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Posted to commits@tvm.apache.org by tq...@apache.org on 2022/06/17 20:34:35 UTC
[tvm-site] branch asf-site updated: deploying docs (apache/tvm@0fdc0eab5199d1b6549d2b2f94c83d86d5545e81)
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 ae238e131 deploying docs (apache/tvm@0fdc0eab5199d1b6549d2b2f94c83d86d5545e81)
ae238e131 is described below
commit ae238e1319722e171e239211f948c73234007095
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Fri Jun 17 20:34:28 2022 +0000
deploying docs (apache/tvm@0fdc0eab5199d1b6549d2b2f94c83d86d5545e81)
---
.../how_to/compile_models/from_darknet.rst.txt | 5 -
.../how_to/compile_models/from_mxnet.rst.txt | 2 +-
.../how_to/compile_models/from_oneflow.rst.txt | 2 +-
.../how_to/compile_models/from_paddle.rst.txt | 2 +-
.../how_to/compile_models/from_pytorch.rst.txt | 2 +-
.../how_to/compile_models/from_tensorflow.rst.txt | 2 +-
.../compile_models/sg_execution_times.rst.txt | 22 +-
.../deploy_models/deploy_model_on_android.rst.txt | 2 +-
.../deploy_object_detection_pytorch.rst.txt | 4 +-
.../deploy_models/deploy_prequantized.rst.txt | 6 +-
.../deploy_prequantized_tflite.rst.txt | 4 +-
.../how_to/deploy_models/deploy_quantized.rst.txt | 2 +-
.../deploy_models/deploy_ssd_gluoncv.rst.txt | 4 +-
.../deploy_models/sg_execution_times.rst.txt | 16 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 2 +-
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.../how_to/extend_tvm/use_pass_instrument.rst.txt | 16 +-
.../optimize_operators/opt_conv_cuda.rst.txt | 2 +-
.../optimize_operators/opt_conv_tensorcore.rst.txt | 2 +-
.../how_to/optimize_operators/opt_gemm.rst.txt | 16 +-
.../optimize_operators/sg_execution_times.rst.txt | 8 +-
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.../tune_conv2d_layer_cuda.rst.txt | 4 +-
.../tune_network_cuda.rst.txt | 2 +-
.../tune_network_x86.rst.txt | 4 +-
.../tune_sparse_x86.rst.txt | 86 ++----
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.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 34 +--
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docs/how_to/compile_models/from_oneflow.html | 75 ++---
docs/how_to/compile_models/from_paddle.html | 2 +-
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271 files changed, 2702 insertions(+), 2596 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 a2352ca82..095f910b7 100644
--- a/docs/_sources/how_to/compile_models/from_darknet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_darknet.rst.txt
@@ -314,11 +314,6 @@ The process is no different from other examples.
-.. rst-class:: sphx-glr-timing
-
- **Total running time of the script:** ( 1 minutes 0.533 seconds)
-
-
.. _sphx_glr_download_how_to_compile_models_from_darknet.py:
.. only:: html
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 f6a66362c..f4a8267fe 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -114,7 +114,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipadaeafcc-a88f-44cc-b134-9bdbaa230378 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip6e7b1d3c-fe8c-4053-9c50-129954c44dad 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 ac8486e0c..b22bd2120 100644
--- a/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_oneflow.rst.txt
@@ -112,7 +112,7 @@ 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
-
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+
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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 9bc679773..deddd1801 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -235,7 +235,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 16.060 seconds)
+ **Total running time of the script:** ( 1 minutes 6.926 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 6846dc4b4..df29dd60b 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -93,7 +93,7 @@ Load a pretrained PyTorch model
.. code-block:: none
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]
35%|###5 | 15.6M/44.7M [00:00<00:00, 164MB/s]
77%|#######7 | 34.5M/44.7M [00:00<00:00, 184MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 198MB/s]
+
0%| | 0.00/44.7M [00:00<?, ?B/s]
43%|####3 | 19.4M/44.7M [00:00<00:00, 203MB/s]
100%|##########| 44.7M/44.7M [00:00<00:00, 237MB/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 50fcd1a84..eb5659921 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -422,7 +422,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 1.191 seconds)
+ **Total running time of the script:** ( 1 minutes 3.713 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 d431498d8..96a0f9c3b 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
=================
-**05:34.660** total execution time for **how_to_compile_models** files:
+**05:25.044** total execution time for **how_to_compile_models** files:
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:16.060 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``) | 01:06.926 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:01.191 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``) | 01:03.713 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 01:00.533 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``) | 00:58.389 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:31.064 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_oneflow.py` (``from_oneflow.py``) | 00:31.414 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:25.581 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``) | 00:23.992 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:22.566 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``) | 00:22.971 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:22.531 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``) | 00:21.655 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:18.857 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``) | 00:19.110 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:13.887 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``) | 00:14.332 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.388 | 0.0 MB |
+| :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``) | 00:02.543 | 0.0 MB |
+-----------------------------------------------------------------------------------+-----------+--------+
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 d4fd9f9ed..a5b4ebeb5 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
@@ -440,7 +440,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.0016 15.7504 16.6340 15.6186 0.4231
+ 16.1169 16.0977 16.2810 15.9832 0.0971
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 06d402f09..52d6de1f5 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
@@ -122,7 +122,7 @@ Load pre-trained maskrcnn from torchvision and do tracing
.. code-block:: none
Downloading: "https://download.pytorch.org/models/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth" to /workspace/.cache/torch/hub/checkpoints/maskrcnn_resnet50_fpn_coco-bf2d0c1e.pth
-
0%| | 0.00/170M [00:00<?, ?B/s]
3%|3 | 5.71M/170M [00:00<00:02, 59.7MB/s]
7%|6 | 11.4M/170M [00:00<00:02, 59.6MB/s]
18%|#8 | 31.2M/170M [00:00<00:01, 127MB/s]
31%|###1 | 52.7M/170M [00:00<00:00, 165MB/s]
43%|####3 | 73.5M/170M [00:00<00:00, 185MB/s]
55%|#####5 | 93.8M/170M [00:00<00:00, 194MB/s]
67%|######7 | 114M/170M [00:00<00:00, 200MB/s]
79%|#######8 | 134M/170M [00:00<00:00, 204MB/s]
92%|#########2| 156M/170M [00:00<00:00, 213MB/s]
100%|##########| 170M/170M [00:00<00:00, 185MB/s]
+
0%| | 0.00/170M [00:00<?, ?B/s]
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20%|#9 | 33.9M/170M [00:00<00:01, 139MB/s]
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50%|##### | 85.7M/170M [00:00<00:00, 219MB/s]
64%|######4 | 109M/170M [00:00<00:00, 228MB/s]
80%|#######9 | 135M/170M [00:00<00:00, 243MB/s]
95%|#########4| 161M/170M [00:00<00:00, 251MB/s]
100%|##########| 170M/170M [00:00<00:00, 212MB/s]
/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3878: 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).
for i in range(dim)
/usr/local/lib/python3.7/dist-packages/torchvision/models/detection/anchor_utils.py:127: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
@@ -291,7 +291,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 53.791 seconds)
+ **Total running time of the script:** ( 3 minutes 1.727 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 234757dcc..f71079efc 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -219,7 +219,7 @@ training. Other models require a full post training calibration.
.. code-block:: none
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]
25%|##5 | 3.44M/13.6M [00:00<00:00, 32.3MB/s]
66%|######6 | 8.98M/13.6M [00:00<00:00, 46.8MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 51.3MB/s]
+
0%| | 0.00/13.6M [00:00<?, ?B/s]
6%|6 | 840k/13.6M [00:00<00:01, 8.59MB/s]
53%|#####2 | 7.18M/13.6M [00:00<00:00, 42.7MB/s]
87%|########7 | 11.8M/13.6M [00:00<00:00, 45.1MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 37.3MB/s]
@@ -399,7 +399,7 @@ 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)
- 90.3514 90.2329 94.3861 90.0187 0.5025
+ 90.4412 90.3514 94.8088 90.1974 0.4659
@@ -448,7 +448,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 6.913 seconds)
+ **Total running time of the script:** ( 1 minutes 8.200 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 af1487272..0b68fe38f 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
@@ -426,7 +426,7 @@ 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)
- 118.8420 118.7439 124.5735 116.6642 1.1390
+ 121.1668 121.0708 127.5322 120.4744 0.7153
@@ -463,7 +463,7 @@ Here we give an example of how to measure performance of TVM compiled models.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 50.550 seconds)
+ **Total running time of the script:** ( 2 minutes 0.999 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_prequantized_tflite.py:
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 404567555..2071e8167 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -254,7 +254,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 30.494 seconds)
+ **Total running time of the script:** ( 1 minutes 15.582 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_quantized.py:
diff --git a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
index c777bcb9f..107ea56d4 100644
--- a/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_ssd_gluoncv.rst.txt
@@ -157,7 +157,7 @@ Convert and compile model for CPU.
data: None
input_sym_arg_type = in_param.infer_type()[0]
Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/ssd_512_resnet50_v1_voc-9c8b225a.zip...
-
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+
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76%|#######5 | 100777/132723 [00:01<00:00, 84823.10KB/s]
82%|########2 | 109410/132723 [00:01<00:00, 85274.55KB/s]
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95%|#########5| 126608/132723 [00:01<00:00, 85631.74KB/s]
100%|#######
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@@ -240,7 +240,7 @@ Display result
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 18.209 seconds)
+ **Total running time of the script:** ( 2 minutes 21.413 seconds)
.. _sphx_glr_download_how_to_deploy_models_deploy_ssd_gluoncv.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 1a031770a..cd0464a70 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
@@ -5,22 +5,22 @@
Computation times
=================
-**10:30.093** total execution time for **how_to_deploy_models** files:
+**10:39.680** 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``) | 02:53.791 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``) | 03:01.727 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 02:18.209 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``) | 02:21.413 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 01:50.550 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``) | 02:00.999 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:30.494 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``) | 01:15.582 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:06.913 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``) | 01:08.200 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:28.342 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``) | 00:29.473 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:21.787 | 0.0 MB |
+| :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``) | 00:22.280 | 0.0 MB |
+------------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``) | 00:00.006 | 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 a5847b45e..9bb8ef6b8 100644
--- a/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
+++ b/docs/_sources/how_to/extend_tvm/bring_your_own_datatypes.rst.txt
@@ -463,7 +463,7 @@ First let us define two helper functions to get the mobilenet model and a cat im
.. code-block:: none
- Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip7d45ff99-f6ce-4514-8fb4-8609767e7dd5 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zipf73a00b1-7787-4154-b92d-15edbd4f6b03 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 41ef20ae8..671cb436d 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
=================
-**00:38.599** total execution time for **how_to_extend_tvm** files:
+**00:40.520** 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``) | 00:35.574 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``) | 00:37.284 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.132 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``) | 00:02.292 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:00.888 | 0.0 MB |
+| :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``) | 00:00.938 | 0.0 MB |
+-------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``) | 00:00.006 | 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 d172fc38d..95a3c6c22 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
@@ -215,10 +215,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 6454us [6454us] (45.65%; 45.65%)
- FoldScaleAxis: 7686us [6us] (54.35%; 54.35%)
- FoldConstant: 7679us [1589us] (54.31%; 99.92%)
- InferType: 6090us [6090us] (43.07%; 79.31%)
+ InferType: 6992us [6992us] (45.96%; 45.96%)
+ FoldScaleAxis: 8220us [6us] (54.04%; 54.04%)
+ FoldConstant: 8214us [1641us] (54.00%; 99.93%)
+ InferType: 6573us [6573us] (43.21%; 80.02%)
@@ -257,10 +257,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 6172us [6172us] (44.74%; 44.74%)
- FoldScaleAxis: 7623us [5us] (55.26%; 55.26%)
- FoldConstant: 7618us [1572us] (55.23%; 99.94%)
- InferType: 6046us [6046us] (43.83%; 79.37%)
+ InferType: 6581us [6581us] (44.72%; 44.72%)
+ FoldScaleAxis: 8135us [5us] (55.28%; 55.28%)
+ FoldConstant: 8130us [1663us] (55.25%; 99.94%)
+ InferType: 6467us [6467us] (43.95%; 79.55%)
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 c94039508..2dc93e4d8 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
@@ -327,7 +327,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 37.096612 ms
+ Convolution: 54.160311 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 0cc2713e8..77e67b95c 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
@@ -658,7 +658,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 7.545861 ms
+ conv2d with tensor core: 8.167091 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 93b54c8a2..bedc7a7ba 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -130,8 +130,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.018394
- Baseline: 3.408293
+ Numpy running time: 0.019787
+ Baseline: 3.402191
@@ -226,7 +226,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.300549
+ Opt1: 0.314941
@@ -329,7 +329,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.337973
+ Opt2: 0.347885
@@ -425,7 +425,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.122914
+ Opt3: 0.120919
@@ -550,7 +550,7 @@ flattening.
