7 @@ flattening.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt4: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.107504
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.107752
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -819,7 +819,7 @@ write to C when all the block results are ready.</p>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt5: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">evaluator</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.116506
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.111886
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -899,7 +899,7 @@ class Module:
<span class="nb">print</span><span class="p">(</span><span class="s2">"Opt6: </span><span class="si">%f</span><span class="s2">"</span> <span class="o">%</span> <span class="n">opt6_time</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.138231
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.133158
</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 fe134e443e..a10853b7bf 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>00:35.033</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:34.236</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>00:31.651</p></td>
+<td><p>00:31.057</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>00:02.002</p></td>
+<td><p>00:01.906</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>00:01.379</p></td>
+<td><p>00:01.274</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 9a9d2042c5..74ff33396a 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>03:41.637</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>03:34.761</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -369,27 +369,27 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_x86.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-x86-py"><span class="std std-ref">Auto-scheduling a Neural Network for x86 CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_x86.py</span></code>)</p></td>
-<td><p>01:35.371</p></td>
+<td><p>01:32.410</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-cuda-py"><span class="std std-ref">Auto-scheduling a Neural Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_cuda.py</span></code>)</p></td>
-<td><p>01:13.848</p></td>
+<td><p>01:12.004</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>
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<tr class="row-even"><td><p><a class="reference internal" href="tune_sparse_x86.html#sphx-glr-how-to-tune-with-autoscheduler-tune-sparse-x86-py"><span class="std std-ref">Auto-scheduling Sparse Matrix Multiplication on CPU with Custom Sketch Rule</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_sparse_x86.py</span></code>)</p></td>
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diff --git a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html b/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
index 7bd1d9d38b..f687db0a20 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
@@ -1032,7 +1032,7 @@ class Module:
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.346 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.335 ms
</pre></div>
</div>
</div>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
index b193a94447..a076639978 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -941,7 +941,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 3.2416 3.2403 3.2458 3.2386 0.0031
+ 3.2038 3.2001 3.2121 3.1992 0.0059
</pre></div>
</div>
</div>
@@ -963,7 +963,7 @@ to learn how to use the RPC Tracker and RPC Server.
To use the RPC Tracker in auto-scheduler, replace the runner in <code class="code docutils literal notranslate"><span class="pre">TuningOptions</span></code>
with <a class="reference internal" href="../../reference/api/python/auto_scheduler.html#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref any py py-class docutils literal notranslate"><span class="pre">auto_scheduler.RPCRunner</span></code></a>.</p></li>
</ol>
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<p><a class="reference download internal" download="" href="../../_downloads/eafe360d52540634c9eea0fa89e804bd/tune_network_cuda.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_cuda.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
index e6de2521b5..595548876b 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -962,7 +962,7 @@ so we can read the log file and load the best schedules.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 766.3748 764.5378 772.7261 761.8605 4.6222
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</pre></div>
</div>
</div>
@@ -984,7 +984,7 @@ to learn how to use the RPC Tracker and RPC Server.
To use the RPC Tracker in auto-scheduler, replace the runner in <code class="code docutils literal notranslate"><span class="pre">TuningOptions</span></code>
with <a class="reference internal" href="../../reference/api/python/auto_scheduler.html#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref any py py-class docutils literal notranslate"><span class="pre">auto_scheduler.RPCRunner</span></code></a>.</p></li>
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diff --git a/docs/how_to/tune_with_autotvm/sg_execution_times.html b/docs/how_to/tune_with_autotvm/sg_execution_times.html
index c70a8fd222..276050ac39 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-tune-with-autotvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:24.066</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:23.665</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -369,11 +369,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-conv2d-cuda-py"><span class="std std-ref">Tuning High Performance Convolution on NVIDIA GPUs</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_cuda.py</span></code>)</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-cuda-py"><span class="std std-ref">Auto-tuning a Convolutional Network for NVIDIA GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_cuda.py</span></code>)</p></td>
diff --git a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
index 272a995c0d..d5ebc9c585 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -630,7 +630,7 @@ and measure running time.</p>
Best config:
,None
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</pre></div>
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<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autotvm-tune-conv2d-cuda-py">
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--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -664,10 +664,10 @@ the tuned operator.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 307.2 98.721 (1, 2, 10, 10, 3) 2 1 [307.2]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.978 0.957 (1, 6, 10, 10) 1 1 [2.978]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 1.002 0.322 (1, 1, 10, 10, 3) 1 1 [1.002]
-Total_time - 311.18 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 304.8 98.717 (1, 2, 10, 10, 3) 2 1 [304.8]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.985 0.967 (1, 6, 10, 10) 1 1 [2.985]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.976 0.316 (1, 1, 10, 10, 3) 1 1 [0.976]
+Total_time - 308.761 - - - - -
</pre></div>
</div>
</div>
@@ -719,13 +719,13 @@ Total_time -
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs Measurements(us)
--------- --- -------- ------- ----- ------ ------- ----------------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 101.3 97.313 (1, 6, 10, 10, 1) 2 1 [101.3]
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.809 1.737 (1, 6, 10, 10) 1 1 [1.809]
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.988 0.949 (1, 1, 10, 10, 3) 1 1 [0.988]
-Total_time - 104.097 - - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 102.2 97.444 (1, 6, 10, 10, 1) 2 1 [102.2]
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.827 1.742 (1, 6, 10, 10) 1 1 [1.827]
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.853 0.813 (1, 3, 10, 10, 1) 1 1 [0.853]
+Total_time - 104.88 - - - - -
</pre></div>
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<p><a class="reference download internal" download="" href="../../_downloads/9ccca8fd489a1486ac71b55a55c320c5/micro_autotune.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">micro_autotune.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/micro_pytorch.html b/docs/how_to/work_with_microtvm/micro_pytorch.html
index a63e93ccc8..233047c22f 100644
--- a/docs/how_to/work_with_microtvm/micro_pytorch.html
+++ b/docs/how_to/work_with_microtvm/micro_pytorch.html
@@ -475,8 +475,8 @@ download a cat image and preprocess it to use as the model input.</p>
Downloading: "https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2_qnnpack_37f702c5.pth
0%| | 0.00/3.42M [00:00<?, ?B/s]
- 61%|###### | 2.09M/3.42M [00:00<00:00, 4.09MB/s]
-100%|##########| 3.42M/3.42M [00:00<00:00, 6.62MB/s]
+ 61%|###### | 2.09M/3.42M [00:00<00:00, 12.8MB/s]
+100%|##########| 3.42M/3.42M [00:00<00:00, 20.5MB/s]
/venv/apache-tvm-py3.8/lib/python3.8/site-packages/torch/_utils.py:314: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
device=storage.device,
/workspace/python/tvm/relay/frontend/pytorch_utils.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
@@ -604,7 +604,7 @@ via the host <cite>main.cc`</cite> or if a Zephyr emulated board is selected as
Torch top-1 id: 282, class name: tiger cat
</pre></div>
</div>
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 28.641 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-pytorch-py">
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<p><a class="reference download internal" download="" href="../../_downloads/12b9ecc04c41abaa12022061771821d1/micro_pytorch.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">micro_pytorch.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/micro_train.html b/docs/how_to/work_with_microtvm/micro_train.html
index af4f7664b6..8ab735349b 100644
--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -543,7 +543,7 @@ take about <strong>2 minutes</strong> to download the Stanford Cars, while COCO
<a href="https://docs.python.org/3/library/shutil.html#shutil.move" title="shutil.move" class="sphx-glr-backref-module-shutil sphx-glr-backref-type-py-function"><span class="n">shutil</span><span class="o">.</span><span class="n">move</span></a><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-typ [...]