.. code-block:: none
- Opt4: 0.110785
+ Opt4: 0.110538
@@ -672,7 +672,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.112291
+ Opt5: 0.111790
@@ -797,7 +797,7 @@ Futhermore, we can also utilize multi-core processors to do the thread-level par
.. code-block:: none
- Opt6: 0.145276
+ Opt6: 0.145566
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 01cf1766a..093316666 100644
--- a/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
Computation times
=================
-**00:34.483** total execution time for **how_to_optimize_operators** files:
+**00:35.019** total execution time for **how_to_optimize_operators** files:
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:32.276 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``) | 00:32.696 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.216 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``) | 00:01.269 | 0.0 MB |
+-----------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:00.991 | 0.0 MB |
+| :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``) | 00:01.054 | 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 dadd13785..df839cf7f 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
=================
-**05:07.789** total execution time for **how_to_tune_with_autoscheduler** files:
+**05:19.961** total execution time for **how_to_tune_with_autoscheduler** files:
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 02:32.144 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``) | 02:41.427 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:19.314 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``) | 01:20.914 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 00:42.501 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``) | 00:43.495 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:17.240 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``) | 00:16.738 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:08.418 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``) | 00:08.699 | 0.0 MB |
+----------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:08.172 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``) | 00:08.687 | 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 d010aed1a..49ba059b8 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
@@ -770,7 +770,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.354 ms
+ Execution time of this operator: 0.366 ms
@@ -1377,7 +1377,7 @@ In the example below we resume the status and do more 5 trials.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 32.144 seconds)
+ **Total running time of the script:** ( 2 minutes 41.427 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py:
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 a945f22c9..d6ee72bb4 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
@@ -646,7 +646,7 @@ 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)
- 9.8039 9.7978 9.8257 9.7883 0.0159
+ 10.0391 10.0250 10.1017 9.9904 0.0465
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 0ce49e681..2fe76dd9a 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
@@ -665,7 +665,7 @@ 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)
- 744.2871 743.5306 746.4699 742.8608 1.5675
+ 763.1815 763.3894 763.4273 762.7276 0.3213
@@ -693,7 +693,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 19.314 seconds)
+ **Total running time of the script:** ( 1 minutes 20.914 seconds)
.. _sphx_glr_download_how_to_tune_with_autoscheduler_tune_network_x86.py:
diff --git a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
index 85ba2f04c..67b8c07bd 100644
--- a/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
+++ b/docs/_sources/how_to/tune_with_autoscheduler/tune_sparse_x86.rst.txt
@@ -396,79 +396,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [65536], []),
compute: Buffer(compute_2: Pointer(float32), float32, [65536], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute}
- preflattened_buffer_map = {compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_8: placeholder_15: Buffer(placeholder_13, int32, [33], []), placeholder_5: placeholder_16: Buffer(placeholder_10, float32, [128, 256], []), placeholder_7: placeholder_17: Buffer(placeholder_12, int32, [4916], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_9: placeholder_19: Buffer(placeholder_14, float32, [128, 512], [])} {
- for (i0.outer.i1.outer.fused: int32, 0, 16) "parallel" {
- allocate(compute_4: Pointer(global float32), float32, [4096]), storage_scope = global {
- for (i.outer.inner: int32, 0, 4) {
- for (nb_j.inner: int32, 0, 2) {
- for (i.inner.init: int32, 0, 32) {
- let cse_var_1: int32 = (((i.outer.inner*1024) + (i.inner.init*32)) + (nb_j.inner*16))
- {
- compute_5: Buffer(compute_4, float32, [4096], [])[cse_var_1] = 0f32
- compute_5[(cse_var_1 + 1)] = 0f32
- compute_5[(cse_var_1 + 2)] = 0f32
- compute_5[(cse_var_1 + 3)] = 0f32
- compute_5[(cse_var_1 + 4)] = 0f32
- compute_5[(cse_var_1 + 5)] = 0f32
- compute_5[(cse_var_1 + 6)] = 0f32
- compute_5[(cse_var_1 + 7)] = 0f32
- compute_5[(cse_var_1 + 8)] = 0f32
- compute_5[(cse_var_1 + 9)] = 0f32
- compute_5[(cse_var_1 + 10)] = 0f32
- compute_5[(cse_var_1 + 11)] = 0f32
- compute_5[(cse_var_1 + 12)] = 0f32
- compute_5[(cse_var_1 + 13)] = 0f32
- compute_5[(cse_var_1 + 14)] = 0f32
- compute_5[(cse_var_1 + 15)] = 0f32
- }
+ preflattened_buffer_map = {placeholder_5: placeholder_15: Buffer(placeholder_10, float32, [128, 256], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_7: placeholder_16: Buffer(placeholder_12, int32, [4916], []), placeholder_8: placeholder_17: Buffer(placeholder_13, int32, [33], []), placeholder_9: placeholder_18: Buffer(placeholder_14, float32, [128, 512], []), placeholder_6: placeholder_19: Buffer(placeholder_11, float32, [4916, 16, 1], [])} {
+ for (i0.outer.i1.outer.fused: int32, 0, 256) "parallel" {
+ allocate(compute_4: Pointer(global float32), float32, [256]), storage_scope = global {
+ for (nb_j.inner: int32, 0, 2) {
+ for (i.inner.init: int32, 0, 8) {
+ for (j.init: int32, 0, 16) {
+ compute_5: Buffer(compute_4, float32, [256], [])[(((i.inner.init*32) + (nb_j.inner*16)) + j.init)] = 0f32
}
- for (elem_idx: int32, 0, let cse_var_2: int32 = ((i0.outer.i1.outer.fused*2) + nb_j.inner) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
- for (i.inner: int32, 0, 32) {
- let cse_var_21: int32 = (elem_idx*16)
- let cse_var_20: int32 = ((i0.outer.i1.outer.fused*2) + nb_j.inner)
- let cse_var_19: int32 = ((i.outer.inner*8192) + (i.inner*256))
- let cse_var_18: int32 = (((i.outer.inner*1024) + (i.inner*32)) + (nb_j.inner*16))
- let cse_var_17: int32 = (cse_var_18 + 9)
- let cse_var_16: int32 = (cse_var_18 + 8)
- let cse_var_15: int32 = (cse_var_18 + 7)
- let cse_var_14: int32 = (cse_var_18 + 6)
- let cse_var_13: int32 = (cse_var_18 + 5)
- let cse_var_12: int32 = (cse_var_18 + 4)
- let cse_var_11: int32 = (cse_var_18 + 3)
- let cse_var_10: int32 = (cse_var_18 + 2)
- let cse_var_9: int32 = (cse_var_18 + 15)
- let cse_var_8: int32 = (cse_var_18 + 14)
- let cse_var_7: int32 = (cse_var_18 + 13)
- let cse_var_6: int32 = (cse_var_18 + 12)
- let cse_var_5: int32 = (cse_var_18 + 11)
- let cse_var_4: int32 = (cse_var_18 + 10)
- let cse_var_3: int32 = (cse_var_18 + 1)
- {
- compute_5[cse_var_18] = (compute_5[cse_var_18] + (placeholder_1[((placeholder_3[cse_var_20]*16) + cse_var_21)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_3] = (compute_5[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 1)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_10] = (compute_5[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 2)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_11] = (compute_5[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 3)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_12] = (compute_5[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 4)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_13] = (compute_5[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 5)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_14] = (compute_5[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 6)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_15] = (compute_5[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 7)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_16] = (compute_5[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 8)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_17] = (compute_5[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 9)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_4] = (compute_5[cse_var_4] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 10)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_5] = (compute_5[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 11)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_6] = (compute_5[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 12)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_7] = (compute_5[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 13)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_8] = (compute_5[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 14)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_9] = (compute_5[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 15)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- }
+ }
+ for (elem_idx: int32, 0, let cse_var_1: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_3[(cse_var_1 + 1)] - placeholder_3[cse_var_1])) {
+ for (i.inner: int32, 0, 8) {
+ for (j: int32, 0, 16) {
+ let cse_var_3: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_2: int32 = (((i.inner*32) + (nb_j.inner*16)) + j)
+ compute_5[cse_var_2] = (compute_5[cse_var_2] + (placeholder_1[(((placeholder_3[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 16)*2048) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_3] + elem_idx)])], 0f32)))
}
}
}
}
- for (i0.inner: int32, 0, 128) {
+ for (i0.inner: int32, 0, 8) {
for (i1.inner: int32, 0, 32) {
- let cse_var_22: int32 = (((i0.inner*512) + (i0.outer.i1.outer.fused*32)) + i1.inner)
- compute[cse_var_22] = max((compute_5[((i0.inner*32) + i1.inner)] + placeholder_4[cse_var_22]), 0f32)
+ let cse_var_4: int32 = ((((floordiv(i0.outer.i1.outer.fused, 16)*4096) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32)) + i1.inner)
+ compute[cse_var_4] = max((compute_5[((i0.inner*32) + i1.inner)] + placeholder_4[cse_var_4]), 0f32)
}
}
}
@@ -525,7 +475,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 1.736 ms
+ Execution time of this operator: 1.589 ms
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 101a34287..5a3e20830 100644
--- a/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
+++ b/docs/_sources/how_to/tune_with_autotvm/sg_execution_times.rst.txt
@@ -5,16 +5,16 @@
Computation times
=================
-**00:42.962** total execution time for **how_to_tune_with_autotvm** files:
+**00:43.862** 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``) | 00:42.930 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``) | 00:43.829 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``) | 00:00.019 | 0.0 MB |
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``) | 00:00.020 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``) | 00:00.005 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``) | 00:00.005 | 0.0 MB |
-+--------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``) | 00:00.004 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
+| :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``) | 00:00.004 | 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 a4fbf1981..10e30ea06 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
@@ -879,8 +879,8 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 32]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2885496
- No: 6 GFLOPS: 42.43/42.43 result: MeasureResult(costs=(0.0054557639473684204,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.631316900253296, timestamp=1655487731.6056771) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
- No: 7 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 6 GFLOPS: 42.38/42.38 result: MeasureResult(costs=(0.005462229789473684,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6179249286651611, timestamp=1655495728.4610019) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
+ No: 7 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1003,7 +1003,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 16, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6225319
- No: 8 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 8 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1126,7 +1126,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,943546
- No: 9 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 9 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1249,7 +1249,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 16, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 32]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2868708
- No: 10 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 10 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 142, in build
res = future.result()
File "/usr/lib/python3.7/concurrent/futures/_base.py", line 435, in result
@@ -1267,7 +1267,7 @@ for this template
TimeoutError
[('tile_f', [-1, 32, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4691833
- No: 11 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 11 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1390,7 +1390,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 2, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1042124
- No: 12 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 12 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1513,7 +1513,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10013405
- No: 13 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 13 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1636,7 +1636,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 8, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6732082
- No: 14 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 14 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1759,7 +1759,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 4, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7536735
- No: 15 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 15 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1882,7 +1882,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,482121
- No: 16 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 16 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2005,7 +2005,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 32, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2824525
- No: 17 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 17 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2128,7 +2128,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4559286
- No: 18 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 18 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2251,7 +2251,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 32, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 512]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9677544
- No: 19 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+ No: 19 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 738, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 702, in run_through_rpc
@@ -2339,7 +2339,7 @@ for this template
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007fd388d74fa2
+ 12: 0x00007f9edb78efa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2404,7 +2404,7 @@ for this template
21: _PyFunction_FastCallKeywords
20: _PyEval_EvalFrameDefault
19: _PyFunction_FastCall [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6390073
- No: 20 GFLOPS: 144.87/144.87 result: MeasureResult(costs=(0.0015980323899999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4396235942840576, timestamp=1655487758.0288036) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
+ No: 20 GFLOPS: 143.39/143.39 result: MeasureResult(costs=(0.0016145025499999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4372198581695557, timestamp=1655495754.351655) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
@@ -2461,7 +2461,7 @@ and measure running time.
Best config:
[('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
Finish loading 20 records
- Time cost of this operator: 0.002035
+ Time cost of this operator: 0.001995
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 5bde40cf5..dd60dc293 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
@@ -328,10 +328,10 @@ Timing the untuned program
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 318.7 98.757 (1, 2, 10, 10, 3) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.079 0.954 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.932 0.289 (1, 1, 10, 10, 3) 1 1
- Total_time - 322.711 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 317.6 98.756 (1, 2, 10, 10, 3) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.076 0.956 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.924 0.287 (1, 1, 10, 10, 3) 1 1
+ Total_time - 321.6 - - - -
@@ -397,10 +397,10 @@ Timing the tuned program
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
- tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 86.35 96.983 (1, 6, 10, 10, 1) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.784 2.004 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.902 1.013 (1, 1, 10, 10, 3) 1 1
- Total_time - 89.036 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 192.7 98.583 (1, 1, 10, 10, 6) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.952 0.999 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.817 0.418 (1, 3, 10, 10, 1) 1 1
+ Total_time - 195.469 - - - -
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 9231ffb3d..79d7ae490 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
@@ -224,7 +224,7 @@ take about **2 minutes** to download the Stanford Cars, while COCO 2017 validati
.. code-block:: none
- '/tmp/tmpjl_tmotx/images/random'
+ '/tmp/tmpswoy7eqf/images/random'
@@ -324,8 +324,8 @@ objects to other stuff? We can display some examples from our datasets using ``m
.. code-block:: none
- /tmp/tmpjl_tmotx/images/target contains 8144 images
- /tmp/tmpjl_tmotx/images/random contains 5000 images
+ /tmp/tmpswoy7eqf/images/target contains 8144 images
+ /tmp/tmpswoy7eqf/images/random contains 5000 images
@@ -500,13 +500,13 @@ the time on our validation set).
.. code-block:: none
Epoch 1/3
- 328/328 - 55s - loss: 0.2093 - accuracy: 0.9261 - val_loss: 0.1326 - val_accuracy: 0.9573
+ 328/328 - 55s - loss: 0.2427 - accuracy: 0.9199 - val_loss: 0.1533 - val_accuracy: 0.9554
Epoch 2/3
- 328/328 - 52s - loss: 0.0967 - accuracy: 0.9642 - val_loss: 0.1191 - val_accuracy: 0.9630
+ 328/328 - 53s - loss: 0.1020 - accuracy: 0.9620 - val_loss: 0.1102 - val_accuracy: 0.9630
Epoch 3/3
- 328/328 - 52s - loss: 0.0622 - accuracy: 0.9771 - val_loss: 0.1048 - val_accuracy: 0.9664
+ 328/328 - 53s - loss: 0.0697 - accuracy: 0.9721 - val_loss: 0.1047 - val_accuracy: 0.9645
- <keras.callbacks.History object at 0x7f50f6406dd0>
+ <keras.callbacks.History object at 0x7fe528b0cc10>
@@ -863,7 +863,7 @@ 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:** ( 5 minutes 13.398 seconds)
+ **Total running time of the script:** ( 4 minutes 28.356 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 e7ffa9159..294b5e687 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
@@ -5,14 +5,14 @@
Computation times
=================
-**05:58.044** total execution time for **how_to_work_with_microtvm** files:
+**05:15.643** total execution time for **how_to_work_with_microtvm** files:
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 05:13.398 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_train.py` (``micro_train.py``) | 04:28.356 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:41.211 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``) | 00:43.771 | 0.0 MB |
+---------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.435 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``) | 00:03.516 | 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 b29bf6d4a..98baedf94 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
@@ -5,12 +5,12 @@
Computation times
=================
-**00:05.612** total execution time for **how_to_work_with_relay** files:
+**00:11.558** total execution time for **how_to_work_with_relay** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:04.359 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``) | 00:10.012 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.247 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``) | 00:01.540 | 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 2d4bcac79..71ec41466 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
@@ -259,7 +259,7 @@ The following example customizes CUDA lowering rule for :code:`exp`.