</pre></div>
</div>
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</pre></div>
</div>
</div>
@@ -603,8 +603,8 @@ objects to other stuff? We can display some examples from our datasets using <co
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s2">"off"</span><span class="p">)</span>
</pre></div>
</div>
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-/tmp/tmph6yqhz09/images/random contains 5000 images
+<img src="../../_images/sphx_glr_micro_train_001.png" srcset="../../_images/sphx_glr_micro_train_001.png" alt="[1.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [0.0, 1.0], [1.0, 0.0], [0.0, 1.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmptx_a_q0x/images/target contains 8144 images
+/tmp/tmptx_a_q0x/images/random contains 5000 images
</pre></div>
</div>
</div>
@@ -716,13 +716,13 @@ the time on our validation set).</p>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Epoch 1/3
-328/328 - 39s - loss: 0.2721 - accuracy: 0.9157 - val_loss: 0.1259 - val_accuracy: 0.9577 - 39s/epoch - 119ms/step
+328/328 - 40s - loss: 0.2298 - accuracy: 0.9227 - val_loss: 0.1226 - val_accuracy: 0.9622 - 40s/epoch - 121ms/step
Epoch 2/3
-328/328 - 36s - loss: 0.1119 - accuracy: 0.9590 - val_loss: 0.1075 - val_accuracy: 0.9634 - 36s/epoch - 109ms/step
+328/328 - 35s - loss: 0.1031 - accuracy: 0.9634 - val_loss: 0.0945 - val_accuracy: 0.9675 - 35s/epoch - 108ms/step
Epoch 3/3
-328/328 - 35s - loss: 0.0739 - accuracy: 0.9719 - val_loss: 0.1007 - val_accuracy: 0.9739 - 35s/epoch - 108ms/step
+328/328 - 35s - loss: 0.0635 - accuracy: 0.9760 - val_loss: 0.1514 - val_accuracy: 0.9475 - 35s/epoch - 107ms/step
-<keras.callbacks.History object at 0x7f46aa3b7160>
+<keras.callbacks.History object at 0x7f5d2956fe80>
</pre></div>
</div>
</div>
@@ -986,7 +986,7 @@ as intended.</p>
<p>From here, we could modify the model to read live images from the camera - we have another
Arduino tutorial for how to do that <a class="reference external" href="https://github.com/guberti/tvm-arduino-demos/tree/master/examples/person_detection">on GitHub</a>. Alternatively, we could also
<a class="reference external" href="https://tvm.apache.org/docs/how_to/work_with_microtvm/micro_autotune.html">use TVM’s autotuning capabilities</a> to dramatically improve the model’s performance.</p>
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 4 minutes 45.827 seconds)</p>
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diff --git a/docs/how_to/work_with_microtvm/sg_execution_times.html b/docs/how_to/work_with_microtvm/sg_execution_times.html
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+++ b/docs/how_to/work_with_microtvm/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-microtvm-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
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+<p><strong>08:07.891</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 82%" />
@@ -369,27 +369,27 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="micro_train.html#sphx-glr-how-to-work-with-microtvm-micro-train-py"><span class="std std-ref">5. Training Vision Models for microTVM on Arduino</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_train.py</span></code>)</p></td>
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<tr class="row-even"><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>
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<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>
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<td><p>0.0 MB</p></td>
</tr>
<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>
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<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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<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 70d4f0badd..9c61c259ec 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-relay-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
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+<p><strong>00:38.622</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-odd"><td><p><a class="reference internal" href="using_pipeline_executor.html#sphx-glr-how-to-work-with-relay-using-pipeline-executor-py"><span class="std std-ref">Using Pipeline Executor in Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_pipeline_executor.py</span></code>)</p></td>
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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>
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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>
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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 906b1b9347..a62fe48671 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -572,7 +572,7 @@ The following example customizes CUDA lowering rule for <code class="code docuti
<a href="../../reference/api/python/ir.html#tvm.ir.register_intrin_lowering" title="tvm.ir.register_intrin_lowering" class="sphx-glr-backref-module-tvm-ir sphx-glr-backref-type-py-function"><span class="n">register_intrin_lowering</span></a><span class="p">(</span><span class="s2">"tir.exp"</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s2">"cuda"</span><span class="p">,</span> <span class="n">f</span><span class="o">= [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7f46ae046280>
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7f5d2ccdb310>
</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 4c574fcb4f..e0e09b0259 100644
--- a/docs/how_to/work_with_schedules/sg_execution_times.html
+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -360,7 +360,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
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<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -369,31 +369,31 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="intrin_math.html#sphx-glr-how-to-work-with-schedules-intrin-math-py"><span class="std std-ref">Intrinsics and Math Functions</span></a> (<code class="docutils literal notranslate"><span class="pre">intrin_math.py</span></code>)</p></td>
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</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensorize.html#sphx-glr-how-to-work-with-schedules-tensorize-py"><span class="std std-ref">Use Tensorize to Leverage Hardware Intrinsics</span></a> (<code class="docutils literal notranslate"><span class="pre">tensorize.py</span></code>)</p></td>
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<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
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<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>00:00.746</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>
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<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="schedule_primitives.html#sphx-glr-how-to-work-with-schedules-schedule-primitives-py"><span class="std std-ref">Schedule Primitives in TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">schedule_primitives.py</span></code>)</p></td>
-<td><p>00:00.070</p></td>
+<td><p>00:00.069</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>00:00.067</p></td>
+<td><p>00:00.066</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tuple_inputs.html#sphx-glr-how-to-work-with-schedules-tuple-inputs-py"><span class="std std-ref">Compute and Reduce with Tuple Inputs</span></a> (<code class="docutils literal notranslate"><span class="pre">tuple_inputs.py</span></code>)</p></td>
diff --git a/docs/install/nnpack.html b/docs/install/nnpack.html
index 262b273e47..61f3a9d084 100644
--- a/docs/install/nnpack.html
+++ b/docs/install/nnpack.html
@@ -249,7 +249,17 @@
<p class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
<ul class="current">
<li class="toctree-l1 current"><a class="reference internal" href="index.html">Installing TVM</a><ul class="current">
-<li class="toctree-l2"><a class="reference internal" href="from_source.html">Install from Source</a></li>
+<li class="toctree-l2 current"><a class="reference internal" href="from_source.html">Install from Source</a><ul class="current">
+<li class="toctree-l3"><a class="reference internal" href="from_source.html#developers-get-source-from-github">Developers: Get Source from Github</a></li>
+<li class="toctree-l3"><a class="reference internal" href="from_source.html#build-the-shared-library">Build the Shared Library</a></li>
+<li class="toctree-l3"><a class="reference internal" href="from_source.html#python-package-installation">Python Package Installation</a></li>
+<li class="toctree-l3 current"><a class="reference internal" href="from_source.html#install-contrib-libraries">Install Contrib Libraries</a><ul class="current">
+<li class="toctree-l4 current"><a class="current reference internal" href="#">NNPACK Contrib Installation</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="from_source.html#enable-c-tests">Enable C++ Tests</a></li>
+</ul>
+</li>
<li class="toctree-l2"><a class="reference internal" href="docker.html">Docker Images</a></li>
<li class="toctree-l2 current"><a class="current reference internal" href="#">NNPACK Contrib Installation</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#conditions">Conditions</a></li>
diff --git a/docs/reference/api/doxygen/functions_c.html b/docs/reference/api/doxygen/functions_c.html
index 0bca6ac6fc..cfed3f5064 100644
--- a/docs/reference/api/doxygen/functions_c.html
+++ b/docs/reference/api/doxygen/functions_c.html
@@ -136,6 +136,9 @@ $(function() {
<li>caller_return_register
: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFrame.html#a2f6c425a89ee6872ead9bc71ab87fdd1">tvm::runtime::vm::VMFrame</a>
</li>
+<li>CallFromRegister()
+: <a class="el" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac2fd6c84fd50b55f7c8afd0edeb5b0ec">tvm::runtime::relax_vm::Instruction</a>
+</li>
<li>CallPacked()
: <a class="el" href="classtvm_1_1GenericFunc.html#a4d3816fb9dddb92e7e9f89bfbb70352a">tvm::GenericFunc</a>
, <a class="el" href="classtvm_1_1runtime_1_1PackedFunc.html#a9b39e8a75956bc889745ded9131b9c17">tvm::runtime::PackedFunc</a>
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: <a class="el" href="classtvm_1_1te_1_1ComputeOpNode.html#a45e42c63bd2ba62b6f85b9b79e0b9361">tvm::te::ComputeOpNode</a>
</li>
<li>ComputeRootStep()
-: <a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeRootStep.html#ab2e65ee558a69c55141b4319a81cb2cc">tvm::auto_scheduler::ComputeRootStep</a>
+: <a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeRootStep.html#a26f5d934c644d211cd5bb51c5abb8734">tvm::auto_scheduler::ComputeRootStep</a>
</li>
<li>Concat()
: <a class="el" href="classtvm_1_1tir_1_1Shuffle.html#a0a46caa8627735586e7dc67fa9321c59">tvm::tir::Shuffle</a>
diff --git a/docs/reference/api/doxygen/functions_e.html b/docs/reference/api/doxygen/functions_e.html
index 4fe0e26c7b..30f6e721ee 100644
--- a/docs/reference/api/doxygen/functions_e.html
+++ b/docs/reference/api/doxygen/functions_e.html
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, <a class="el" href="classtvm_1_1relax_1_1BlockBuilderNode.html#aecf7b4a03d847d33d6b5c8ed1f869aec">tvm::relax::BlockBuilderNode</a>
</li>
<li>EmitCall()
-: <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a3d3315cbf54d5ffe9f5b9424db928681">tvm::relax::ExecBuilderNode</a>
+: <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a8e16ffb417b0033ef3d63fee11cdc5ad">tvm::relax::ExecBuilderNode</a>
</li>
<li>EmitFatal()
: <a class="el" href="classtvm_1_1DiagnosticContext.html#a3668f9c5770d93f92bc1ad3b7b449ee4">tvm::DiagnosticContext</a>
diff --git a/docs/reference/api/doxygen/functions_func_c.html b/docs/reference/api/doxygen/functions_func_c.html
index bbcd4b06ea..61912c6395 100644
--- a/docs/reference/api/doxygen/functions_func_c.html
+++ b/docs/reference/api/doxygen/functions_func_c.html
@@ -114,11 +114,14 @@ $(function() {
<li>CallDoc()
: <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDoc.html#a8bebc54ecdc7c2c7cbf4b8bb6dc902c0">tvm::script::printer::CallDoc</a>
</li>
+<li>CallFromRegister()
+: <a class="el" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac2fd6c84fd50b55f7c8afd0edeb5b0ec">tvm::runtime::relax_vm::Instruction</a>
+</li>
<li>CallPacked()
: <a class="el" href="classtvm_1_1GenericFunc.html#a4d3816fb9dddb92e7e9f89bfbb70352a">tvm::GenericFunc</a>
, <a class="el" href="classtvm_1_1runtime_1_1PackedFunc.html#a9b39e8a75956bc889745ded9131b9c17">tvm::runtime::PackedFunc</a>
, <a class="el" href="classtvm_1_1runtime_1_1PackedFuncObj.html#ae5f18a03762f4e3e347b624140774855">tvm::runtime::PackedFuncObj</a>
-, <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#ae281ce8a586816f9827eebc92514e1f4">tvm::runtime::SessionObj</a>
+, <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a3e5a412f242d3e466f9b359852fcc0fa">tvm::runtime::SessionObj</a>
</li>
<li>CallPattern()
: <a class="el" href="classtvm_1_1relax_1_1CallPattern.html#a1257b1b980b0e34ce4a94f06227a3ff0">tvm::relax::CallPattern</a>
diff --git a/docs/reference/api/doxygen/functions_func_g.html b/docs/reference/api/doxygen/functions_func_g.html
index 8ec8b82c05..249b48a0b7 100644
--- a/docs/reference/api/doxygen/functions_func_g.html
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@@ -120,7 +120,7 @@ $(function() {
, <a class="el" href="classtvm_1_1TargetKind.html#a11c894b5e17dd940287648261d5efc0d">tvm::TargetKind</a>
, <a class="el" href="classtvm_1_1TargetTag.html#af90a7c152674c7dfe96f6e5aac2f9b25">tvm::TargetTag</a>
, <a class="el" href="classtvm_1_1tir_1_1InstructionKind.html#a6d165507be268ad41aa5221d48062da7">tvm::tir::InstructionKind</a>
-, <a class="el" href="classtvm_1_1tir_1_1LayoutAxis.html#a273d3cfc07193e551292450bc2b0e56f">tvm::tir::LayoutAxis</a>
+, <a class="el" href="classtvm_1_1tir_1_1LayoutAxis.html#a4b5df87bf9971c025f4c3399a369fd99">tvm::tir::LayoutAxis</a>
, <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#aec0dd6e11e5c3cd85766a5a5ad9acd41">tvm::tir::ScheduleNode</a>
</li>
<li>get()
@@ -133,7 +133,7 @@ $(function() {
</li>
<li>get()
: <a class="el" href="classtvm_1_1tir_1_1Var.html#a018469fa554bee82399594e7d6bfad1d">tvm::tir::Var</a>
-, <a class="el" href="classtvm_1_1With.html#acc09c3d117aa5500f8579e18866209f8">tvm::With< ContextType ></a>
+, <a class="el" href="classtvm_1_1With.html#a54ab86b1e1f78e9304d8b89c97eb07af">tvm::With< ContextType ></a>
</li>
<li>get_c_struct_name()
: <a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ConstantInfoMetadataNode.html#a00880e8239fec43504324e48552d8632">tvm::runtime::metadata::ConstantInfoMetadataNode</a>
diff --git a/docs/reference/api/doxygen/functions_func_n.html b/docs/reference/api/doxygen/functions_func_n.html
index 459dfc01f5..eee33d0745 100644
--- a/docs/reference/api/doxygen/functions_func_n.html
+++ b/docs/reference/api/doxygen/functions_func_n.html
@@ -86,7 +86,7 @@ $(function() {
: <a class="el" href="classtvm_1_1relax_1_1BlockBuilderNode.html#a0d90afaaadeab9dedac9a61311c910f5">tvm::relax::BlockBuilderNode</a>
</li>
<li>NameSupply()
-: <a class="el" href="classtvm_1_1NameSupply.html#ad6c6c3d3a4698ee50ab2fd2062566820">tvm::NameSupply</a>
+: <a class="el" href="classtvm_1_1NameSupply.html#a4ad1b3236ebe88ea083148702549fdc6">tvm::NameSupply</a>
</li>
<li>NameSupplyNode()
: <a class="el" href="classtvm_1_1NameSupplyNode.html#aba5bb3284648f9f8740eb76500499a12">tvm::NameSupplyNode</a>
diff --git a/docs/reference/api/doxygen/functions_func_t.html b/docs/reference/api/doxygen/functions_func_t.html
index 3acfbead18..d899287bfa 100644
--- a/docs/reference/api/doxygen/functions_func_t.html
+++ b/docs/reference/api/doxygen/functions_func_t.html
@@ -201,7 +201,7 @@ $(function() {
: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a953bca4123b5a758adfdcd65634a5f3b">tvm::tir::ScheduleNode</a>
</li>
<li>Trace()
-: <a class="el" href="classtvm_1_1tir_1_1Trace.html#a8e09abffd0b9b1afac7b832cf16c142d">tvm::tir::Trace</a>
+: <a class="el" href="classtvm_1_1tir_1_1Trace.html#af79bccf1bde25efea387bb1b82dacaa6">tvm::tir::Trace</a>
</li>
<li>Traced()
: <a class="el" href="classtvm_1_1tir_1_1Schedule.html#a15eec0ab3d2caa651f68ad7c88ed31eb">tvm::tir::Schedule</a>
diff --git a/docs/reference/api/doxygen/functions_g.html b/docs/reference/api/doxygen/functions_g.html
index 0afc2fefd1..b789c97513 100644
--- a/docs/reference/api/doxygen/functions_g.html
+++ b/docs/reference/api/doxygen/functions_g.html
@@ -123,7 +123,7 @@ $(function() {
, <a class="el" href="classtvm_1_1TargetKind.html#a11c894b5e17dd940287648261d5efc0d">tvm::TargetKind</a>
, <a class="el" href="classtvm_1_1TargetTag.html#af90a7c152674c7dfe96f6e5aac2f9b25">tvm::TargetTag</a>
, <a class="el" href="classtvm_1_1tir_1_1InstructionKind.html#a6d165507be268ad41aa5221d48062da7">tvm::tir::InstructionKind</a>
-, <a class="el" href="classtvm_1_1tir_1_1LayoutAxis.html#a8980b8d6362947fe93a890e1a97028d4">tvm::tir::LayoutAxis</a>
+, <a class="el" href="classtvm_1_1tir_1_1LayoutAxis.html#a273d3cfc07193e551292450bc2b0e56f">tvm::tir::LayoutAxis</a>
, <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a1d34e09f35c6ca2f179165a041037c4c">tvm::tir::ScheduleNode</a>
</li>
<li>get()
diff --git a/docs/reference/api/doxygen/functions_p.html b/docs/reference/api/doxygen/functions_p.html
index f9a3c9dc23..6a887afdea 100644
--- a/docs/reference/api/doxygen/functions_p.html
+++ b/docs/reference/api/doxygen/functions_p.html
@@ -90,7 +90,7 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1PackedFunc.html#afde7eaa98f6cb12c7e80da16e859c210">tvm::runtime::PackedFunc</a>
</li>
<li>PackedFuncObj()
-: <a class="el" href="classtvm_1_1runtime_1_1PackedFuncObj.html#a063452b7982696b09f35b20993ac3138">tvm::runtime::PackedFuncObj</a>
+: <a class="el" href="classtvm_1_1runtime_1_1PackedFuncObj.html#a8c162670ce34f10ca3dac0b1bbb59292">tvm::runtime::PackedFuncObj</a>
</li>
<li>PackedFuncSubObj()
: <a class="el" href="classtvm_1_1runtime_1_1PackedFuncSubObj.html#a2c5d6759714a3674b36bfd64a9f38992">tvm::runtime::PackedFuncSubObj< TCallable ></a>
@@ -263,7 +263,7 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1PatternConstructor.html#a96adb22c131d7bac1e54a7b646116143">tvm::relay::PatternConstructor</a>
</li>
<li>PatternContext()
-: <a class="el" href="classtvm_1_1relax_1_1PatternContext.html#ae7208ad6046d56d0c7098ca78d85f0b4">tvm::relax::PatternContext</a>
+: <a class="el" href="classtvm_1_1relax_1_1PatternContext.html#ad06ccd048982b7ac3b8230b9a34a75d9">tvm::relax::PatternContext</a>
</li>
<li>patterns
: <a class="el" href="classtvm_1_1relax_1_1PatternSeqNode.html#a1cca092a78997a85dc98359bb95ca1a5">tvm::relax::PatternSeqNode</a>
@@ -280,7 +280,7 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1PatternVar.html#a54c56ad693111a8375e55961bd9b49fa">tvm::relay::PatternVar</a>
</li>
<li>PatternWildcard()
-: <a class="el" href="classtvm_1_1relay_1_1PatternWildcard.html#aab7d1690088beab9987f97cdebd64c0c">tvm::relay::PatternWildcard</a>
+: <a class="el" href="classtvm_1_1relay_1_1PatternWildcard.html#aea56c9cc7113d61aee41cd6569aef9d5">tvm::relay::PatternWildcard</a>
</li>
<li>pc
: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFrame.html#af798dec5a7e9049d6673093d2f3e7dea">tvm::runtime::vm::VMFrame</a>
diff --git a/docs/reference/api/doxygen/functions_t.html b/docs/reference/api/doxygen/functions_t.html
index aa5ffe2f48..8dbbaf4472 100644
--- a/docs/reference/api/doxygen/functions_t.html
+++ b/docs/reference/api/doxygen/functions_t.html
@@ -84,7 +84,7 @@ $(function() {
, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a46879dbe84105fb621a6167f8d73b223">tvm::runtime::vm::Instruction</a>
</li>
<li>Target()
-: <a class="el" href="classtvm_1_1Target.html#a77f3d7cc97d8cfd7172af58b4e784d89">tvm::Target</a>
+: <a class="el" href="classtvm_1_1Target.html#a58a5a1e042e265fe5a6973045226fe1a">tvm::Target</a>
</li>
<li>target
: <a class="el" href="classtvm_1_1VDeviceNode.html#a05a30c026e6448638a34092b3b85d11f">tvm::VDeviceNode</a>
@@ -1776,13 +1776,13 @@ $(function() {
<li>type
: <a class="el" href="structtvm_1_1detail_1_1is__specialized.html#a3ea7783c457d7ddc82100674292724f4">tvm::detail::is_specialized< Type, Container ></a>
, <a class="el" href="structtvm_1_1detail_1_1is__specialized_3_01Container_3_01Args_8_8_8_01_4_00_01Container_01_4.html#a8dee3a1604498d6bc64948f1c0d19dc2">tvm::detail::is_specialized< Container< Args... >, Container ></a>
+, <a class="el" href="structtvm_1_1relax_1_1PairCons.html#aa7fe6fdef3ab68d2f5176485000646b9">tvm::relax::PairCons</a>
</li>
<li>Type