.. code-block:: none
- <function my_cuda_math_rule at 0x7f504905eb90>
+ <function my_cuda_math_rule at 0x7fe530d6a560>
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 fbaabe3a2..5bedc2c41 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
=================
-**00:03.522** total execution time for **how_to_work_with_schedules** files:
+**00:04.103** total execution time for **how_to_work_with_schedules** files:
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:01.769 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``) | 00:01.902 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:00.610 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``) | 00:00.980 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.489 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.529 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``) | 00:00.485 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``) | 00:00.516 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.098 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``) | 00:00.101 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.033 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``) | 00:00.034 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.025 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``) | 00:00.027 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.012 | 0.0 MB |
+| :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``) | 00:00.013 | 0.0 MB |
+------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
index bf60169eb..94d1be6d2 100644
--- a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
@@ -346,7 +346,7 @@ The importing needs to happen before the tensorized GEMV being executed.
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C}
preflattened_buffer_map = {A_1: A_3: Buffer(A_2, float32, [1024, 64], []), B_1: B_3: Buffer(B_2, float32, [512, 64], []), C_1: C_3: Buffer(C_2, float32, [1024, 512], [])} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmp9e52vytt/input0.cc'\nsource_filename = \"/tmp/tmp9e52vytt/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpzc_fl_hs/input0.cc'\nsource_filename = \"/tmp/tmpzc_fl_hs/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = alloca float*, align 8\n %8 = alloca float*, align 8\n %9 = alloca floa [...]
for (i, 0, 1024) {
for (j.outer: int32, 0, 32) {
@tir.call_extern("gemv_update", @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), C_2, ((i*512) + (j.outer*16)), 16, 2, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), A_2, (i*64), 64, 1, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), B_2, (j.outer*1024), 1024, 1, dtype=handle), 16, 64, 64, dtype=int32)
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 0ede6b4c2..4e47d1c49 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
=================
-**00:20.218** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:21.494** total execution time for **topic_vta_tutorials_autotvm** files:
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:20.212 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``) | 00:21.487 | 0.0 MB |
+---------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``) | 00:00.006 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``) | 00:00.007 | 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 19fee9910..31646b7cc 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -291,7 +291,7 @@ The compilation steps are:
DeprecationWarning,
/workspace/vta/tutorials/frontend/deploy_classification.py:213: 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.
relay_prog, target=tvm.target.Target(target, host=env.target_host), params=params
- resnet18_v1 inference graph built in 21.70s!
+ resnet18_v1 inference graph built in 23.12s!
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 25368ef38..9c0a67f46 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -335,7 +335,7 @@ The compilation steps are:
"target_host parameter is going to be deprecated. "
/workspace/python/tvm/relay/build_module.py:389: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- yolov3-tiny inference graph built in 15.59s!
+ yolov3-tiny inference graph built in 16.01s!
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 e009e0a56..da3af5912 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/sg_execution_times.rst.txt
@@ -5,10 +5,10 @@
Computation times
=================
-**01:29.251** total execution time for **topic_vta_tutorials_frontend** files:
+**01:34.031** total execution time for **topic_vta_tutorials_frontend** files:
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:47.713 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``) | 00:50.712 | 0.0 MB |
+------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:41.538 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``) | 00:43.319 | 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 cccfe5803..2e0bb8c17 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
=================
-**00:03.228** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.199** total execution time for **topic_vta_tutorials_optimize** files:
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.873 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``) | 00:02.807 | 0.0 MB |
+--------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.356 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``) | 00:00.392 | 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 db59a05e4..1491de1f2 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
=================
-**00:00.617** total execution time for **topic_vta_tutorials** files:
+**00:00.675** total execution time for **topic_vta_tutorials** files:
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.325 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``) | 00:00.346 | 0.0 MB |
+---------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.292 | 0.0 MB |
+| :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``) | 00:00.330 | 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 3b6408e00..52d9a4dc3 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -327,7 +327,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 93.718 ms
+ Execution time of this operator: 93.332 ms
diff --git a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
index b61555386..6e4982102 100644
--- a/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_matmul_x86.rst.txt
@@ -449,16 +449,16 @@ reduce variance, we take 5 measurements and average them.
waiting for device...
device available
Get devices for measurement successfully!
- No: 1 GFLOPS: 9.41/9.41 result: MeasureResult(costs=(0.028528636200000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5863704681396484, timestamp=1655486599.8214881) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
- No: 2 GFLOPS: 2.41/9.41 result: MeasureResult(costs=(0.11160172239999999,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.9324774742126465, timestamp=1655486601.770372) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
- No: 3 GFLOPS: 11.84/11.84 result: MeasureResult(costs=(0.0226801726,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.544255256652832, timestamp=1655486602.7900786) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
- No: 4 GFLOPS: 1.65/11.84 result: MeasureResult(costs=(0.16238027380000003,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.714060068130493, timestamp=1655486606.0595603) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
- No: 5 GFLOPS: 3.63/11.84 result: MeasureResult(costs=(0.074033503,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.3246564865112305, timestamp=1655486608.0080574) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
- No: 6 GFLOPS: 1.71/11.84 result: MeasureResult(costs=(0.15702880319999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.664867401123047, timestamp=1655486610.7191503) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
- No: 7 GFLOPS: 0.80/11.84 result: MeasureResult(costs=(0.3340988224,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.4783337116241455, timestamp=1655486616.2408695) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
- No: 8 GFLOPS: 10.07/11.84 result: MeasureResult(costs=(0.0266654002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5722219944000244, timestamp=1655486616.8287463) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
- No: 9 GFLOPS: 1.82/11.84 result: MeasureResult(costs=(0.14722629780000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4541280269622803, timestamp=1655486619.4021802) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
- No: 10 GFLOPS: 2.48/11.84 result: MeasureResult(costs=(0.10825188700000002,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8308920860290527, timestamp=1655486621.2936637) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
+ No: 1 GFLOPS: 10.59/10.59 result: MeasureResult(costs=(0.025350754399999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5417935848236084, timestamp=1655494596.0339978) [('tile_y', [-1, 1]), ('tile_x', [-1, 256])],None,80
+ No: 2 GFLOPS: 2.91/10.59 result: MeasureResult(costs=(0.0922198056,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6125414371490479, timestamp=1655494597.6738045) [('tile_y', [-1, 4]), ('tile_x', [-1, 8])],None,32
+ No: 3 GFLOPS: 11.67/11.67 result: MeasureResult(costs=(0.022993986,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5693972110748291, timestamp=1655494598.7122824) [('tile_y', [-1, 64]), ('tile_x', [-1, 32])],None,56
+ No: 4 GFLOPS: 1.85/11.67 result: MeasureResult(costs=(0.144850218,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4384047985076904, timestamp=1655494601.7014444) [('tile_y', [-1, 1]), ('tile_x', [-1, 4])],None,20
+ No: 5 GFLOPS: 3.53/11.67 result: MeasureResult(costs=(0.076073456,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.337911605834961, timestamp=1655494603.1683533) [('tile_y', [-1, 256]), ('tile_x', [-1, 16])],None,48
+ No: 6 GFLOPS: 1.88/11.67 result: MeasureResult(costs=(0.1431307018,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.4245381355285645, timestamp=1655494606.1388836) [('tile_y', [-1, 512]), ('tile_x', [-1, 4])],None,29
+ No: 7 GFLOPS: 0.87/11.67 result: MeasureResult(costs=(0.30853695560000005,), error_no=MeasureErrorNo.NO_ERROR, all_cost=5.0530781745910645, timestamp=1655494611.2407897) [('tile_y', [-1, 512]), ('tile_x', [-1, 2])],None,19
+ No: 8 GFLOPS: 10.42/11.67 result: MeasureResult(costs=(0.0257719838,), error_no=MeasureErrorNo.NO_ERROR, all_cost=0.5576310157775879, timestamp=1655494611.8182216) [('tile_y', [-1, 4]), ('tile_x', [-1, 64])],None,62
+ No: 9 GFLOPS: 1.89/11.67 result: MeasureResult(costs=(0.1421505362,), error_no=MeasureErrorNo.NO_ERROR, all_cost=2.377051830291748, timestamp=1655494614.3144066) [('tile_y', [-1, 2]), ('tile_x', [-1, 2])],None,11
+ No: 10 GFLOPS: 2.49/11.67 result: MeasureResult(costs=(0.1076101258,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8288979530334473, timestamp=1655494616.2023952) [('tile_y', [-1, 4]), ('tile_x', [-1, 4])],None,22
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 661de9b0e..5e720fac1 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -314,7 +314,7 @@ standard deviation.
.. code-block:: none
- {'mean': 497.45479426998827, 'median': 497.9651370999818, 'std': 2.5633199724376263}
+ {'mean': 496.82471173000977, 'median': 496.607584100002, 'std': 1.1306536165218921}
@@ -550,31 +550,31 @@ the tuning data to.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 17.23/ 17.23 GFLOPS | Progress: (4/20) | 6.20 s
[Task 1/25] Current/Best: 6.16/ 17.23 GFLOPS | Progress: (8/20) | 9.18 s
[Task 1/25] Current/Best: 11.52/ 22.75 GFLOPS | Progress: (12/20) | 11.59 s
[Task 1/25] Current/Best: 16.70/ 22.85 GFLOPS | Progress: (16/20) | 13.28 s
[Task 1/25] Current/Best: 11.59/ 23.92 GFLOPS | Progress: (20/20) | 15.02 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 12.14/ 13.22 GFLOPS | Progress: (4/20) | 3.79 s
[Task 2/25] Current/Best: 14.48/ 18.35 GFLOPS | Progress: (8/20) | 5.11 s
[Task 2/25] Current/Best: 20.94/ 20.94 GFLOPS | Progress: (12/20) | 6.45 s
[Task 2/25] Current/Best: 12.55/ 20.94 GFLOPS | Progress: (16/20) | 7.74 s
[Task 2/25] Current/Best: 19.00/ 20.94 GFLOPS | Progress: (20/20) | 9.36 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 1.62/ 10.52 GFLOPS | Progress: (4/20) | 5.86 s
[Task 3/25] Current/Best: 15.50/ 16.81 GFLOPS | Progress: (8/20) | 7.77 s
[Task 3/25] Current/Best: 14.89/ 16.81 GFLOPS | Progress: (12/20) | 9.50 s
[Task 3/25] Current/Best: 7.19/ 23.77 GFLOPS | Progress: (16/20) | 11.44 s
[Task 3/25] Current/Best: 12.62/ 23.77 GFLOPS | Progress: (20/20) | 15.97 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 9.46/ 20.08 GFLOPS | Progress: (4/20) | 2.35 s
[Task 4/25] Current/Best: 6.85/ 20.08 GFLOPS | Progress: (8/20) | 6.65 s
[Task 4/25] Current/Best: 22.17/ 22.17 GFLOPS | Progress: (12/20) | 11.21 s
[Task 4/25] Current/Best: 17.25/ 22.17 GFLOPS | Progress: (16/20) | 13.44 s
[Task 4/25] Current/Best: 13.30/ 22.17 GFLOPS | Progress: (20/20) | 15.33 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 9.51/ 10.01 GFLOPS | Progress: (4/20) | 2.60 s
[Task 5/25] Current/Best: 11.74/ 12.69 GFLOPS | Progress: (8/20) | 4.66 s
[Task 5/25] Current/Best: 11.78/ 18.06 GFLOPS | Progress: (12/20) | 7.73 s
[Task 5/25] Current/Best: 11.54/ 22.70 GFLOPS | Progress: (16/20) | 9.15 s
[Task 5/25] Current/Best: 11.76/ 22.70 GFLOPS | Progress: (20/20) | 11.04 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 12.15/ 20.77 GFLOPS | Progress: (4/20) | 3.93 s
[Task 6/25] Current/Best: 18.93/ 20.77 GFLOPS | Progress: (8/20) | 5.68 s
[Task 6/25] Current/Best: 13.21/ 20.77 GFLOPS | Progress: (12/20) | 7.61 s
[Task 6/25] Current/Best: 20.10/ 20.77 GFLOPS | Progress: (16/20) | 9.84 s
[Task 6/25] Current/Best: 3.72/ 20.77 GFLOPS | Progress: (20/20) | 12.33 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 11.21/ 12.94 GFLOPS | Progress: (4/20) | 3.54 s
[Task 7/25] Current/Best: 20.26/ 20.96 GFLOPS | Progress: (8/20) | 5.04 s
[Task 7/25] Current/Best: 15.84/ 20.97 GFLOPS | Progress: (12/20) | 6.95 s
[Task 7/25] Current/Best: 12.21/ 20.97 GFLOPS | Progress: (16/20) | 9.00 s
[Task 7/25] Current/Best: 6.41/ 21.74 GFLOPS | Progress: (20/20) | 11.46 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 9.89/ 13.97 GFLOPS | Progress: (4/20) | 2.90 s
[Task 8/25] Current/Best: 9.25/ 13.97 GFLOPS | Progress: (8/20) | 7.69 s
[Task 8/25] Current/Best: 12.33/ 13.97 GFLOPS | Progress: (12/20) | 13.85 s
[Task 8/25] Current/Best: 18.89/ 18.89 GFLOPS | Progress: (16/20) | 15.94 s
[Task 8/25] Current/Best: 19.94/ 19.94 GFLOPS | Progress: (20/20) | 22.40 s Done.