: <a class="el" href="structtvm_1_1relax_1_1PairCons.html#ab64ed8db46c468684a6e00fcb6530647">tvm::relax::PairCons</a>
</li>
<li>type
-: <a class="el" href="structtvm_1_1relax_1_1PairCons.html#aa7fe6fdef3ab68d2f5176485000646b9">tvm::relax::PairCons</a>
-, <a class="el" href="classtvm_1_1relax_1_1TypePatternNode.html#a9d39ad8c323c486e494cea88f2bd60a3">tvm::relax::TypePatternNode</a>
+: <a class="el" href="classtvm_1_1relax_1_1TypePatternNode.html#a9d39ad8c323c486e494cea88f2bd60a3">tvm::relax::TypePatternNode</a>
, <a class="el" href="classtvm_1_1relay_1_1TypePatternNode.html#aab5faa2a58862707b8dc18b59cccac19">tvm::relay::TypePatternNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1memory_1_1Allocator.html#a5690ce0a8e9e25bd8e5568173cc0b1bb">tvm::runtime::memory::Allocator</a>
</li>
diff --git a/docs/reference/api/doxygen/namespacemembers_b.html b/docs/reference/api/doxygen/namespacemembers_b.html
index 29d8dba8f7..189cb38de6 100644
--- a/docs/reference/api/doxygen/namespacemembers_b.html
+++ b/docs/reference/api/doxygen/namespacemembers_b.html
@@ -199,7 +199,7 @@ $(function() {
: <a class="el" href="namespacetvm_1_1tir.html#ac3d21b3e013c52e289180cd6d7d0a420">tvm::tir</a>
</li>
<li>build()
-: <a class="el" href="namespacetvm.html#a018d7138c17ef78300ee256f6d348d00">tvm</a>
+: <a class="el" href="namespacetvm.html#ab5392acd55c76e34323a71a4052f7bb2">tvm</a>
</li>
<li>Build()
: <a class="el" href="namespacetvm_1_1codegen.html#a0d6322c2dda54a66a3b82022f5f3632c">tvm::codegen</a>
diff --git a/docs/reference/api/doxygen/namespacemembers_e.html b/docs/reference/api/doxygen/namespacemembers_e.html
index 768788ad91..9919fe31e8 100644
--- a/docs/reference/api/doxygen/namespacemembers_e.html
+++ b/docs/reference/api/doxygen/namespacemembers_e.html
@@ -106,7 +106,7 @@ $(function() {
: <a class="el" href="namespacetvm_1_1relax.html#aff256c278f6c4493843a3b8fe5703092">tvm::relax</a>
</li>
<li>equal()
-: <a class="el" href="namespacetvm_1_1topi.html#a0e5aecf572e9eea859442ef181df0abc">tvm::topi</a>
+: <a class="el" href="namespacetvm_1_1topi.html#ab3048426a7157ce04d8e14bebd023b12">tvm::topi</a>
</li>
<li>EraseToWellDefined()
: <a class="el" href="namespacetvm_1_1relax.html#ae61c04eb7fcb890934bf2a2f221082d7">tvm::relax</a>
diff --git a/docs/reference/api/doxygen/namespacemembers_func_b.html b/docs/reference/api/doxygen/namespacemembers_func_b.html
index c8ae207a40..92c768e0aa 100644
--- a/docs/reference/api/doxygen/namespacemembers_func_b.html
+++ b/docs/reference/api/doxygen/namespacemembers_func_b.html
@@ -166,7 +166,7 @@ $(function() {
: <a class="el" href="namespacetvm_1_1tir.html#ac3d21b3e013c52e289180cd6d7d0a420">tvm::tir</a>
</li>
<li>build()
-: <a class="el" href="namespacetvm.html#a67dce8ba3396d28be88593081fc291fb">tvm</a>
+: <a class="el" href="namespacetvm.html#a018d7138c17ef78300ee256f6d348d00">tvm</a>
</li>
<li>Build()
: <a class="el" href="namespacetvm_1_1codegen.html#a0d6322c2dda54a66a3b82022f5f3632c">tvm::codegen</a>
diff --git a/docs/reference/api/doxygen/namespacetvm_1_1runtime_1_1relax__vm.html b/docs/reference/api/doxygen/namespacetvm_1_1runtime_1_1relax__vm.html
index a6aa422ff5..9138da8a14 100644
--- a/docs/reference/api/doxygen/namespacetvm_1_1runtime_1_1relax__vm.html
+++ b/docs/reference/api/doxygen/namespacetvm_1_1runtime_1_1relax__vm.html
@@ -124,10 +124,14 @@ Enumerations</h2></td></tr>
}</td></tr>
<tr class="memdesc:a160eebee09cc711d1723aa82bcf73350"><td class="mdescLeft"> </td><td class="mdescRight">Op code used in builtin function MakeShape. <a href="namespacetvm_1_1runtime_1_1relax__vm.html#a160eebee09cc711d1723aa82bcf73350">More...</a><br /></td></tr>
<tr class="separator:a160eebee09cc711d1723aa82bcf73350"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:ad66623de70a1c78143c899a7d6096087"><td class="memItemLeft" align="right" valign="top">enum class  </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">Opcode</a> { <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e">Call</a> = 1U
+<tr class="memitem:ad66623de70a1c78143c899a7d6096087"><td class="memItemLeft" align="right" valign="top">enum class  </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">Opcode</a> { <br />
+  <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e">Call</a> = 1U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd">Ret</a> = 2U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e">Goto</a> = 3U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087a786887572f6ef1c20f2d8177cb2f1639">If</a> = 4U
+, <br />
+  <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830">CallFromRegister</a> = 5U
+<br />
}</td></tr>
<tr class="memdesc:ad66623de70a1c78143c899a7d6096087"><td class="mdescLeft"> </td><td class="mdescRight">An enumeration of Relax's opcodes. <a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">More...</a><br /></td></tr>
<tr class="separator:ad66623de70a1c78143c899a7d6096087"><td class="memSeparator" colspan="2"> </td></tr>
@@ -287,6 +291,7 @@ Enumerations</h2></td></tr>
<tr><td class="fieldname"><a id="ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd"></a>Ret </td><td class="fielddoc"></td></tr>
<tr><td class="fieldname"><a id="ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e"></a>Goto </td><td class="fielddoc"></td></tr>
<tr><td class="fieldname"><a id="ad66623de70a1c78143c899a7d6096087a786887572f6ef1c20f2d8177cb2f1639"></a>If </td><td class="fielddoc"></td></tr>
+<tr><td class="fieldname"><a id="ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830"></a>CallFromRegister </td><td class="fielddoc"></td></tr>
</table>
</div>
diff --git a/docs/reference/api/doxygen/relax__vm_2bytecode_8h.html b/docs/reference/api/doxygen/relax__vm_2bytecode_8h.html
index d77881fc77..19f7ca7dd2 100644
--- a/docs/reference/api/doxygen/relax__vm_2bytecode_8h.html
+++ b/docs/reference/api/doxygen/relax__vm_2bytecode_8h.html
@@ -129,10 +129,14 @@ Typedefs</h2></td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="enum-members"></a>
Enumerations</h2></td></tr>
-<tr class="memitem:ad66623de70a1c78143c899a7d6096087"><td class="memItemLeft" align="right" valign="top">enum class  </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">tvm::runtime::relax_vm::Opcode</a> { <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e">tvm::runtime::relax_vm::Call</a> = 1U
+<tr class="memitem:ad66623de70a1c78143c899a7d6096087"><td class="memItemLeft" align="right" valign="top">enum class  </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">tvm::runtime::relax_vm::Opcode</a> { <br />
+  <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e">tvm::runtime::relax_vm::Call</a> = 1U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd">tvm::runtime::relax_vm::Ret</a> = 2U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e">tvm::runtime::relax_vm::Goto</a> = 3U
, <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087a786887572f6ef1c20f2d8177cb2f1639">tvm::runtime::relax_vm::If</a> = 4U
+, <br />
+  <a class="el" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830">tvm::runtime::relax_vm::CallFromRegister</a> = 5U
+<br />
}</td></tr>
<tr class="memdesc:ad66623de70a1c78143c899a7d6096087"><td class="mdescLeft"> </td><td class="mdescRight">An enumeration of Relax's opcodes. <a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">More...</a><br /></td></tr>
<tr class="separator:ad66623de70a1c78143c899a7d6096087"><td class="memSeparator" colspan="2"> </td></tr>
diff --git a/docs/reference/api/doxygen/relax__vm_2bytecode_8h_source.html b/docs/reference/api/doxygen/relax__vm_2bytecode_8h_source.html
index 24f80b16c6..a4a99f25a5 100644
--- a/docs/reference/api/doxygen/relax__vm_2bytecode_8h_source.html
+++ b/docs/reference/api/doxygen/relax__vm_2bytecode_8h_source.html
@@ -112,104 +112,111 @@ $(function() {
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd">Ret</a> = 2U,</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e">Goto</a> = 3U,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087a786887572f6ef1c20f2d8177cb2f1639">If</a> = 4U,</div>
-<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> };</div>
-<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  </div>
-<div class="line"><a name="l00072"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html"> 72</a></span> <span class="keyword">struct </span><a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> {</div>
-<div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a"> 74</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a">kKindBit</a> = 8;</div>
-<div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a"> 76</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">kValueBit</a> = <span class= [...]
-<div class="line"><a name="l00078"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de"> 78</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de">kValueMask</a> = (<span clas [...]
-<div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87"> 80</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">kValueMaxLimit</a> = (<span [...]
-<div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230"> 82</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">kValueMinLimit</a> = -<a cla [...]
-<div class="line"><a name="l00084"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e"> 84</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e">kBeginSpecialReg</a> = <span [...]
-<div class="line"><a name="l00086"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86"> 86</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86">kVoidRegister</a> = <a class= [...]
-<div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec"> 88</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec">kVMRegister</a> = <a class="c [...]
-<div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6"> 92</a></span>  <span class="keyword">enum class</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> : int { <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef [...]
-<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  </div>
-<div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4"> 94</a></span>  <span class="keyword">friend</span> std::ostream& <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4">operator<<</a>(std::ostream& os, <span class="keyword">const</span> <a class="code" href="structtvm_1_1runtime_1_1relax__v [...]
-<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">switch</span> (kind) {</div>
-<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef6c8ca2b268509e83">ArgKind::kRegister</a>:</div>
-<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  os << <span class="stringliteral">"kRegister"</span>;</div>
-<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">break</span>;</div>
-<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a9d5396915e9c40be7d43f985aa8e5ae0">ArgKind::kImmediate</a>:</div>
-<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  os << <span class="stringliteral">"kImmediate"</span>;</div>
-<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">break</span>;</div>
-<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a41f45af4bfb31067ad8d53e9f08045e3">ArgKind::kConstIdx</a>:</div>
-<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  os << <span class="stringliteral">"kConstIdx"</span>;</div>
-<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">break</span>;</div>
-<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6acb07450c2a8f691a404d4574344af92e">ArgKind::kFuncIdx</a>:</div>
-<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  os << <span class="stringliteral">"kFuncIdx"</span>;</div>
-<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">break</span>;</div>
-<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">default</span>:</div>
-<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  LOG(FATAL) << <span class="stringliteral">"Internal error: "</span></div>
-<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  << <span class="stringliteral">"Invalid ArgKind with integer value "</span> << <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(kind);</div>
-<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  }</div>
-<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">return</span> os;</div>
-<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  }</div>
-<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  </div>
-<div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html"> 118</a></span>  <span class="keyword">class </span><a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> {</div>
-<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">public</span>:</div>
-<div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42"> 121</a></span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>() : data_(<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a>::<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1I [...]
-<div class="line"><a name="l00126"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed"> 126</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed">FromData</a>(<a class="code" href="namespacet [...]
-<div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505"> 132</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505">Register</a>(<a class="code" href="namespacet [...]
-<div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e"> 138</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e">ConstIdx</a>(<a class="code" href="namespacet [...]
-<div class="line"><a name="l00144"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f"> 144</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f">Immediate</a>(int64_t imm_value) { <span clas [...]
-<div class="line"><a name="l00150"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e"> 150</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e">FuncIdx</a>(<a class="code" href="namespacetv [...]
-<div class="line"><a name="l00155"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780"> 155</a></span>  <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>()<span class="keyword"> const </span>{</div>
-<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  uint8_t <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a> = (data_ >> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">kValueBit</a>) & 0xFF;</div>
-<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">return</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">Instruction::ArgKind</a>(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>);</div>
-<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div>
-<div class="line"><a name="l00164"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49"> 164</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>()<span class="keyword"> const </span>{ <span class [...]
-<div class="line"><a name="l00169"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a"> 169</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">data</a>()<span class="keyword"> const </span>{ <span class= [...]
-<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  </div>
-<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">private</span>:</div>
-<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">explicit</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>(<a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">data</a>) : data_( [...]
-<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>(<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>, <a class="code" href="namespacetvm_ [...]
-<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  ICHECK_LE(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>, <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">kValueMaxLimit</a>);</div>
-<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  ICHECK_GE(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>, <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">kValueMinLimit</a>);</div>
-<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  data_ = (<span class="keyword">static_cast<</span><a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a><span class="keyword">></span>(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>) << <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.htm [...]
-<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }</div>
-<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> data_;</div>
-<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  };</div>
-<div class="line"><a name="l00184"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09"> 184</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">Opcode</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09">op</a>;</div>
-<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">union </span>{</div>
-<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keyword">struct </span><span class="comment">/* Call */</span> {</div>
-<div class="line"><a name="l00188"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52"> 188</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52">dst</a>;</div>
-<div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4"> 190</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4">func_idx</a>;</div>
-<div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c"> 192</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c">num_args</a>;</div>
-<div class="line"><a name="l00194"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d"> 194</a></span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a>* <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d">args</a>;</div>
-<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  };</div>
-<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keyword">struct </span><span class="comment">/* Ret */</span> {</div>
-<div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e"> 198</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e">result</a>;</div>
-<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  };</div>
-<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keyword">struct </span><span class="comment">/* Goto */</span> {</div>
-<div class="line"><a name="l00202"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6"> 202</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6">pc_offset</a>;</div>
-<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  };</div>
-<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">struct </span><span class="comment">/* If */</span> {</div>
-<div class="line"><a name="l00206"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5"> 206</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5">cond</a>;</div>
-<div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69"> 208</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69">false_offset</a>;</div>
+<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830">CallFromRegister</a> = 5U,</div>
+<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> };</div>
+<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  </div>
+<div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html"> 73</a></span> <span class="keyword">struct </span><a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> {</div>
+<div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a"> 75</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a">kKindBit</a> = 8;</div>
+<div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a"> 77</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">kValueBit</a> = <span class= [...]
+<div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de"> 79</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de">kValueMask</a> = (<span clas [...]
+<div class="line"><a name="l00081"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87"> 81</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">kValueMaxLimit</a> = (<span [...]
+<div class="line"><a name="l00083"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230"> 83</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">kValueMinLimit</a> = -<a cla [...]
+<div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e"> 85</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e">kBeginSpecialReg</a> = <span [...]
+<div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86"> 87</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86">kVoidRegister</a> = <a class= [...]
+<div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec"> 89</a></span>  <span class="keyword">static</span> constexpr <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec">kVMRegister</a> = <a class="c [...]
+<div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6"> 93</a></span>  <span class="keyword">enum class</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> : int { <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef [...]
+<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  </div>
+<div class="line"><a name="l00095"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4"> 95</a></span>  <span class="keyword">friend</span> std::ostream& <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4">operator<<</a>(std::ostream& os, <span class="keyword">const</span> <a class="code" href="structtvm_1_1runtime_1_1relax__v [...]
+<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordflow">switch</span> (kind) {</div>
+<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef6c8ca2b268509e83">ArgKind::kRegister</a>:</div>
+<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  os << <span class="stringliteral">"kRegister"</span>;</div>
+<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">break</span>;</div>
+<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a9d5396915e9c40be7d43f985aa8e5ae0">ArgKind::kImmediate</a>:</div>
+<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  os << <span class="stringliteral">"kImmediate"</span>;</div>
+<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">break</span>;</div>
+<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a41f45af4bfb31067ad8d53e9f08045e3">ArgKind::kConstIdx</a>:</div>
+<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  os << <span class="stringliteral">"kConstIdx"</span>;</div>
+<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">break</span>;</div>
+<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">case</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6acb07450c2a8f691a404d4574344af92e">ArgKind::kFuncIdx</a>:</div>
+<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  os << <span class="stringliteral">"kFuncIdx"</span>;</div>
+<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">break</span>;</div>
+<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">default</span>:</div>
+<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  LOG(FATAL) << <span class="stringliteral">"Internal error: "</span></div>
+<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  << <span class="stringliteral">"Invalid ArgKind with integer value "</span> << <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(kind);</div>
+<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</div>
+<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">return</span> os;</div>
+<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div>
+<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  </div>
+<div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html"> 119</a></span>  <span class="keyword">class </span><a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> {</div>
+<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">public</span>:</div>
+<div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42"> 122</a></span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>() : data_(<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a>::<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1I [...]
+<div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed"> 127</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed">FromData</a>(<a class="code" href="namespacet [...]
+<div class="line"><a name="l00133"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505"> 133</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505">Register</a>(<a class="code" href="namespacet [...]
+<div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e"> 139</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e">ConstIdx</a>(<a class="code" href="namespacet [...]
+<div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f"> 145</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f">Immediate</a>(int64_t imm_value) { <span clas [...]
+<div class="line"><a name="l00151"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e"> 151</a></span>  <span class="keyword">static</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e">FuncIdx</a>(<a class="code" href="namespacetv [...]
+<div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780"> 156</a></span>  <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>()<span class="keyword"> const </span>{</div>
+<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  uint8_t <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a> = (data_ >> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">kValueBit</a>) & 0xFF;</div>
+<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordflow">return</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">Instruction::ArgKind</a>(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>);</div>
+<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</div>
+<div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49"> 165</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>()<span class="keyword"> const </span>{ <span class [...]
+<div class="line"><a name="l00170"></a><span class="lineno"><a class="line" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a"> 170</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">data</a>()<span class="keyword"> const </span>{ <span class= [...]
+<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  </div>
+<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">private</span>:</div>
+<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keyword">explicit</span> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>(<a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">data</a>) : data_( [...]
+<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">Arg</a>(<a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">ArgKind</a> <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>, <a class="code" href="namespacetvm_ [...]
+<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  ICHECK_LE(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>, <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">kValueMaxLimit</a>);</div>
+<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  ICHECK_GE(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">value</a>, <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">kValueMinLimit</a>);</div>
+<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  data_ = (<span class="keyword">static_cast<</span><a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a><span class="keyword">></span>(<a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">kind</a>) << <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.htm [...]
+<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  }</div>
+<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">ExecWord</a> data_;</div>
+<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  };</div>
+<div class="line"><a name="l00185"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09"> 185</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087">Opcode</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09">op</a>;</div>
+<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keyword">union </span>{</div>
+<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keyword">struct </span><span class="comment">/* Call, CallFromRegister */</span> {</div>
+<div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52"> 189</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52">dst</a>;</div>
+<div class="line"><a name="l00196"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4"> 196</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4">func_idx</a>;</div>
+<div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c"> 198</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c">num_args</a>;</div>
+<div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d"> 200</a></span>  <a class="code" href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">Arg</a>* <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d">args</a>;</div>
+<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  };</div>
+<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keyword">struct </span><span class="comment">/* Ret */</span> {</div>
+<div class="line"><a name="l00204"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e"> 204</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e">result</a>;</div>
+<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  };</div>
+<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keyword">struct </span><span class="comment">/* Goto */</span> {</div>
+<div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6"> 208</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6">pc_offset</a>;</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  };</div>
-<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  };</div>
-<div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac5ae8676419e1d09a1337e690502c431"> 219</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac5ae8676419e1d09a1337e690502c431">Call</a>(<a class="code" href="namespacetvm_1_1runtime_1_ [...]