-
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 14.31/ 15.67 GFLOPS | Progress: (4/20) | 11.91 s
[Task 9/25] Current/Best: 23.16/ 23.16 GFLOPS | Progress: (8/20) | 13.66 s
[Task 9/25] Current/Best: 8.25/ 23.16 GFLOPS | Progress: (12/20) | 16.08 s
[Task 9/25] Current/Best: 18.01/ 23.16 GFLOPS | Progress: (16/20) | 18.76 s
[Task 9/25] Current/Best: 9.04/ 23.16 GFLOPS | Progress: (20/20) | 26.45 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 18.40/ 18.40 GFLOPS | Progress: (4/20) | 2.53 s
[Task 10/25] Current/Best: 15.55/ 18.40 GFLOPS | Progress: (8/20) | 4.11 s
[Task 10/25] Current/Best: 12.31/ 18.94 GFLOPS | Progress: (12/20) | 5.63 s
[Task 10/25] Current/Best: 19.04/ 20.28 GFLOPS | Progress: (16/20) | 6.73 s
[Task 10/25] Current/Best: 8.81/ 20.28 GFLOPS | Progress: (20/20
) | 8.25 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/ 18.16 GFLOPS | Progress: (4/20) | 3.31 s
[Task 11/25] Current/Best: 16.85/ 18.16 GFLOPS | Progress: (8/20) | 6.05 s
[Task 11/25] Current/Best: 17.93/ 18.16 GFLOPS | Progress: (12/20) | 8.05 s
[Task 11/25] Current/Best: 11.94/ 21.21 GFLOPS | Progress: (16/20) | 10.89 s
[Task 11/25] Current/Best: 19.43/ 21.63 GFLOPS | Progress: (20/20) | 12.92 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 7.80/ 18.06 GFLOPS | Progress: (4/20) | 5.29 s
[Task 12/25] Current/Best: 5.18/ 18.06 GFLOPS | Progress: (8/20) | 9.01 s
[Task 12/25] Current/Best: 18.64/ 18.88 GFLOPS | Progress: (12/20) | 11.00 s
[Task 12/25] Current/Best: 14.91/ 18.88 GFLOPS | Progress: (16/20) | 13.78 s
[Task 12/25] Current/Best: 15.20/ 19.12 GFLOPS | Progress: (20/20) | 15.70 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 8.72/ 17.22 GFLOPS | Progress: (4/20) | 3.59 s
[Task 13/25] Current/Best: 15.37/ 20.92 GFLOPS | Progress: (8/20) | 6.04 s
[Task 13/25] Current/Best: 19.69/ 21.23 GFLOPS | Progress: (12/20) | 8.90 s
[Task 13/25] Current/Best: 12.21/ 21.23 GFLOPS | Progress: (16/20) | 12.25 s
[Task 13/25] Current/Best: 18.67/ 21.23 GFLOPS | Progress: (20/20) | 14.50 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 13.62/ 13.62 GFLOPS | Progress: (4/20) | 3.19 s
[Task 14/25] Current/Best: 6.11/ 13.62 GFLOPS | Progress: (8/20) | 5.37 s
[Task 14/25] Current/Best: 20.28/ 20.28 GFLOPS | Progress: (12/20) | 7.89 s
[Task 14/25] Current/Best: 16.26/ 20.28 GFLOPS | Progress: (16/20) | 9.53 s Done.
-
[Task 14/25] Current/Best: 17.15/ 20.28 GFLOPS | Progress: (20/20) | 11.24 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 16.01/ 17.42 GFLOPS | Progress: (4/20) | 2.66 s
[Task 15/25] Current/Best: 13.14/ 17.99 GFLOPS | Progress: (8/20) | 3.96 s
[Task 15/25] Current/Best: 10.40/ 22.12 GFLOPS | Progress: (12/20) | 6.02 s
[Task 15/25] Current/Best: 20.44/ 22.12 GFLOPS | Progress: (16/20) | 8.91 s
[Task 15/25] Current/Best: 9.69/ 22.12 GFLOPS | Progress: (20/20) | 9.88 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 20.37/ 20.37 GFLOPS | Progress: (4/20) | 2.96 s
[Task 16/25] Current/Best: 3.04/ 20.37 GFLOPS | Progress: (8/20) | 4.57 s
[Task 16/25] Current/Best: 19.52/ 20.37 GFLOPS | Progress: (12/20) | 5.80 s
[Task 16/25] Current/Best: 18.06/ 20.37 GFLOPS | Progress: (16/20) |
7.16 s
[Task 16/25] Current/Best: 9.98/ 22.22 GFLOPS | Progress: (20/20) | 9.20 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 12.93/ 18.78 GFLOPS | Progress: (4/20) | 4.67 s
[Task 17/25] Current/Best: 13.33/ 23.34 GFLOPS | Progress: (8/20) | 7.42 s
[Task 17/25] Current/Best: 16.88/ 23.34 GFLOPS | Progress: (12/20) | 9.46 s
[Task 17/25] Current/Best: 16.42/ 23.34 GFLOPS | Progress: (16/20) | 11.60 s
[Task 17/25] Current/Best: 10.03/ 23.34 GFLOPS | Progress: (20/20) | 13.71 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 11.39/ 17.75 GFLOPS | Progress: (4/20) | 3.59 s
[Task 18/25] Current/Best: 10.54/ 19.65 GFLOPS | Progress: (8/20) | 6.96 s
[Task 18/25] Current/Best: 17.92/ 19.65 GFLOPS | Progress: (12/20) | 8.86 s
[Task 18/25] Current/Best: 10.03/ 19.65 GFLOPS | Progress: (16/20) | 12.40 s
[Task 18/25] Current/Best: 20.79/ 20.79 GFLOPS | Progress: (20/20) | 13.90 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 7.04/ 20.48 GFLOPS | Progress: (4/20) | 5.94 s
[Task 19/25] Current/Best: 2.60/ 20.48 GFLOPS | Progress: (8/20) | 9.27 s
[Task 19/25] Current/Best: 19.26/ 20.64 GFLOPS | Progress: (12/20) | 12.05 s
[Task 19/25] Current/Best: 13.05/ 21.10 GFLOPS | Progress: (16/20) | 14.91 s
[Task 19/25] Current/Best: 2.70/ 23.42 GFLOPS | Progress: (20/20) | 17.69 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 9.36/ 15.18 GFLOPS | Progress: (4/20) | 3.26 s Done.
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 1/25] Current/Best: 17.40/ 17.40 GFLOPS | Progress: (4/20) | 6.11 s
[Task 1/25] Current/Best: 6.16/ 17.40 GFLOPS | Progress: (8/20) | 8.99 s
[Task 1/25] Current/Best: 11.48/ 22.46 GFLOPS | Progress: (12/20) | 11.43 s
[Task 1/25] Current/Best: 16.71/ 22.56 GFLOPS | Progress: (16/20) | 13.12 s
[Task 1/25] Current/Best: 11.55/ 23.89 GFLOPS | Progress: (20/20) | 14.88 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 2/25] Current/Best: 12.06/ 13.15 GFLOPS | Progress: (4/20) | 3.79 s
[Task 2/25] Current/Best: 13.84/ 18.12 GFLOPS | Progress: (8/20) | 5.11 s
[Task 2/25] Current/Best: 20.77/ 20.77 GFLOPS | Progress: (12/20) | 6.43 s
[Task 2/25] Current/Best: 11.92/ 20.77 GFLOPS | Progress: (16/20) | 7.70 s
[Task 2/25] Current/Best: 18.99/ 20.77 GFLOPS | Progress: (20/20) | 9.31 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 3/25] Current/Best: 1.63/ 10.56 GFLOPS | Progress: (4/20) | 5.84 s
[Task 3/25] Current/Best: 15.50/ 16.83 GFLOPS | Progress: (8/20) | 7.76 s
[Task 3/25] Current/Best: 14.86/ 16.83 GFLOPS | Progress: (12/20) | 9.49 s
[Task 3/25] Current/Best: 7.20/ 23.72 GFLOPS | Progress: (16/20) | 11.39 s
[Task 3/25] Current/Best: 12.15/ 23.72 GFLOPS | Progress: (20/20) | 15.97 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 4/25] Current/Best: 9.51/ 20.38 GFLOPS | Progress: (4/20) | 2.35 s
[Task 4/25] Current/Best: 6.69/ 20.38 GFLOPS | Progress: (8/20) | 6.76 s
[Task 4/25] Current/Best: 22.20/ 22.20 GFLOPS | Progress: (12/20) | 11.39 s
[Task 4/25] Current/Best: 16.23/ 22.20 GFLOPS | Progress: (16/20) | 13.69 s
[Task 4/25] Current/Best: 13.44/ 22.20 GFLOPS | Progress: (20/20) | 15.58 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 5/25] Current/Best: 8.94/ 10.03 GFLOPS | Progress: (4/20) | 2.57 s
[Task 5/25] Current/Best: 11.75/ 13.08 GFLOPS | Progress: (8/20) | 4.64 s
[Task 5/25] Current/Best: 11.38/ 17.97 GFLOPS | Progress: (12/20) | 7.75 s
[Task 5/25] Current/Best: 11.66/ 22.45 GFLOPS | Progress: (16/20) | 9.18 s
[Task 5/25] Current/Best: 11.96/ 22.45 GFLOPS | Progress: (20/20) | 11.02 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 6/25] Current/Best: 12.19/ 20.85 GFLOPS | Progress: (4/20) | 3.94 s
[Task 6/25] Current/Best: 18.97/ 20.85 GFLOPS | Progress: (8/20) | 5.72 s
[Task 6/25] Current/Best: 13.20/ 20.85 GFLOPS | Progress: (12/20) | 7.67 s
[Task 6/25] Current/Best: 19.96/ 20.85 GFLOPS | Progress: (16/20) | 9.91 s
[Task 6/25] Current/Best: 3.71/ 20.85 GFLOPS | Progress: (20/20) | 12.46 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 7/25] Current/Best: 11.26/ 12.69 GFLOPS | Progress: (4/20) | 3.53 s
[Task 7/25] Current/Best: 20.21/ 20.94 GFLOPS | Progress: (8/20) | 5.05 s
[Task 7/25] Current/Best: 15.85/ 20.94 GFLOPS | Progress: (12/20) | 6.97 s
[Task 7/25] Current/Best: 12.20/ 20.94 GFLOPS | Progress: (16/20) | 9.04 s
[Task 7/25] Current/Best: 6.36/ 21.67 GFLOPS | Progress: (20/20) | 11.51 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 8/25] Current/Best: 10.25/ 13.99 GFLOPS | Progress: (4/20) | 2.88 s
[Task 8/25] Current/Best: 10.24/ 13.99 GFLOPS | Progress: (8/20) | 7.64 s
[Task 8/25] Current/Best: 13.03/ 13.99 GFLOPS | Progress: (12/20) | 13.85 s
[Task 8/25] Current/Best: 18.75/ 18.75 GFLOPS | Progress: (16/20) | 15.92 s
[Task 8/25] Current/Best: 19.53/ 19.53 GFLOPS | Progress: (20/20) | 22.44 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 9/25] Current/Best: 14.19/ 15.33 GFLOPS | Progress: (4/20) | 11.92 s
[Task 9/25] Current/Best: 23.31/ 23.31 GFLOPS | Progress: (8/20) | 13.76 s
[Task 9/25] Current/Best: 7.43/ 23.31 GFLOPS | Progress: (12/20) | 16.16 s
[Task 9/25] Current/Best: 17.90/ 23.31 GFLOPS | Progress: (16/20) | 18.85 s
[Task 9/25] Current/Best: 8.96/ 23.31 GFLOPS | Progress: (20/20) | 26.65 s
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 10/25] Current/Best: 18.37/ 18.37 GFLOPS | Progress: (4/20) | 2.54 s
[Task 10/25] Current/Best: 15.63/ 18.37 GFLOPS | Progress: (8/20) | 4.16 s
[Task 10/25] Current/Best: 12.14/ 18.81 GFLOPS | Progress: (12/20) | 5.68 s
[Task 10/25] Current/Best: 19.11/ 20.21 GFLOPS | Progress: (16/20) | 6.79 s
[Task 10/25] Current/Best: 8.87/ 20.21 GFLOPS | Progress: (20/20
) | 8.32 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 11/25] Current/Best: 12.27/ 18.03 GFLOPS | Progress: (4/20) | 3.31 s
[Task 11/25] Current/Best: 16.86/ 18.03 GFLOPS | Progress: (8/20) | 6.04 s
[Task 11/25] Current/Best: 18.12/ 18.12 GFLOPS | Progress: (12/20) | 8.05 s
[Task 11/25] Current/Best: 13.25/ 21.16 GFLOPS | Progress: (16/20) | 10.77 s
[Task 11/25] Current/Best: 19.50/ 21.53 GFLOPS | Progress: (20/20) | 12.78 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 12/25] Current/Best: 7.79/ 18.32 GFLOPS | Progress: (4/20) | 5.35 s
[Task 12/25] Current/Best: 5.22/ 18.32 GFLOPS | Progress: (8/20) | 9.05 s
[Task 12/25] Current/Best: 18.91/ 18.91 GFLOPS | Progress: (12/20) | 11.07 s
[Task 12/25] Current/Best: 15.28/ 18.91 GFLOPS | Progress: (16/20) | 13.88 s
[Task 12/25] Current/Best: 15.16/ 18.91 GFLOPS | Progress: (20/20) | 15.79 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 13/25] Current/Best: 8.66/ 17.30 GFLOPS | Progress: (4/20) | 3.65 s
[Task 13/25] Current/Best: 15.60/ 20.94 GFLOPS | Progress: (8/20) | 6.11 s
[Task 13/25] Current/Best: 19.43/ 21.55 GFLOPS | Progress: (12/20) | 9.09 s
[Task 13/25] Current/Best: 12.21/ 21.55 GFLOPS | Progress: (16/20) | 12.47 s
[Task 13/25] Current/Best: 18.50/ 21.55 GFLOPS | Progress: (20/20) | 14.72 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 14/25] Current/Best: 13.60/ 13.60 GFLOPS | Progress: (4/20) | 3.23 s
[Task 14/25] Current/Best: 6.07/ 13.60 GFLOPS | Progress: (8/20) | 5.39 s
[Task 14/25] Current/Best: 20.09/ 20.09 GFLOPS | Progress: (12/20) | 7.93 s
[Task 14/25] Current/Best: 16.69/ 20.09 GFLOPS | Progress: (16/20) | 9.57 s Done.
+
[Task 14/25] Current/Best: 16.92/ 20.09 GFLOPS | Progress: (20/20) | 11.31 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 15/25] Current/Best: 16.15/ 17.62 GFLOPS | Progress: (4/20) | 2.65 s
[Task 15/25] Current/Best: 14.30/ 18.04 GFLOPS | Progress: (8/20) | 3.99 s
[Task 15/25] Current/Best: 10.34/ 22.32 GFLOPS | Progress: (12/20) | 6.10 s
[Task 15/25] Current/Best: 20.42/ 22.32 GFLOPS | Progress: (16/20) | 9.57 s
[Task 15/25] Current/Best: 9.70/ 22.32 GFLOPS | Progress: (20/20) | 10.60 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 16/25] Current/Best: 19.60/ 19.60 GFLOPS | Progress: (4/20) | 2.91 s
[Task 16/25] Current/Best: 3.04/ 19.60 GFLOPS | Progress: (8/20) | 4.54 s
[Task 16/25] Current/Best: 19.33/ 19.60 GFLOPS | Progress: (12/20) | 5.76 s
[Task 16/25] Current/Best: 17.66/ 19.60 GFLOPS | Progress: (16/20) |
7.12 s
[Task 16/25] Current/Best: 9.98/ 22.20 GFLOPS | Progress: (20/20) | 9.18 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 17/25] Current/Best: 13.45/ 18.79 GFLOPS | Progress: (4/20) | 4.67 s
[Task 17/25] Current/Best: 14.30/ 22.89 GFLOPS | Progress: (8/20) | 7.53 s
[Task 17/25] Current/Best: 16.92/ 22.89 GFLOPS | Progress: (12/20) | 9.58 s
[Task 17/25] Current/Best: 16.49/ 22.89 GFLOPS | Progress: (16/20) | 11.73 s
[Task 17/25] Current/Best: 10.01/ 22.89 GFLOPS | Progress: (20/20) | 13.86 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 18/25] Current/Best: 11.34/ 18.05 GFLOPS | Progress: (4/20) | 3.67 s
[Task 18/25] Current/Best: 10.49/ 18.05 GFLOPS | Progress: (8/20) | 7.12 s
[Task 18/25] Current/Best: 19.13/ 19.13 GFLOPS | Progress: (12/20) | 9.05 s
[Task 18/25] Current/Best: 9.92/ 19.13 GFLOPS | Progress: (16/20) | 12.71 s
[Task 18/25] Current/Best: 20.65/ 20.65 GFLOPS | Progress: (20/20) | 14.21 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 19/25] Current/Best: 6.69/ 20.17 GFLOPS | Progress: (4/20) | 6.08 s
[Task 19/25] Current/Best: 2.60/ 20.17 GFLOPS | Progress: (8/20) | 9.35 s
[Task 19/25] Current/Best: 19.19/ 21.29 GFLOPS | Progress: (12/20) | 12.17 s
[Task 19/25] Current/Best: 14.80/ 21.29 GFLOPS | Progress: (16/20) | 15.00 s
[Task 19/25] Current/Best: 2.70/ 23.11 GFLOPS | Progress: (20/20) | 17.83 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 20/25] Current/Best: 9.20/ 14.73 GFLOPS | Progress: (4/20) | 3.32 s Done.
Done.
-
[Task 20/25] Current/Best: 10.15/ 15.18 GFLOPS | Progress: (8/20) | 6.67 s
[Task 20/25] Current/Best: 2.32/ 16.83 GFLOPS | Progress: (12/20) | 10.64 s
[Task 20/25] Current/Best: 12.54/ 16.83 GFLOPS | Progress: (16/20) | 14.33 s
[Task 20/25] Current/Best: 12.14/ 22.26 GFLOPS | Progress: (20/20) | 16.39 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 6.39/ 17.46 GFLOPS | Progress: (4/20) | 3.18 s
[Task 21/25] Current/Best: 14.61/ 17.46 GFLOPS | Progress: (8/20) | 4.76 s
[Task 21/25] Current/Best: 1.61/ 17.46 GFLOPS | Progress: (12/20) | 6.91 s
[Task 21/25] Current/Best: 18.18/ 18.18 GFLOPS | Progress: (16/20) | 10.33 s
[Task 21/25] Current/Best: 4.47/ 18.18 GFLOPS | Progress: (20/20) | 17.39 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 2.71/ 17.03 GFLOPS | Progress: (4/20
) | 2.59 s
[Task 22/25] Current/Best: 8.69/ 20.35 GFLOPS | Progress: (8/20) | 4.57 s
[Task 22/25] Current/Best: 19.95/ 20.35 GFLOPS | Progress: (12/20) | 6.86 s
[Task 22/25] Current/Best: 15.38/ 20.35 GFLOPS | Progress: (16/20) | 8.88 s
[Task 22/25] Current/Best: 13.89/ 20.35 GFLOPS | Progress: (20/20) | 10.57 s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 17.70/ 20.94 GFLOPS | Progress: (4/20) | 3.15 s
[Task 23/25] Current/Best: 15.27/ 20.94 GFLOPS | Progress: (8/20) | 6.52 s
[Task 23/25] Current/Best: 21.09/ 21.61 GFLOPS | Progress: (12/20) | 8.36 s
[Task 23/25] Current/Best: 6.25/ 21.61 GFLOPS | Progress: (16/20) | 15.37 s
[Task 23/25] Current/Best: 7.93/ 21.61 GFLOPS | Progress: (20/20) | 19.57 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 8.54/ 8.54 GFLOPS | Progress: (4/20) | 11.73 s
[Task 24/25] Current/Best: 2.16/ 8.54 GFLOPS | Progress: (8/20) | 22.69 s
[Task 24/25] Current/Best: 4.54/ 8.54 GFLOPS | Progress: (12/20) | 34.16 s Done.
+
[Task 20/25] Current/Best: 10.44/ 14.73 GFLOPS | Progress: (8/20) | 6.79 s
[Task 20/25] Current/Best: 2.32/ 16.62 GFLOPS | Progress: (12/20) | 10.67 s
[Task 20/25] Current/Best: 12.43/ 16.62 GFLOPS | Progress: (16/20) | 14.31 s
[Task 20/25] Current/Best: 12.62/ 21.88 GFLOPS | Progress: (20/20) | 16.42 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 21/25] Current/Best: 6.36/ 17.72 GFLOPS | Progress: (4/20) | 3.21 s
[Task 21/25] Current/Best: 14.54/ 17.72 GFLOPS | Progress: (8/20) | 4.78 s
[Task 21/25] Current/Best: 1.61/ 17.72 GFLOPS | Progress: (12/20) | 6.94 s
[Task 21/25] Current/Best: 18.26/ 18.26 GFLOPS | Progress: (16/20) | 10.38 s
[Task 21/25] Current/Best: 4.47/ 18.26 GFLOPS | Progress: (20/20) | 17.54 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 22/25] Current/Best: 2.70/ 17.01 GFLOPS | Progress: (4/20
) | 2.68 s
[Task 22/25] Current/Best: 8.95/ 21.49 GFLOPS | Progress: (8/20) | 4.66 s
[Task 22/25] Current/Best: 19.46/ 21.49 GFLOPS | Progress: (12/20) | 6.97 s
[Task 22/25] Current/Best: 14.62/ 21.49 GFLOPS | Progress: (16/20) | 9.07 s
[Task 22/25] Current/Best: 13.12/ 21.49 GFLOPS | Progress: (20/20) | 10.75 s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 23/25] Current/Best: 17.05/ 20.28 GFLOPS | Progress: (4/20) | 3.25 s
[Task 23/25] Current/Best: 15.74/ 20.28 GFLOPS | Progress: (8/20) | 6.53 s
[Task 23/25] Current/Best: 20.73/ 21.47 GFLOPS | Progress: (12/20) | 8.37 s
[Task 23/25] Current/Best: 6.16/ 21.47 GFLOPS | Progress: (16/20) | 15.60 s
[Task 23/25] Current/Best: 7.55/ 21.47 GFLOPS | Progress: (20/20) | 19.86 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 24/25] Current/Best: 8.33/ 8.33 GFLOPS | Progress: (4/20) | 11.79 s
[Task 24/25] Current/Best: 3.44/ 8.33 GFLOPS | Progress: (8/20) | 23.01 s
[Task 24/25] Current/Best: 4.11/ 8.33 GFLOPS | Progress: (12/20) | 33.75 s Done.
Done.
-
[Task 24/25] Current/Best: 6.43/ 8.96 GFLOPS | Progress: (16/20) | 39.56 s
[Task 24/25] Current/Best: 3.38/ 8.98 GFLOPS | Progress: (20/20) | 45.49 s Done.
-
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 1.55/ 2.76 GFLOPS | Progress: (4/20) | 11.49 s
[Task 25/25] Current/Best: 5.67/ 8.33 GFLOPS | Progress: (8/20) | 22.69 s
[Task 25/25] Current/Best: 5.69/ 8.33 GFLOPS | Progress: (12/20) | 33.98 s
[Task 25/25] Current/Best: 5.84/ 8.76 GFLOPS | Progress: (16/20) | 35.83 s
[Task 25/25] Current/Best: 2.87/ 8.76 GFLOPS | Progress: (20/20) | 46.54 s
+
[Task 24/25] Current/Best: 7.13/ 8.48 GFLOPS | Progress: (16/20) | 39.49 s
[Task 24/25] Current/Best: 3.24/ 8.48 GFLOPS | Progress: (20/20) | 45.48 s Done.
+
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/20) | 0.00 s
[Task 25/25] Current/Best: 1.55/ 2.83 GFLOPS | Progress: (4/20) | 11.59 s
[Task 25/25] Current/Best: 5.65/ 7.68 GFLOPS | Progress: (8/20) | 22.87 s
[Task 25/25] Current/Best: 5.86/ 7.68 GFLOPS | Progress: (12/20) | 34.32 s
[Task 25/25] Current/Best: 5.78/ 8.86 GFLOPS | Progress: (16/20) | 36.25 s
[Task 25/25] Current/Best: 2.94/ 8.86 GFLOPS | Progress: (20/20) | 46.96 s
@@ -735,8 +735,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 412.4972258800062, 'median': 411.84960950004097, 'std': 1.7953834009500136}
- unoptimized: {'mean': 497.45479426998827, 'median': 497.9651370999818, 'std': 2.5633199724376263}
+ optimized: {'mean': 415.4814270199995, 'median': 415.33691914999054, 'std': 0.991975886786009}
+ unoptimized: {'mean': 496.82471173000977, 'median': 496.607584100002, 'std': 1.1306536165218921}
@@ -759,7 +759,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 10 minutes 12.165 seconds)
+ **Total running time of the script:** ( 10 minutes 18.648 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 5f42372a2..4f63ececb 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -269,7 +269,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.311e-07 secs/op
+ 1.278e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index cbefd68a1..a2c6f7c7c 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -262,7 +262,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0x18b92d40)), stage(b, placeholder(b, 0x21a8a550)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(mi [...]
+ [stage(a, placeholder(a, 0x21d54cf0)), stage(b, placeholder(b, 0x21d35c50)), stage(T_add, compute(T_add, body=[(a[ax0, ax1, ax2] + b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(min=0, ext=10))], reduce_axis=[], tag=broadcast, attrs={})), stage(T_multiply, compute(T_multiply, body=[(a[ax0, ax1, ax2]*b[ax1, ax2])], axis=[iter_var(ax0, range(min=0, ext=100)), iter_var(ax1, range(min=0, ext=10)), iter_var(ax2, range(mi [...]
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index c3e7521d5..8ffe21bc5 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,29 +5,29 @@
Computation times
=================
-**12:57.117** total execution time for **tutorial** files:
+**12:55.906** total execution time for **tutorial** files:
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 10:12.165 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``) | 10:18.648 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:01.032 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``) | 01:01.711 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 00:49.628 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``) | 00:42.133 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:28.034 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``) | 00:28.535 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:24.828 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``) | 00:23.539 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.688 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``) | 00:00.671 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.585 | 0.0 MB |
+| :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``) | 00:00.518 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.156 | 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_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``) | 00:00.152 | 0.0 MB |
+------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_tutorial_introduction.py` (``introduction.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_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 8cd034788..d667e6f89 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -289,7 +289,7 @@ helper function to run a profile of the TVM generated code.
.. code-block:: none
Numpy running time: 0.000008
- naive: 0.000007
+ naive: 0.000006
@@ -390,7 +390,7 @@ compile and run this new schedule with the parallel operation applied:
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- parallel: 0.000006
+ parallel: 0.000007
@@ -499,10 +499,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 8.26027999210055e-06 1.0
- naive 6.667e-06 0.8071154980673498
- parallel 6.0463e-06 0.7319727667563548
- vector 2.4526300000000003e-05 2.9691850667840476
+ numpy 8.145460001287574e-06 1.0
+ naive 5.970999999999999e-06 0.7330463840048503
+ parallel 6.9872e-06 0.8578029968713264
+ vector 2.46095e-05 3.021253556718701
@@ -923,7 +923,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.018088
+ Numpy running time: 0.019130
@@ -983,7 +983,7 @@ optimizations.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- none: 3.426103
+ none: 3.399759
@@ -1088,7 +1088,7 @@ schedule.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- blocking: 0.303000
+ blocking: 0.319590
@@ -1186,7 +1186,7 @@ already cache friendly from our previous optimizations.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- vectorization: 0.339759
+ vectorization: 0.350898
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1262,7 +1262,7 @@ more cache friendly.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- loop permutation: 0.115717
+ loop permutation: 0.120820
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1363,7 +1363,7 @@ optimized schedule.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- array packing: 0.109683
+ array packing: 0.109345
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1458,7 +1458,7 @@ to `C` when all the block results are ready.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- block caching: 0.108772
+ block caching: 0.111683
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1546,7 +1546,7 @@ of thread-level parallelization.
/workspace/python/tvm/driver/build_module.py:264: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead.