-<div class="line"><a name="l00225"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af90b3fe3d8f2fafcba237296a3b26c68"> 225</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af90b3fe3d8f2fafcba237296a3b26c68">Ret</a>(<a class="code" href="namespacetvm_1_1runtime_1_1 [...]
-<div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16ae2bb2f9b89af6112523c2357ab662"> 231</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16ae2bb2f9b89af6112523c2357ab662">Goto</a>(<a class="code" href="namespacetvm_1_1runtime_1_ [...]
-<div class="line"><a name="l00238"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af94b8389ff91d2befbe1b60709fa9f5c"> 238</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af94b8389ff91d2befbe1b60709fa9f5c">If</a>(<a class="code" href="namespacetvm_1_1runtime_1_1r [...]
-<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> };</div>
-<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  </div>
-<div class="line"><a name="l00241"></a><span class="lineno"> 241</span> } <span class="comment">// namespace relax_vm</span></div>
-<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> } <span class="comment">// namespace runtime</span></div>
-<div class="line"><a name="l00243"></a><span class="lineno"> 243</span> } <span class="comment">// namespace tvm</span></div>
-<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  </div>
-<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="preprocessor">#endif </span><span class="comment">// TVM_RUNTIME_RELAX_VM_BYTECODE_H_</span></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">tvm::runtime::relax_vm::Instruction::Arg</a></div><div class="ttdoc">The auxiliary data structure for instruction argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:118</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a12f0b8a40de07e9f6bce34825cfe8505"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505">tvm::runtime::relax_vm::Instruction::Arg::Register</a></div><div class="ttdeci">static Arg Register(RegName reg)</div><div class="ttdoc">construct a register Arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:132</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a16f1ed70c4a48f85d377d17f9f5c0780"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">tvm::runtime::relax_vm::Instruction::Arg::kind</a></div><div class="ttdeci">ArgKind kind() const</div><div class="ttdoc">Get the kind of argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:155</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a1bfc14ff424a1d4e62dbf3a142d4165e"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e">tvm::runtime::relax_vm::Instruction::Arg::FuncIdx</a></div><div class="ttdeci">static Arg FuncIdx(Index index)</div><div class="ttdoc">construct a FuncIdx arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:150</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a2a43f61daee2fedd63647a90b4b7bf9a"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">tvm::runtime::relax_vm::Instruction::Arg::data</a></div><div class="ttdeci">ExecWord data() const</div><div class="ttdoc">Get the raw data repr of the arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:169</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a37f9d9015bf3af9875b43ca260ead9ed"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed">tvm::runtime::relax_vm::Instruction::Arg::FromData</a></div><div class="ttdeci">static Arg FromData(ExecWord data)</div><div class="ttdoc">construct Arg from data.</div><div class="ttdef"><b>Definition:</b> bytecode.h:126</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a407acb6b4aa72a5b704fb4d396dd091f"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f">tvm::runtime::relax_vm::Instruction::Arg::Immediate</a></div><div class="ttdeci">static Arg Immediate(int64_t imm_value)</div><div class="ttdoc">construct a immediate arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:144</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a5a36ed4b3116f12e229fca54845f9f49"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">tvm::runtime::relax_vm::Instruction::Arg::value</a></div><div class="ttdeci">ExecWord value() const</div><div class="ttdoc">Get the value of argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:164</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_ae9ed722e3b8a6468814d6580f96b9f42"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">tvm::runtime::relax_vm::Instruction::Arg::Arg</a></div><div class="ttdeci">Arg()</div><div class="ttdoc">Construct a void argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:121</div></div>
-<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_aef0086a9684f47fc1da940be5407450e"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e">tvm::runtime::relax_vm::Instruction::Arg::ConstIdx</a></div><div class="ttdeci">static Arg ConstIdx(Index index)</div><div class="ttdoc">construct a ConstIdx arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:138</div></div>
+<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">struct </span><span class="comment">/* If */</span> {</div>
+<div class="line"><a name="l00212"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5"> 212</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">RegName</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5">cond</a>;</div>
+<div class="line"><a name="l00214"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69"> 214</a></span>  <a class="code" href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">Index</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69">false_offset</a>;</div>
+<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  };</div>
+<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  };</div>
+<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  </div>
+<div class="line"><a name="l00227"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac5ae8676419e1d09a1337e690502c431"> 227</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac5ae8676419e1d09a1337e690502c431">Call</a>(<a class="code" href="namespacetvm_1_1runtime_1_ [...]
+<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  </div>
+<div class="line"><a name="l00238"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac2fd6c84fd50b55f7c8afd0edeb5b0ec"> 238</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac2fd6c84fd50b55f7c8afd0edeb5b0ec">CallFromRegister</a>(<a class="code" href="namespacetvm_1 [...]
+<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  </div>
+<div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af90b3fe3d8f2fafcba237296a3b26c68"> 245</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af90b3fe3d8f2fafcba237296a3b26c68">Ret</a>(<a class="code" href="namespacetvm_1_1runtime_1_1 [...]
+<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  </div>
+<div class="line"><a name="l00252"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16ae2bb2f9b89af6112523c2357ab662"> 252</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16ae2bb2f9b89af6112523c2357ab662">Goto</a>(<a class="code" href="namespacetvm_1_1runtime_1_ [...]
+<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  </div>
+<div class="line"><a name="l00260"></a><span class="lineno"><a class="line" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af94b8389ff91d2befbe1b60709fa9f5c"> 260</a></span>  <span class="keyword">static</span> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">Instruction</a> <a class="code" href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af94b8389ff91d2befbe1b60709fa9f5c">If</a>(<a class="code" href="namespacetvm_1_1runtime_1_1r [...]
+<div class="line"><a name="l00261"></a><span class="lineno"> 261</span> };</div>
+<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  </div>
+<div class="line"><a name="l00263"></a><span class="lineno"> 263</span> } <span class="comment">// namespace relax_vm</span></div>
+<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> } <span class="comment">// namespace runtime</span></div>
+<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> } <span class="comment">// namespace tvm</span></div>
+<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  </div>
+<div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="preprocessor">#endif </span><span class="comment">// TVM_RUNTIME_RELAX_VM_BYTECODE_H_</span></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html">tvm::runtime::relax_vm::Instruction::Arg</a></div><div class="ttdoc">The auxiliary data structure for instruction argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:119</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a12f0b8a40de07e9f6bce34825cfe8505"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a12f0b8a40de07e9f6bce34825cfe8505">tvm::runtime::relax_vm::Instruction::Arg::Register</a></div><div class="ttdeci">static Arg Register(RegName reg)</div><div class="ttdoc">construct a register Arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:133</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a16f1ed70c4a48f85d377d17f9f5c0780"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a16f1ed70c4a48f85d377d17f9f5c0780">tvm::runtime::relax_vm::Instruction::Arg::kind</a></div><div class="ttdeci">ArgKind kind() const</div><div class="ttdoc">Get the kind of argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:156</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a1bfc14ff424a1d4e62dbf3a142d4165e"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a1bfc14ff424a1d4e62dbf3a142d4165e">tvm::runtime::relax_vm::Instruction::Arg::FuncIdx</a></div><div class="ttdeci">static Arg FuncIdx(Index index)</div><div class="ttdoc">construct a FuncIdx arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:151</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a2a43f61daee2fedd63647a90b4b7bf9a"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a2a43f61daee2fedd63647a90b4b7bf9a">tvm::runtime::relax_vm::Instruction::Arg::data</a></div><div class="ttdeci">ExecWord data() const</div><div class="ttdoc">Get the raw data repr of the arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:170</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a37f9d9015bf3af9875b43ca260ead9ed"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a37f9d9015bf3af9875b43ca260ead9ed">tvm::runtime::relax_vm::Instruction::Arg::FromData</a></div><div class="ttdeci">static Arg FromData(ExecWord data)</div><div class="ttdoc">construct Arg from data.</div><div class="ttdef"><b>Definition:</b> bytecode.h:127</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a407acb6b4aa72a5b704fb4d396dd091f"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a407acb6b4aa72a5b704fb4d396dd091f">tvm::runtime::relax_vm::Instruction::Arg::Immediate</a></div><div class="ttdeci">static Arg Immediate(int64_t imm_value)</div><div class="ttdoc">construct a immediate arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:145</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_a5a36ed4b3116f12e229fca54845f9f49"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#a5a36ed4b3116f12e229fca54845f9f49">tvm::runtime::relax_vm::Instruction::Arg::value</a></div><div class="ttdeci">ExecWord value() const</div><div class="ttdoc">Get the value of argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:165</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_ae9ed722e3b8a6468814d6580f96b9f42"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#ae9ed722e3b8a6468814d6580f96b9f42">tvm::runtime::relax_vm::Instruction::Arg::Arg</a></div><div class="ttdeci">Arg()</div><div class="ttdoc">Construct a void argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:122</div></div>
+<div class="ttc" id="aclasstvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg_html_aef0086a9684f47fc1da940be5407450e"><div class="ttname"><a href="classtvm_1_1runtime_1_1relax__vm_1_1Instruction_1_1Arg.html#aef0086a9684f47fc1da940be5407450e">tvm::runtime::relax_vm::Instruction::Arg::ConstIdx</a></div><div class="ttdeci">static Arg ConstIdx(Index index)</div><div class="ttdoc">construct a ConstIdx arg.</div><div class="ttdef"><b>Definition:</b> bytecode.h:139</div></div>
<div class="ttc" id="adata__type_8h_html"><div class="ttname"><a href="data__type_8h.html">data_type.h</a></div></div>