"target_host parameter is going to be deprecated. "
- parallelization: 0.141845
+ parallelization: 0.144316
@main = primfn(A_1: handle, B_1: handle, C_1: handle) -> ()
attr = {"from_legacy_te_schedule": True, "global_symbol": "main", "tir.noalias": True}
buffers = {A: Buffer(A_2: Pointer(float32), float32, [1048576], []),
@@ -1627,13 +1627,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.426102657 1.0
- blocking 0.30300038920000005 0.08843879461140153
- vectorization 0.3397592362 0.09916785053297368
- loop permutation 0.1157168019 0.033775053897925275
- array packing 0.10968294189999998 0.03201390993813411
- block caching 0.1087722851 0.03174811031355503
- parallelization 0.1418450866 0.04140129494082465
+ none 3.3997592064999997 1.0
+ blocking 0.3195900774 0.09400373908510218
+ vectorization 0.3508984549 0.10321273760480366
+ loop permutation 0.1208201829 0.03553786476083479
+ array packing 0.1093451409 0.03216261336712995
+ block caching 0.1116831393 0.03285030865905827
+ parallelization 0.1443160211 0.04244889485822472
@@ -1675,7 +1675,7 @@ the computation for specific platforms.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 1.032 seconds)
+ **Total running time of the script:** ( 1 minutes 1.711 seconds)
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
diff --git a/docs/commit_hash b/docs/commit_hash
index 28457d7e2..984e08112 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-dffc3108bbd406e7da49693533983adba634b19d
+0fdc0eab5199d1b6549d2b2f94c83d86d5545e81
diff --git a/docs/how_to/compile_models/from_darknet.html b/docs/how_to/compile_models/from_darknet.html
index aa42c58df..56516f4d8 100644
--- a/docs/how_to/compile_models/from_darknet.html
+++ b/docs/how_to/compile_models/from_darknet.html
@@ -550,7 +550,6 @@ class:['truck 0.9266'] left:471 right:83 top:689 bottom:169
class:['bicycle 0.9984'] left:111 right:113 top:577 bottom:447
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 0.533 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 c422d5bd7..8173807c2 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -403,7 +403,7 @@ to download the full example code</p>
<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.zipadaeafcc-a88f-44cc-b134-9bdbaa230378 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.zip6e7b1d3c-fe8c-4053-9c50-129954c44dad 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 b720e5578..84ba08427 100644
--- a/docs/how_to/compile_models/from_oneflow.html
+++ b/docs/how_to/compile_models/from_oneflow.html
@@ -408,43 +408,44 @@ python3 -m pip install -f https://release.oneflow.info <span class="nv">oneflow<
<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
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diff --git a/docs/how_to/compile_models/from_paddle.html b/docs/how_to/compile_models/from_paddle.html
index 456bf9806..ab9231109 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -469,7 +469,7 @@ A quick solution is</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 16.060 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.926 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 72b75bcde..866c1ec8e 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -390,9 +390,8 @@ be unstable.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
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</pre></div>
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diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index 27c9fa253..b41caa219 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -612,7 +612,7 @@ 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 1.191 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 3.713 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 3338671f8..e4d753c72 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>05:34.660</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>05:25.044</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 81%" />
@@ -312,43 +312,43 @@
</colgroup>
<tbody>
<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>01:16.060</p></td>
+<td><p>01:06.926</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>01:01.191</p></td>
+<td><p>01:03.713</p></td>
<td><p>0.0 MB</p></td>
</tr>
<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>01:00.533</p></td>
+<td><p>00:58.389</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>00:31.064</p></td>
+<td><p>00:31.414</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>00:25.581</p></td>
+<td><p>00:23.992</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="from_mxnet.html#sphx-glr-how-to-compile-models-from-mxnet-py"><span class="std std-ref">Compile MXNet Models</span></a> (<code class="docutils literal notranslate"><span class="pre">from_mxnet.py</span></code>)</p></td>
-<td><p>00:22.566</p></td>
+<td><p>00:22.971</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>00:22.531</p></td>
+<td><p>00:21.655</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>00:18.857</p></td>
+<td><p>00:19.110</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:13.887</p></td>
+<td><p>00:14.332</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>00:02.388</p></td>
+<td><p>00:02.543</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
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 a2f1933f8..99f052c97 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -629,7 +629,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.0016 15.7504 16.6340 15.6186 0.4231
+ 16.1169 16.0977 16.2810 15.9832 0.0971
</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 781f80e81..e2c7a82f8 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -412,16 +412,15 @@ be unstable.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>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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+ 3%|3 | 5.33M/170M [00:00<00:03, 55.8MB/s]
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+ 50%|##### | 85.7M/170M [00:00<00:00, 219MB/s]
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+ 95%|#########4| 161M/170M [00:00<00:00, 251MB/s]
+100%|##########| 170M/170M [00:00<00:00, 212MB/s]
/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3878: 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).
for i in range(dim)
/usr/local/lib/python3.7/dist-packages/torchvision/models/detection/anchor_utils.py:127: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
@@ -516,7 +515,7 @@ 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> ( 2 minutes 53.791 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 1.727 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 8978b2e38..9cb5829cf 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -453,9 +453,10 @@ training. Other models require a full post training calibration.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth" to /workspace/.cache/torch/hub/checkpoints/mobilenet_v2-b0353104.pth
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-100%|##########| 13.6M/13.6M [00:00<00:00, 51.3MB/s]
+ 6%|6 | 840k/13.6M [00:00<00:01, 8.59MB/s]
+ 53%|#####2 | 7.18M/13.6M [00:00<00:00, 42.7MB/s]
+ 87%|########7 | 11.8M/13.6M [00:00<00:00, 45.1MB/s]
+100%|##########| 13.6M/13.6M [00:00<00:00, 37.3MB/s]
</pre></div>
</div>
</div>
@@ -544,7 +545,7 @@ 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)
- 90.3514 90.2329 94.3861 90.0187 0.5025
+ 90.4412 90.3514 94.8088 90.1974 0.4659
</pre></div>
</div>
<div class="admonition note">
@@ -583,7 +584,7 @@ This includes support for the VNNI 8 bit dot product instruction (CascadeLake or
<div class="section" id="deploy-a-quantized-tflite-model">
<h2>Deploy a quantized TFLite Model<a class="headerlink" href="#deploy-a-quantized-tflite-model" title="Permalink to this headline">¶</a></h2>
<p>TODO</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 6.913 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 8.200 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-prequantized-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/fb8217c13f4351224c6cf3aacf1a87fc/deploy_prequantized.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_prequantized.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_prequantized_tflite.html b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
index f19eb4b02..256263030 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -546,7 +546,7 @@ 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)
- 118.8420 118.7439 124.5735 116.6642 1.1390
+ 121.1668 121.0708 127.5322 120.4744 0.7153
</pre></div>
</div>
<div class="admonition note">
@@ -574,7 +574,7 @@ network for ARM CPU</span></a>.</p></li>
</ul>
</div></blockquote>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 50.550 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 0.999 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-prequantized-tflite-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/56691c7a27d45da61d112276334640d3/deploy_prequantized_tflite.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_tflite.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_quantized.html b/docs/how_to/deploy_models/deploy_quantized.html
index 5c956108f..94880e2e5 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -485,7 +485,7 @@ for calibration. But the accuracy might be impacted.</p>
DeprecationWarning,
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 30.494 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 15.582 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/deploy_ssd_gluoncv.html b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
index 442333c92..3359cce15 100644
--- a/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
+++ b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
@@ -417,24 +417,22 @@ to your device.</p>
Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/ssd_512_resnet50_v1_voc-9c8b225a.zip...
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</pre></div>
</div>
<p>Create TVM runtime and do inference
@@ -477,7 +475,7 @@ Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from h
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
</div>
-<img src="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" srcset="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" alt="deploy ssd gluoncv" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 18.209 seconds)</p>
+<img src="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" srcset="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" alt="deploy ssd gluoncv" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 21.413 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-ssd-gluoncv-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/cccb17d28e5e8b2e94ea8cd5ec59f6ed/deploy_ssd_gluoncv.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_ssd_gluoncv.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 54f3c37b4..7094367b7 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
+++ b/docs/how_to/deploy_models/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>10:30.093</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>10:39.680</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 86%" />
@@ -312,31 +312,31 @@
</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>02:53.791</p></td>
+<td><p>03:01.727</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_ssd_gluoncv.html#sphx-glr-how-to-deploy-models-deploy-ssd-gluoncv-py"><span class="std std-ref">Deploy Single Shot Multibox Detector(SSD) model</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_ssd_gluoncv.py</span></code>)</p></td>
-<td><p>02:18.209</p></td>
+<td><p>02:21.413</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="deploy_prequantized_tflite.html#sphx-glr-how-to-deploy-models-deploy-prequantized-tflite-py"><span class="std std-ref">Deploy a Framework-prequantized Model with TVM - Part 3 (TFLite)</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_prequantized_tflite.py</span></code>)</p></td>
-<td><p>01:50.550</p></td>
+<td><p>02:00.999</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="deploy_quantized.html#sphx-glr-how-to-deploy-models-deploy-quantized-py"><span class="std std-ref">Deploy a Quantized Model on Cuda</span></a> (<code class="docutils literal notranslate"><span class="pre">deploy_quantized.py</span></code>)</p></td>
-<td><p>01:30.494</p></td>
+<td><p>01:15.582</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>01:06.913</p></td>
+<td><p>01:08.200</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>00:28.342</p></td>
+<td><p>00:29.473</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>00:21.787</p></td>
+<td><p>00:22.280</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 3f4e8ba78..2cf1f1a18 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -585,7 +585,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
<span class="n">module</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">params</span></a> <span class="o">=</span> <span class="n">get_mobilenet</span><span class="p">()</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip7d45ff99-f6ce-4514-8fb4-8609767e7dd5 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.zipf73a00b1-7787-4154-b92d-15edbd4f6b03 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 b80973069..1087f929c 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>00:38.599</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:40.520</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -312,15 +312,15 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="bring_your_own_datatypes.html#sphx-glr-how-to-extend-tvm-bring-your-own-datatypes-py"><span class="std std-ref">Bring Your Own Datatypes to TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">bring_your_own_datatypes.py</span></code>)</p></td>
-<td><p>00:35.574</p></td>
+<td><p>00:37.284</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>00:02.132</p></td>
+<td><p>00:02.292</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>00:00.888</p></td>
+<td><p>00:00.938</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="low_level_custom_pass.html#sphx-glr-how-to-extend-tvm-low-level-custom-pass-py"><span class="std std-ref">Writing a Customized Pass</span></a> (<code class="docutils literal notranslate"><span class="pre">low_level_custom_pass.py</span></code>)</p></td>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 38796c848..4cd9a809b 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -488,10 +488,10 @@ 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: 6454us [6454us] (45.65%; 45.65%)
-FoldScaleAxis: 7686us [6us] (54.35%; 54.35%)
- FoldConstant: 7679us [1589us] (54.31%; 99.92%)
- InferType: 6090us [6090us] (43.07%; 79.31%)
+InferType: 6992us [6992us] (45.96%; 45.96%)
+FoldScaleAxis: 8220us [6us] (54.04%; 54.04%)
+ FoldConstant: 8214us [1641us] (54.00%; 99.93%)
+ InferType: 6573us [6573us] (43.21%; 80.02%)
</pre></div>
</div>
</div>
@@ -513,10 +513,10 @@ 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: 6172us [6172us] (44.74%; 44.74%)
-FoldScaleAxis: 7623us [5us] (55.26%; 55.26%)
- FoldConstant: 7618us [1572us] (55.23%; 99.94%)
- InferType: 6046us [6046us] (43.83%; 79.37%)
+InferType: 6581us [6581us] (44.72%; 44.72%)
+FoldScaleAxis: 8135us [5us] (55.28%; 55.28%)
+ FoldConstant: 8130us [1663us] (55.25%; 99.94%)
+ InferType: 6467us [6467us] (43.95%; 79.55%)
</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 827fda60a..77bce58e2 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -537,7 +537,7 @@ 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: 37.096612 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 54.160311 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 5baf3738b..9455226da 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -879,7 +879,7 @@ 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: 7.545861 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 8.167091 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 90424a0f4..860653bed 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -434,8 +434,8 @@ 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: 0.018394
-Baseline: 3.408293
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.019787
+Baseline: 3.402191
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -495,7 +495,7 @@ 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: 0.300549
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.314941
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -562,7 +562,7 @@ 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: 0.337973
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.347885
</pre></div>
</div>
<p>Here is the generated IR after vectorization.</p>
@@ -623,7 +623,7 @@ 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: 0.122914
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.120919
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -706,7 +706,7 @@ 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: 0.110785
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.110538
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -792,7 +792,7 @@ 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: 0.112291
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.111790
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -882,7 +882,7 @@ write to C when all the block results are ready.</p>
<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: 0.145276
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.145566
</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 0ad65b2cd..a20b06fe9 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -303,7 +303,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-optimize-operators-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:34.483</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:35.019</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -312,15 +312,15 @@
</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>00:32.276</p></td>
+<td><p>00:32.696</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="opt_conv_tensorcore.html#sphx-glr-how-to-optimize-operators-opt-conv-tensorcore-py"><span class="std std-ref">How to optimize convolution using TensorCores</span></a> (<code class="docutils literal notranslate"><span class="pre">opt_conv_tensorcore.py</span></code>)</p></td>
-<td><p>00:01.216</p></td>
+<td><p>00:01.269</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="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>00:00.991</p></td>
+<td><p>00:01.054</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 186cb9b2d..3e262b3c8 100644
--- a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
+++ b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>05:07.789</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>05:19.961</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -312,27 +312,27 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_layer_cuda.html#sphx-glr-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py"><span class="std std-ref">Auto-scheduling a Convolution Layer for GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_layer_cuda.py</span></code>)</p></td>
-<td><p>02:32.144</p></td>
+<td><p>02:41.427</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>01:19.314</p></td>
+<td><p>01:20.914</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>00:42.501</p></td>
+<td><p>00:43.495</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_sparse_x86.html#sphx-glr-how-to-tune-with-autoscheduler-tune-sparse-x86-py"><span class="std std-ref">Auto-scheduling Sparse Matrix Multiplication on CPU with Custom Sketch Rule</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_sparse_x86.py</span></code>)</p></td>
-<td><p>00:17.240</p></td>
+<td><p>00:16.738</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_network_mali.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-mali-py"><span class="std std-ref">Auto-scheduling a Neural Network for mali GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_mali.py</span></code>)</p></td>
-<td><p>00:08.418</p></td>
+<td><p>00:08.699</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_network_arm.html#sphx-glr-how-to-tune-with-autoscheduler-tune-network-arm-py"><span class="std std-ref">Auto-scheduling a Neural Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_network_arm.py</span></code>)</p></td>
-<td><p>00:08.172</p></td>
+<td><p>00:08.687</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html b/docs/how_to/tune_with_autoscheduler/tune_conv2d_layer_cuda.html
index 13b4bcb71..798457c5d 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
@@ -980,7 +980,7 @@ cooperative fetching, unrolling and operator fusion.</p>
<span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.354 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.366 ms
</pre></div>
</div>
</div>
@@ -1543,7 +1543,7 @@ In the example below we resume the status and do more 5 trials.</p>
Get devices for measurement successfully!