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_a4560c3b2c804d776496f2b1943bba8ec"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#a4560c3b2c804d776496f2b1943bba8ec">tvm::runtime::relax_vm::RegName</a></div><div class="ttdeci">ExecWord RegName</div><div class="ttdoc">A register name.</div><div class="ttdef"><b>Definition:</b> bytecode.h:43</div></div>
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_a662b9d8203cd114bbec14cc659a3257e"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#a662b9d8203cd114bbec14cc659a3257e">tvm::runtime::relax_vm::Index</a></div><div class="ttdeci">ExecWord Index</div><div class="ttdoc">An alias for the integer type used ubiquitously in the VM.</div><div class="ttdef"><b>Definition:</b> bytecode.h:48</div></div>
@@ -218,35 +225,37 @@ $(function() {
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aa4228a09dd66155de8e93a39245768bd">tvm::runtime::relax_vm::Opcode::Ret</a></div><div class="ttdeci">@ Ret</div></div>
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087aae8fae3d74fdc80ef40995c3c6ca152e">tvm::runtime::relax_vm::Opcode::Goto</a></div><div class="ttdeci">@ Goto</div></div>
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac3755e61202abd74da5885d2e9c9160e">tvm::runtime::relax_vm::Opcode::Call</a></div><div class="ttdeci">@ Call</div></div>
+<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#ad66623de70a1c78143c899a7d6096087ac4fec197f8c40da24606b141397a2830">tvm::runtime::relax_vm::Opcode::CallFromRegister</a></div><div class="ttdeci">@ CallFromRegister</div></div>
<div class="ttc" id="anamespacetvm_1_1runtime_1_1relax__vm_html_af2af16397df7403bc45e610860b91434"><div class="ttname"><a href="namespacetvm_1_1runtime_1_1relax__vm.html#af2af16397df7403bc45e610860b91434">tvm::runtime::relax_vm::ExecWord</a></div><div class="ttdeci">int64_t ExecWord</div><div class="ttdoc">The storage type for the bytecode in the VM.</div><div class="ttdef"><b>Definition:</b> bytecode.h:40</div></div>
<div class="ttc" id="anamespacetvm_html"><div class="ttname"><a href="namespacetvm.html">tvm</a></div><div class="ttdoc">runtime implementation for LibTorch/TorchScript.</div><div class="ttdef"><b>Definition:</b> analyzer.h:36</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">tvm::runtime::relax_vm::Instruction</a></div><div class="ttdoc">A single virtual machine instruction.</div><div class="ttdef"><b>Definition:</b> bytecode.h:72</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a023a7a9dc4d344941edbdfbb427f19e5"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5">tvm::runtime::relax_vm::Instruction::cond</a></div><div class="ttdeci">RegName cond</div><div class="ttdoc">The register containing the cond value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:206</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a0bca4d5544e9b881abfde32f61734e09"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09">tvm::runtime::relax_vm::Instruction::op</a></div><div class="ttdeci">Opcode op</div><div class="ttdoc">The instruction opcode.</div><div class="ttdef"><b>Definition:</b> bytecode.h:184</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a154b0c041367bdb03e8c96e9e0e6f230"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">tvm::runtime::relax_vm::Instruction::kValueMinLimit</a></div><div class="ttdeci">static constexpr ExecWord kValueMinLimit</div><div class="ttdoc">Minimum possible value, remove 1 slot to keep things symmetric.</div><div class="ttdef"><b>Definition:</b> bytecode.h [...]
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a166e16e66086ae40de60fc266724daec"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec">tvm::runtime::relax_vm::Instruction::kVMRegister</a></div><div class="ttdeci">static constexpr RegName kVMRegister</div><div class="ttdoc">Random magic number that represents the VM context.</div><div class="ttdef"><b>Definition:</b> bytecode.h:88</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">tvm::runtime::relax_vm::Instruction</a></div><div class="ttdoc">A single virtual machine instruction.</div><div class="ttdef"><b>Definition:</b> bytecode.h:73</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a023a7a9dc4d344941edbdfbb427f19e5"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a023a7a9dc4d344941edbdfbb427f19e5">tvm::runtime::relax_vm::Instruction::cond</a></div><div class="ttdeci">RegName cond</div><div class="ttdoc">The register containing the cond value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:212</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a0bca4d5544e9b881abfde32f61734e09"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a0bca4d5544e9b881abfde32f61734e09">tvm::runtime::relax_vm::Instruction::op</a></div><div class="ttdeci">Opcode op</div><div class="ttdoc">The instruction opcode.</div><div class="ttdef"><b>Definition:</b> bytecode.h:185</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a154b0c041367bdb03e8c96e9e0e6f230"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a154b0c041367bdb03e8c96e9e0e6f230">tvm::runtime::relax_vm::Instruction::kValueMinLimit</a></div><div class="ttdeci">static constexpr ExecWord kValueMinLimit</div><div class="ttdoc">Minimum possible value, remove 1 slot to keep things symmetric.</div><div class="ttdef"><b>Definition:</b> bytecode.h [...]
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a166e16e66086ae40de60fc266724daec"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a166e16e66086ae40de60fc266724daec">tvm::runtime::relax_vm::Instruction::kVMRegister</a></div><div class="ttdeci">static constexpr RegName kVMRegister</div><div class="ttdoc">Random magic number that represents the VM context.</div><div class="ttdef"><b>Definition:</b> bytecode.h:89</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a16ae2bb2f9b89af6112523c2357ab662"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16ae2bb2f9b89af6112523c2357ab662">tvm::runtime::relax_vm::Instruction::Goto</a></div><div class="ttdeci">static Instruction Goto(RegName pc_offset)</div><div class="ttdoc">Construct a goto instruction.</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a16b5191e31348e3670b69b790688077a"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">tvm::runtime::relax_vm::Instruction::kValueBit</a></div><div class="ttdeci">static constexpr ExecWord kValueBit</div><div class="ttdoc">The number of bit for storing value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:76</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a18ce2faf2a0ee70003228368c041ea69"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69">tvm::runtime::relax_vm::Instruction::false_offset</a></div><div class="ttdeci">Index false_offset</div><div class="ttdoc">The program counter offset for the false branch.</div><div class="ttdef"><b>Definition:</b> bytecode.h:208</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a1b985430a35bd5dddb326cc1ea153f2d"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d">tvm::runtime::relax_vm::Instruction::args</a></div><div class="ttdeci">Arg * args</div><div class="ttdoc">The arguments of the packed function.</div><div class="ttdef"><b>Definition:</b> bytecode.h:194</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a474312edc1446aa274b3e64d1cb37b52"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52">tvm::runtime::relax_vm::Instruction::dst</a></div><div class="ttdeci">RegName dst</div><div class="ttdoc">The destination register.</div><div class="ttdef"><b>Definition:</b> bytecode.h:188</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a6abf44e125902a836a5417a0d10c14de"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de">tvm::runtime::relax_vm::Instruction::kValueMask</a></div><div class="ttdeci">static constexpr ExecWord kValueMask</div><div class="ttdoc">The bit mask of the value part.</div><div class="ttdef"><b>Definition:</b> bytecode.h:78</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aa3236d92c4a140acec567ed3821cb3f4"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4">tvm::runtime::relax_vm::Instruction::operator<<</a></div><div class="ttdeci">friend std::ostream & operator<<(std::ostream &os, const ArgKind &kind)</div><div class="ttdef"><b>Definition:</b> bytecode.h:94</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aabbaa135169678a9bfb3131e25622d86"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86">tvm::runtime::relax_vm::Instruction::kVoidRegister</a></div><div class="ttdeci">static constexpr RegName kVoidRegister</div><div class="ttdoc">Random magic number that represents void argument, indicate null value.</div><div class="ttdef"><b>Definition:</b> bytec [...]
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ab12e0decb84c1d3227799f758c6bfc0a"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a">tvm::runtime::relax_vm::Instruction::kKindBit</a></div><div class="ttdeci">static constexpr ExecWord kKindBit</div><div class="ttdoc">The number of bit for storing value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:74</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ab3bf6aac84ca4db099d236d051af6b87"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">tvm::runtime::relax_vm::Instruction::kValueMaxLimit</a></div><div class="ttdeci">static constexpr ExecWord kValueMaxLimit</div><div class="ttdoc">Maximum possible value, use 1 bit for sign.</div><div class="ttdef"><b>Definition:</b> bytecode.h:80</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac42bc936e81c8cd235760794b78e5b2e"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e">tvm::runtime::relax_vm::Instruction::kBeginSpecialReg</a></div><div class="ttdeci">static constexpr RegName kBeginSpecialReg</div><div class="ttdoc">Beginning of special register section.</div><div class="ttdef"><b>Definition:</b> bytecode.h:84</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a16b5191e31348e3670b69b790688077a"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a16b5191e31348e3670b69b790688077a">tvm::runtime::relax_vm::Instruction::kValueBit</a></div><div class="ttdeci">static constexpr ExecWord kValueBit</div><div class="ttdoc">The number of bit for storing value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:77</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a18ce2faf2a0ee70003228368c041ea69"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a18ce2faf2a0ee70003228368c041ea69">tvm::runtime::relax_vm::Instruction::false_offset</a></div><div class="ttdeci">Index false_offset</div><div class="ttdoc">The program counter offset for the false branch.</div><div class="ttdef"><b>Definition:</b> bytecode.h:214</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a1b985430a35bd5dddb326cc1ea153f2d"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a1b985430a35bd5dddb326cc1ea153f2d">tvm::runtime::relax_vm::Instruction::args</a></div><div class="ttdeci">Arg * args</div><div class="ttdoc">The arguments of the packed function.</div><div class="ttdef"><b>Definition:</b> bytecode.h:200</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a474312edc1446aa274b3e64d1cb37b52"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a474312edc1446aa274b3e64d1cb37b52">tvm::runtime::relax_vm::Instruction::dst</a></div><div class="ttdeci">RegName dst</div><div class="ttdoc">The destination register.</div><div class="ttdef"><b>Definition:</b> bytecode.h:189</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_a6abf44e125902a836a5417a0d10c14de"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#a6abf44e125902a836a5417a0d10c14de">tvm::runtime::relax_vm::Instruction::kValueMask</a></div><div class="ttdeci">static constexpr ExecWord kValueMask</div><div class="ttdoc">The bit mask of the value part.</div><div class="ttdef"><b>Definition:</b> bytecode.h:79</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aa3236d92c4a140acec567ed3821cb3f4"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aa3236d92c4a140acec567ed3821cb3f4">tvm::runtime::relax_vm::Instruction::operator<<</a></div><div class="ttdeci">friend std::ostream & operator<<(std::ostream &os, const ArgKind &kind)</div><div class="ttdef"><b>Definition:</b> bytecode.h:95</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aabbaa135169678a9bfb3131e25622d86"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aabbaa135169678a9bfb3131e25622d86">tvm::runtime::relax_vm::Instruction::kVoidRegister</a></div><div class="ttdeci">static constexpr RegName kVoidRegister</div><div class="ttdoc">Random magic number that represents void argument, indicate null value.</div><div class="ttdef"><b>Definition:</b> bytec [...]