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 32.144 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 41.427 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-conv2d-layer-cuda-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/e3e540f3b477c0c52d8eb73e674e8ffd/tune_conv2d_layer_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_conv2d_layer_cuda.py</span></code></a></p>
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 abc33f2f3..c2d148313 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -882,7 +882,7 @@ 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)
- 9.8039 9.7978 9.8257 9.7883 0.0159
+ 10.0391 10.0250 10.1017 9.9904 0.0465
</pre></div>
</div>
</div>
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 151434e8f..035a3325b 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -901,7 +901,7 @@ 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)
- 744.2871 743.5306 746.4699 742.8608 1.5675
+ 763.1815 763.3894 763.4273 762.7276 0.3213
</pre></div>
</div>
</div>
@@ -923,7 +923,7 @@ to learn how to use the RPC Tracker and RPC Server.
To use the RPC Tracker in auto-scheduler, replace the runner in <code class="code docutils literal notranslate"><span class="pre">TuningOptions</span></code>
with <a class="reference internal" href="../../reference/api/python/auto_scheduler.html#tvm.auto_scheduler.RPCRunner" title="tvm.auto_scheduler.RPCRunner"><code class="xref any py py-class docutils literal notranslate"><span class="pre">auto_scheduler.RPCRunner</span></code></a>.</p></li>
</ol>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 19.314 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 20.914 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-x86-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/e416b94ca1090b0897c0f6e0df95b911/tune_network_x86.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">tune_network_x86.py</span></code></a></p>
diff --git a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
index 5ac8d61b3..de6303ab4 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
@@ -601,79 +601,29 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
placeholder_4: Buffer(placeholder_14: Pointer(float32), float32, [65536], []),
compute: Buffer(compute_2: Pointer(float32), float32, [65536], [])}
buffer_map = {placeholder_5: placeholder, placeholder_6: placeholder_1, placeholder_7: placeholder_2, placeholder_8: placeholder_3, placeholder_9: placeholder_4, compute_1: compute}
- preflattened_buffer_map = {compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_8: placeholder_15: Buffer(placeholder_13, int32, [33], []), placeholder_5: placeholder_16: Buffer(placeholder_10, float32, [128, 256], []), placeholder_7: placeholder_17: Buffer(placeholder_12, int32, [4916], []), placeholder_6: placeholder_18: Buffer(placeholder_11, float32, [4916, 16, 1], []), placeholder_9: placeholder_19: Buffer(placeholder_14, float32, [128, 512], [])} {
- for (i0.outer.i1.outer.fused: int32, 0, 16) "parallel" {
- allocate(compute_4: Pointer(global float32), float32, [4096]), storage_scope = global {
- for (i.outer.inner: int32, 0, 4) {
- for (nb_j.inner: int32, 0, 2) {
- for (i.inner.init: int32, 0, 32) {
- let cse_var_1: int32 = (((i.outer.inner*1024) + (i.inner.init*32)) + (nb_j.inner*16))
- {
- compute_5: Buffer(compute_4, float32, [4096], [])[cse_var_1] = 0f32
- compute_5[(cse_var_1 + 1)] = 0f32
- compute_5[(cse_var_1 + 2)] = 0f32
- compute_5[(cse_var_1 + 3)] = 0f32
- compute_5[(cse_var_1 + 4)] = 0f32
- compute_5[(cse_var_1 + 5)] = 0f32
- compute_5[(cse_var_1 + 6)] = 0f32
- compute_5[(cse_var_1 + 7)] = 0f32
- compute_5[(cse_var_1 + 8)] = 0f32
- compute_5[(cse_var_1 + 9)] = 0f32
- compute_5[(cse_var_1 + 10)] = 0f32
- compute_5[(cse_var_1 + 11)] = 0f32
- compute_5[(cse_var_1 + 12)] = 0f32
- compute_5[(cse_var_1 + 13)] = 0f32
- compute_5[(cse_var_1 + 14)] = 0f32
- compute_5[(cse_var_1 + 15)] = 0f32
- }
+ preflattened_buffer_map = {placeholder_5: placeholder_15: Buffer(placeholder_10, float32, [128, 256], []), compute_1: compute_3: Buffer(compute_2, float32, [128, 512], []), placeholder_7: placeholder_16: Buffer(placeholder_12, int32, [4916], []), placeholder_8: placeholder_17: Buffer(placeholder_13, int32, [33], []), placeholder_9: placeholder_18: Buffer(placeholder_14, float32, [128, 512], []), placeholder_6: placeholder_19: Buffer(placeholder_11, float32, [4916, 16, 1], [])} {
+ for (i0.outer.i1.outer.fused: int32, 0, 256) "parallel" {
+ allocate(compute_4: Pointer(global float32), float32, [256]), storage_scope = global {
+ for (nb_j.inner: int32, 0, 2) {
+ for (i.inner.init: int32, 0, 8) {
+ for (j.init: int32, 0, 16) {
+ compute_5: Buffer(compute_4, float32, [256], [])[(((i.inner.init*32) + (nb_j.inner*16)) + j.init)] = 0f32
}
- for (elem_idx: int32, 0, let cse_var_2: int32 = ((i0.outer.i1.outer.fused*2) + nb_j.inner) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
- for (i.inner: int32, 0, 32) {
- let cse_var_21: int32 = (elem_idx*16)
- let cse_var_20: int32 = ((i0.outer.i1.outer.fused*2) + nb_j.inner)
- let cse_var_19: int32 = ((i.outer.inner*8192) + (i.inner*256))
- let cse_var_18: int32 = (((i.outer.inner*1024) + (i.inner*32)) + (nb_j.inner*16))
- let cse_var_17: int32 = (cse_var_18 + 9)
- let cse_var_16: int32 = (cse_var_18 + 8)
- let cse_var_15: int32 = (cse_var_18 + 7)
- let cse_var_14: int32 = (cse_var_18 + 6)
- let cse_var_13: int32 = (cse_var_18 + 5)
- let cse_var_12: int32 = (cse_var_18 + 4)
- let cse_var_11: int32 = (cse_var_18 + 3)
- let cse_var_10: int32 = (cse_var_18 + 2)
- let cse_var_9: int32 = (cse_var_18 + 15)
- let cse_var_8: int32 = (cse_var_18 + 14)
- let cse_var_7: int32 = (cse_var_18 + 13)
- let cse_var_6: int32 = (cse_var_18 + 12)
- let cse_var_5: int32 = (cse_var_18 + 11)
- let cse_var_4: int32 = (cse_var_18 + 10)
- let cse_var_3: int32 = (cse_var_18 + 1)
- {
- compute_5[cse_var_18] = (compute_5[cse_var_18] + (placeholder_1[((placeholder_3[cse_var_20]*16) + cse_var_21)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_3] = (compute_5[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 1)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_10] = (compute_5[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 2)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_11] = (compute_5[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 3)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_12] = (compute_5[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 4)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_13] = (compute_5[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 5)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_14] = (compute_5[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 6)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_15] = (compute_5[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 7)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_16] = (compute_5[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 8)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_17] = (compute_5[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 9)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_4] = (compute_5[cse_var_4] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 10)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_5] = (compute_5[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 11)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_6] = (compute_5[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 12)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_7] = (compute_5[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 13)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_8] = (compute_5[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 14)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- compute_5[cse_var_9] = (compute_5[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_20]*16) + cse_var_21) + 15)]*max(placeholder[(cse_var_19 + placeholder_2[(placeholder_3[cse_var_20] + elem_idx)])], 0f32)))
- }
+ }
+ for (elem_idx: int32, 0, let cse_var_1: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_3[(cse_var_1 + 1)] - placeholder_3[cse_var_1])) {
+ for (i.inner: int32, 0, 8) {
+ for (j: int32, 0, 16) {
+ let cse_var_3: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_2: int32 = (((i.inner*32) + (nb_j.inner*16)) + j)
+ compute_5[cse_var_2] = (compute_5[cse_var_2] + (placeholder_1[(((placeholder_3[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 16)*2048) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_3] + elem_idx)])], 0f32)))
}
}
}
}
- for (i0.inner: int32, 0, 128) {
+ for (i0.inner: int32, 0, 8) {
for (i1.inner: int32, 0, 32) {
- let cse_var_22: int32 = (((i0.inner*512) + (i0.outer.i1.outer.fused*32)) + i1.inner)
- compute[cse_var_22] = max((compute_5[((i0.inner*32) + i1.inner)] + placeholder_4[cse_var_22]), 0f32)
+ let cse_var_4: int32 = ((((floordiv(i0.outer.i1.outer.fused, 16)*4096) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32)) + i1.inner)
+ compute[cse_var_4] = max((compute_5[((i0.inner*32) + i1.inner)] + placeholder_4[cse_var_4]), 0f32)
}
}
}
@@ -712,7 +662,7 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
<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: 1.736 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.589 ms
</pre></div>
</div>
<div class="admonition note">
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 404647844..326e73822 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>00:42.962</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:43.862</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
@@ -312,22 +312,22 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="tune_conv2d_cuda.html#sphx-glr-how-to-tune-with-autotvm-tune-conv2d-cuda-py"><span class="std std-ref">Tuning High Performance Convolution on NVIDIA GPUs</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_conv2d_cuda.py</span></code>)</p></td>
-<td><p>00:42.930</p></td>
+<td><p>00:43.829</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_x86.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-x86-py"><span class="std std-ref">Auto-tuning a Convolutional Network for x86 CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_x86.py</span></code>)</p></td>
-<td><p>00:00.019</p></td>
+<td><p>00:00.020</p></td>
<td><p>0.0 MB</p></td>
</tr>
<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>
<td><p>00:00.005</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_arm.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-arm-py"><span class="std std-ref">Auto-tuning a Convolutional Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_arm.py</span></code>)</p></td>
-<td><p>00:00.005</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tune_relay_mobile_gpu.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-mobile-gpu-py"><span class="std std-ref">Auto-tuning a Convolutional Network for Mobile GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_mobile_gpu.py</span></code>)</p></td>
+<td><p>00:00.004</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_mobile_gpu.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-mobile-gpu-py"><span class="std std-ref">Auto-tuning a Convolutional Network for Mobile GPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_mobile_gpu.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tune_relay_arm.html#sphx-glr-how-to-tune-with-autotvm-tune-relay-arm-py"><span class="std std-ref">Auto-tuning a Convolutional Network for ARM CPU</span></a> (<code class="docutils literal notranslate"><span class="pre">tune_relay_arm.py</span></code>)</p></td>
<td><p>00:00.004</p></td>
<td><p>0.0 MB</p></td>
</tr>
diff --git a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
index e4c17122c..6cb3ea23c 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -1145,8 +1145,8 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 4, 32]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 1, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2885496
-No: 6 GFLOPS: 42.43/42.43 result: MeasureResult(costs=(0.0054557639473684204,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.631316900253296, timestamp=1655487731.6056771) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
-No: 7 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 6 GFLOPS: 42.38/42.38 result: MeasureResult(costs=(0.005462229789473684,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.6179249286651611, timestamp=1655495728.4610019) [('tile_f', [-1, 1, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,3754080
+No: 7 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1269,7 +1269,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 16, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 256, 1]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6225319
-No: 8 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 8 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1392,7 +1392,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 32]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 8, 64]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,943546
-No: 9 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 9 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1515,7 +1515,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 4, 16, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 16, 32]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2868708
-No: 10 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 10 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 142, in build
res = future.result()
File "/usr/lib/python3.7/concurrent/futures/_base.py", line 435, in result
@@ -1533,7 +1533,7 @@ No: 10 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
TimeoutError
[('tile_f', [-1, 32, 2, 4]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 4, 2]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4691833
-No: 11 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 11 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1656,7 +1656,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 2, 64]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,1042124
-No: 12 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 12 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1779,7 +1779,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 32, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 32, 16]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,10013405
-No: 13 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 13 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -1902,7 +1902,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 8, 8, 2]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 1, 7, 1]), ('tile_rc', [-1, 4, 32]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6732082
-No: 14 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 14 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2025,7 +2025,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 4, 32]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 1, 1, 1]), ('tile_rc', [-1, 4, 128]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 1)],None,7536735
-No: 15 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 15 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2148,7 +2148,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 4]), ('tile_y', [-1, 1, 1, 7]), ('tile_x', [-1, 1, 1, 7]), ('tile_rc', [-1, 128, 4]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 1, 1]), ('auto_unroll_max_step', 0), ('unroll_explicit', 0)],None,482121
-No: 16 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 16 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2271,7 +2271,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 2, 1, 16]), ('tile_y', [-1, 1, 7, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 32, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 512), ('unroll_explicit', 0)],None,2824525
-No: 17 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 17 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2394,7 +2394,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 64, 1, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 8, 8]), ('tile_ry', [-1, 1, 3]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 0)],None,4559286
-No: 18 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 18 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 588, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 540, in _build_func_common
@@ -2517,7 +2517,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 871, in verify_pass
raise InstantiationError("Skipped because of invalid gpu kernel")
tvm.autotvm.task.space.InstantiationError: Skipped because of invalid gpu kernel [('tile_f', [-1, 1, 32, 16]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 512]), ('tile_ry', [-1, 3, 1]), ('tile_rx', [-1, 3, 1]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9677544
-No: 19 GFLOPS: 0.00/42.43 result: Traceback (most recent call last):
+No: 19 GFLOPS: 0.00/42.38 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 738, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 702, in run_through_rpc