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ab12e0decb84c1d3227799f758c6bfc0a"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab12e0decb84c1d3227799f758c6bfc0a">tvm::runtime::relax_vm::Instruction::kKindBit</a></div><div class="ttdeci">static constexpr ExecWord kKindBit</div><div class="ttdoc">The number of bit for storing value.</div><div class="ttdef"><b>Definition:</b> bytecode.h:75</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ab3bf6aac84ca4db099d236d051af6b87"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ab3bf6aac84ca4db099d236d051af6b87">tvm::runtime::relax_vm::Instruction::kValueMaxLimit</a></div><div class="ttdeci">static constexpr ExecWord kValueMaxLimit</div><div class="ttdoc">Maximum possible value, use 1 bit for sign.</div><div class="ttdef"><b>Definition:</b> bytecode.h:81</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac2fd6c84fd50b55f7c8afd0edeb5b0ec"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac2fd6c84fd50b55f7c8afd0edeb5b0ec">tvm::runtime::relax_vm::Instruction::CallFromRegister</a></div><div class="ttdeci">static Instruction CallFromRegister(Index func_idx, Index num_args, Arg *args, RegName dst)</div><div class="ttdoc">Construct a Call instruction.</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac42bc936e81c8cd235760794b78e5b2e"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac42bc936e81c8cd235760794b78e5b2e">tvm::runtime::relax_vm::Instruction::kBeginSpecialReg</a></div><div class="ttdeci">static constexpr RegName kBeginSpecialReg</div><div class="ttdoc">Beginning of special register section.</div><div class="ttdef"><b>Definition:</b> bytecode.h:85</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac5ae8676419e1d09a1337e690502c431"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac5ae8676419e1d09a1337e690502c431">tvm::runtime::relax_vm::Instruction::Call</a></div><div class="ttdeci">static Instruction Call(Index func_idx, Index num_args, Arg *args, RegName dst)</div><div class="ttdoc">Construct a Call instruction.</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac6f16daf6e9882d7d77fbb01b66db8d4"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4">tvm::runtime::relax_vm::Instruction::func_idx</a></div><div class="ttdeci">Index func_idx</div><div class="ttdoc">The index into the packed function table.</div><div class="ttdef"><b>Definition:</b> bytecode.h:190</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac816b9d31aad8e352e146f55f77f017e"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e">tvm::runtime::relax_vm::Instruction::result</a></div><div class="ttdeci">RegName result</div><div class="ttdoc">The return result.</div><div class="ttdef"><b>Definition:</b> bytecode.h:198</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ad01109b8e710fb8988eac9ed4bbed9e6"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">tvm::runtime::relax_vm::Instruction::ArgKind</a></div><div class="ttdeci">ArgKind</div><div class="ttdoc">The kind of instruction's argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:92</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac6f16daf6e9882d7d77fbb01b66db8d4"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac6f16daf6e9882d7d77fbb01b66db8d4">tvm::runtime::relax_vm::Instruction::func_idx</a></div><div class="ttdeci">Index func_idx</div><div class="ttdoc">The index of the function.</div><div class="ttdef"><b>Definition:</b> bytecode.h:196</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ac816b9d31aad8e352e146f55f77f017e"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ac816b9d31aad8e352e146f55f77f017e">tvm::runtime::relax_vm::Instruction::result</a></div><div class="ttdeci">RegName result</div><div class="ttdoc">The return result.</div><div class="ttdef"><b>Definition:</b> bytecode.h:204</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ad01109b8e710fb8988eac9ed4bbed9e6"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6">tvm::runtime::relax_vm::Instruction::ArgKind</a></div><div class="ttdeci">ArgKind</div><div class="ttdoc">The kind of instruction's argument.</div><div class="ttdef"><b>Definition:</b> bytecode.h:93</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef6c8ca2b268509e83"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#ad01109b8e710fb8988eac9ed4bbed9e6a31b4285f9ab9bdef6c8ca2b268509e83">tvm::runtime::relax_vm::Instruction::ArgKind::kRegister</a></div><div class="ttdeci">@ kRegister</div></div>
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-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aedb4eea5107320bc240afd3cfdf9e29c"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c">tvm::runtime::relax_vm::Instruction::num_args</a></div><div class="ttdeci">Index num_args</div><div class="ttdoc">The number of arguments to the packed function.</div><div class="ttdef"><b>Definition:</b> bytecode.h:192</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_aedb4eea5107320bc240afd3cfdf9e29c"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#aedb4eea5107320bc240afd3cfdf9e29c">tvm::runtime::relax_vm::Instruction::num_args</a></div><div class="ttdeci">Index num_args</div><div class="ttdoc">The number of arguments to the packed function.</div><div class="ttdef"><b>Definition:</b> bytecode.h:198</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_af90b3fe3d8f2fafcba237296a3b26c68"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af90b3fe3d8f2fafcba237296a3b26c68">tvm::runtime::relax_vm::Instruction::Ret</a></div><div class="ttdeci">static Instruction Ret(RegName result)</div><div class="ttdoc">Construct a return instruction.</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_af9386954431e7fa345882e5da55dddc6"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6">tvm::runtime::relax_vm::Instruction::pc_offset</a></div><div class="ttdeci">Index pc_offset</div><div class="ttdoc">The jump offset.</div><div class="ttdef"><b>Definition:</b> bytecode.h:202</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_af9386954431e7fa345882e5da55dddc6"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af9386954431e7fa345882e5da55dddc6">tvm::runtime::relax_vm::Instruction::pc_offset</a></div><div class="ttdeci">Index pc_offset</div><div class="ttdoc">The jump offset.</div><div class="ttdef"><b>Definition:</b> bytecode.h:208</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html_af94b8389ff91d2befbe1b60709fa9f5c"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html#af94b8389ff91d2befbe1b60709fa9f5c">tvm::runtime::relax_vm::Instruction::If</a></div><div class="ttdeci">static Instruction If(RegName cond, Index false_offset)</div><div class="ttdoc">Construct an If instruction.</div></div>
</div><!-- fragment --></div><!-- contents -->
<!-- start footer part -->
diff --git a/docs/reference/api/doxygen/relax__vm_2executable_8h_source.html b/docs/reference/api/doxygen/relax__vm_2executable_8h_source.html
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--- a/docs/reference/api/doxygen/relax__vm_2executable_8h_source.html
+++ b/docs/reference/api/doxygen/relax__vm_2executable_8h_source.html
@@ -225,7 +225,7 @@ $(function() {
<div class="ttc" id="aobject_8h_html"><div class="ttname"><a href="object_8h.html">object.h</a></div><div class="ttdoc">A managed object in the TVM runtime.</div></div>
<div class="ttc" id="apacked__func_8h_html"><div class="ttname"><a href="packed__func_8h.html">packed_func.h</a></div><div class="ttdoc">Type-erased function used across TVM API.</div></div>
<div class="ttc" id="aregistry_8h_html"><div class="ttname"><a href="registry_8h.html">registry.h</a></div><div class="ttdoc">This file defines the TVM global function registry.</div></div>
-<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">tvm::runtime::relax_vm::Instruction</a></div><div class="ttdoc">A single virtual machine instruction.</div><div class="ttdef"><b>Definition:</b> bytecode.h:72</div></div>
+<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1Instruction_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1Instruction.html">tvm::runtime::relax_vm::Instruction</a></div><div class="ttdoc">A single virtual machine instruction.</div><div class="ttdef"><b>Definition:</b> bytecode.h:73</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo_html"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo.html">tvm::runtime::relax_vm::VMFuncInfo</a></div><div class="ttdoc">Information entry in executable function table.</div><div class="ttdef"><b>Definition:</b> executable.h:53</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo_html_a0b53a2d0a9d0662fd45bc0a30e0f6289"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo.html#a0b53a2d0a9d0662fd45bc0a30e0f6289">tvm::runtime::relax_vm::VMFuncInfo::Load</a></div><div class="ttdeci">bool Load(dmlc::Stream *reader)</div></div>
<div class="ttc" id="astructtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo_html_a20095c297b45a5dfc0e1a4bac5dbb45d"><div class="ttname"><a href="structtvm_1_1runtime_1_1relax__vm_1_1VMFuncInfo.html#a20095c297b45a5dfc0e1a4bac5dbb45d">tvm::runtime::relax_vm::VMFuncInfo::kind</a></div><div class="ttdeci">FuncKind kind</div><div class="ttdoc">The kind of function.</div><div class="ttdef"><b>Definition:</b> executable.h:64</div></div>
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