@@ -2605,7 +2605,7 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007fd388d74fa2
+ 12: 0x00007f9edb78efa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2670,7 +2670,7 @@ Traceback (most recent call last):
21: _PyFunction_FastCallKeywords
20: _PyEval_EvalFrameDefault
19: _PyFunction_FastCall [('tile_f', [-1, 8, 2, 16]), ('tile_y', [-1, 7, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 1, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 0), ('unroll_explicit', 1)],None,6390073
-No: 20 GFLOPS: 144.87/144.87 result: MeasureResult(costs=(0.0015980323899999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4396235942840576, timestamp=1655487758.0288036) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
+No: 20 GFLOPS: 143.39/143.39 result: MeasureResult(costs=(0.0016145025499999998,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4372198581695557, timestamp=1655495754.351655) [('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
</pre></div>
</div>
<p>Finally we can inspect the best config from log file, check correctness,
@@ -2711,7 +2711,7 @@ and measure running time.</p>
Best config:
[('tile_f', [-1, 1, 4, 1]), ('tile_y', [-1, 1, 1, 1]), ('tile_x', [-1, 7, 1, 1]), ('tile_rc', [-1, 4, 1]), ('tile_ry', [-1, 1, 1]), ('tile_rx', [-1, 1, 3]), ('auto_unroll_max_step', 1500), ('unroll_explicit', 1)],None,9881539
Finish loading 20 records
-Time cost of this operator: 0.002035
+Time cost of this operator: 0.001995
</pre></div>
</div>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autotvm-tune-conv2d-cuda-py">
diff --git a/docs/how_to/work_with_microtvm/micro_autotune.html b/docs/how_to/work_with_microtvm/micro_autotune.html
index 12f2b4d10..b9e796f44 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -559,10 +559,10 @@ the tuned operator.</p>
########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 318.7 98.757 (1, 2, 10, 10, 3) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.079 0.954 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.932 0.289 (1, 1, 10, 10, 3) 1 1
-Total_time - 322.711 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 317.6 98.756 (1, 2, 10, 10, 3) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.076 0.956 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.924 0.287 (1, 1, 10, 10, 3) 1 1
+Total_time - 321.6 - - - -
</pre></div>
</div>
</div>
@@ -615,10 +615,10 @@ Total_time -
########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 86.35 96.983 (1, 6, 10, 10, 1) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.784 2.004 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.902 1.013 (1, 1, 10, 10, 3) 1 1
-Total_time - 89.036 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 192.7 98.583 (1, 1, 10, 10, 6) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.952 0.999 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.817 0.418 (1, 3, 10, 10, 1) 1 1
+Total_time - 195.469 - - - -
</pre></div>
</div>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-autotune-py">
diff --git a/docs/how_to/work_with_microtvm/micro_train.html b/docs/how_to/work_with_microtvm/micro_train.html
index ce0eda5df..0b6eedad5 100644
--- a/docs/how_to/work_with_microtvm/micro_train.html
+++ b/docs/how_to/work_with_microtvm/micro_train.html
@@ -490,7 +490,7 @@ 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>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>'/tmp/tmpjl_tmotx/images/random'
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>'/tmp/tmpswoy7eqf/images/random'
</pre></div>
</div>
</div>
@@ -550,8 +550,8 @@ 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>
-<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], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmpjl_tmotx/images/target contains 8144 images
-/tmp/tmpjl_tmotx/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], [1.0, 0.0], [0.0, 1.0], [1.0, 0.0]" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/tmp/tmpswoy7eqf/images/target contains 8144 images
+/tmp/tmpswoy7eqf/images/random contains 5000 images
</pre></div>
</div>
</div>
@@ -663,13 +663,13 @@ 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 - 55s - loss: 0.2093 - accuracy: 0.9261 - val_loss: 0.1326 - val_accuracy: 0.9573
+328/328 - 55s - loss: 0.2427 - accuracy: 0.9199 - val_loss: 0.1533 - val_accuracy: 0.9554
Epoch 2/3
-328/328 - 52s - loss: 0.0967 - accuracy: 0.9642 - val_loss: 0.1191 - val_accuracy: 0.9630
+328/328 - 53s - loss: 0.1020 - accuracy: 0.9620 - val_loss: 0.1102 - val_accuracy: 0.9630
Epoch 3/3
-328/328 - 52s - loss: 0.0622 - accuracy: 0.9771 - val_loss: 0.1048 - val_accuracy: 0.9664
+328/328 - 53s - loss: 0.0697 - accuracy: 0.9721 - val_loss: 0.1047 - val_accuracy: 0.9645
-<keras.callbacks.History object at 0x7f50f6406dd0>
+<keras.callbacks.History object at 0x7fe528b0cc10>
</pre></div>
</div>
</div>
@@ -931,7 +931,7 @@ 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>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 13.398 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 4 minutes 28.356 seconds)</p>
<div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-work-with-microtvm-micro-train-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/b52cec46baf4f78d6bcd94cbe269c8a6/micro_train.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_train.py</span></code></a></p>
diff --git a/docs/how_to/work_with_microtvm/sg_execution_times.html b/docs/how_to/work_with_microtvm/sg_execution_times.html
index 17f0fe186..8bd7802f8 100644
--- a/docs/how_to/work_with_microtvm/sg_execution_times.html
+++ b/docs/how_to/work_with_microtvm/sg_execution_times.html
@@ -303,7 +303,7 @@
<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>
-<p><strong>05:58.044</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
+<p><strong>05:15.643</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -312,15 +312,15 @@
</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">Training Vision Models for microTVM on Arduino</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_train.py</span></code>)</p></td>
-<td><p>05:13.398</p></td>
+<td><p>04:28.356</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="micro_autotune.html#sphx-glr-how-to-work-with-microtvm-micro-autotune-py"><span class="std std-ref">Autotuning with microTVM</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_autotune.py</span></code>)</p></td>
-<td><p>00:41.211</p></td>
+<td><p>00:43.771</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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">microTVM with TFLite Models</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_tflite.py</span></code>)</p></td>
-<td><p>00:03.435</p></td>
+<td><p>00:03.516</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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">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 022606ceb..2d9edc100 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -303,7 +303,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-relay-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:05.612</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:11.558</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -312,11 +312,11 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="using_external_lib.html#sphx-glr-how-to-work-with-relay-using-external-lib-py"><span class="std std-ref">Using External Libraries in Relay</span></a> (<code class="docutils literal notranslate"><span class="pre">using_external_lib.py</span></code>)</p></td>
-<td><p>00:04.359</p></td>
+<td><p>00:10.012</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="build_gcn.html#sphx-glr-how-to-work-with-relay-build-gcn-py"><span class="std std-ref">Building a Graph Convolutional Network</span></a> (<code class="docutils literal notranslate"><span class="pre">build_gcn.py</span></code>)</p></td>
-<td><p>00:01.247</p></td>
+<td><p>00:01.540</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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 282eb6af1..ed35a451e 100644
--- a/docs/how_to/work_with_schedules/intrin_math.html
+++ b/docs/how_to/work_with_schedules/intrin_math.html
@@ -496,7 +496,7 @@ 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 0x7f504905eb90>
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><function my_cuda_math_rule at 0x7fe530d6a560>
</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 e312c31bd..a20173805 100644
--- a/docs/how_to/work_with_schedules/sg_execution_times.html
+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -303,7 +303,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:03.522</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:04.103</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 83%" />
@@ -312,35 +312,35 @@
</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>
-<td><p>00:01.769</p></td>
+<td><p>00:01.902</p></td>
<td><p>0.0 MB</p></td>
</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>
-<td><p>00:00.610</p></td>
+<td><p>00:00.980</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="scan.html#sphx-glr-how-to-work-with-schedules-scan-py"><span class="std std-ref">Scan and Recurrent Kernel</span></a> (<code class="docutils literal notranslate"><span class="pre">scan.py</span></code>)</p></td>
-<td><p>00:00.489</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
+<td><p>00:00.529</p></td>
<td><p>0.0 MB</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal" href="reduction.html#sphx-glr-how-to-work-with-schedules-reduction-py"><span class="std std-ref">Reduction</span></a> (<code class="docutils literal notranslate"><span class="pre">reduction.py</span></code>)</p></td>
-<td><p>00:00.485</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="scan.html#sphx-glr-how-to-work-with-schedules-scan-py"><span class="std std-ref">Scan and Recurrent Kernel</span></a> (<code class="docutils literal notranslate"><span class="pre">scan.py</span></code>)</p></td>
+<td><p>00:00.516</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="extern_op.html#sphx-glr-how-to-work-with-schedules-extern-op-py"><span class="std std-ref">External Tensor Functions</span></a> (<code class="docutils literal notranslate"><span class="pre">extern_op.py</span></code>)</p></td>
-<td><p>00:00.098</p></td>
+<td><p>00:00.101</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="schedule_primitives.html#sphx-glr-how-to-work-with-schedules-schedule-primitives-py"><span class="std std-ref">Schedule Primitives in TVM</span></a> (<code class="docutils literal notranslate"><span class="pre">schedule_primitives.py</span></code>)</p></td>
-<td><p>00:00.033</p></td>
+<td><p>00:00.034</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>00:00.025</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="tuple_inputs.html#sphx-glr-how-to-work-with-schedules-tuple-inputs-py"><span class="std std-ref">Compute and Reduce with Tuple Inputs</span></a> (<code class="docutils literal notranslate"><span class="pre">tuple_inputs.py</span></code>)</p></td>
-<td><p>00:00.012</p></td>
+<td><p>00:00.013</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/work_with_schedules/tensorize.html b/docs/how_to/work_with_schedules/tensorize.html
index 0a4e6c4b4..2e6b3811b 100644
--- a/docs/how_to/work_with_schedules/tensorize.html
+++ b/docs/how_to/work_with_schedules/tensorize.html
@@ -552,7 +552,7 @@ The importing needs to happen before the tensorized GEMV being executed.</p>
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C}
preflattened_buffer_map = {A_1: A_3: Buffer(A_2, float32, [1024, 64], []), B_1: B_3: Buffer(B_2, float32, [512, 64], []), C_1: C_3: Buffer(C_2, float32, [1024, 512], [])} {
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+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpzc_fl_hs/input0.cc'\nsource_filename = \"/tmp/tmpzc_fl_hs/input0.cc\"\ntarget datalayout = \"e-m:e-i64:64-f80:128-n8:16:32:64-S128\"\ntarget triple = \"x86_64-pc-linux-gnu\"\n\n; Function Attrs: noinline nounwind optnone uwtable\ndefine dso_local i32 @gemv_update(float*, float*, float*, i32, i32, i32) #0 {\n %7 = allo [...]
for (i, 0, 1024) {
for (j.outer: int32, 0, 32) {
@tir.call_extern("gemv_update", @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), C_2, ((i*512) + (j.outer*16)), 16, 2, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), A_2, (i*64), 64, 1, dtype=handle), @tir.tvm_access_ptr(@tir.type_annotation(, dtype=float32), B_2, (j.outer*1024), 1024, 1, dtype=handle), 16, 64, 64, dtype=int32)
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index 59df59907..c8a7fcc29 100644
--- a/docs/reference/api/doxygen/apply__history__best_8h_source.html
+++ b/docs/reference/api/doxygen/apply__history__best_8h_source.html
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<div class="ttc" id="classtvm_1_1AttrVisitor_html"><div class="ttname"><a href="classtvm_1_1AttrVisitor.html">tvm::AttrVisitor</a></div><div class="ttdoc">Visitor class to get the attributes of an AST/IR node. The content is going to be called for each fie...</div><div class="ttdef"><b>Definition:</b> reflection.h:52</div></div>
<div class="ttc" id="tensor_8h_html"><div class="ttname"><a href="tensor_8h.html">tensor.h</a></div><div class="ttdoc">Dataflow tensor object. </div></div>
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+<div class="ttc" id="classtvm_1_1meta__schedule_1_1Database_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1Database.html">tvm::meta_schedule::Database</a></div><div class="ttdoc">Managed reference to DatabaseNode. </div><div class="ttdef"><b>Definition:</b> database.h:314</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Array_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Array.html">tvm::runtime::Array</a></div><div class="ttdoc">Array, container representing a contiguous sequence of ObjectRefs. </div><div class="ttdef"><b>Definition:</b> array.h:270</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1ApplyHistoryBestNode_html_a6be4c52d4ff271c11d2f2daf53861778"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1ApplyHistoryBestNode.html#a6be4c52d4ff271c11d2f2daf53861778">tvm::meta_schedule::ApplyHistoryBestNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> apply_history_best.h:52</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1String_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html">tvm::runtime::String</a></div><div class="ttdoc">Reference to string objects. </div><div class="ttdef"><b>Definition:</b> string.h:129</div></div>
diff --git a/docs/reference/api/doxygen/classes.html b/docs/reference/api/doxygen/classes.html
index 5b60a4a52..043f338b0 100644
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<tr><td rowspan="2" valign="bottom"><a name="letter_a"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  a  </div></td></tr></table>
</td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ConvWinogradWeightTransformAttrs.html">ConvWinogradWeightTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1support_1_1Span_1_1iterator__base.html">Span::iterator_base</a> (<a class="el" href="namespacetvm_1_1support.html">tvm::support</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__schedu [...]
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-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AccessAnalyzer.html">AccessAnalyzer</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1CostModel.html">CostModel</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1auto__scheduler_1_1Atta [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AccessAnalyzerNode.html">AccessAnalyzerNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1CostModel.html">CostModel</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1Iter [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AdaptivePool1DAttrs.html">AdaptivePool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1CostModelNode.html">CostModelNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMapExprNode.html">Ite [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AdaptivePool2DAttrs.html">AdaptivePool2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1CostModelNode.html">CostModelNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMapResult.html">It [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1CorrelationAttrs.html">CorrelationAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1IteratorNode.html">IteratorNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1PReluAttrs.html">PReluAttrs</ [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AccessAnalyzer.html">AccessAnalyzer</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1CostModel.html">CostModel</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1auto__scheduler_1_1A [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AccessAnalyzerNode.html">AccessAnalyzerNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1CostModel.html">CostModel</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMap [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AdaptivePool1DAttrs.html">AdaptivePool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1CostModelNode.html">CostModelNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMapExprNode.html">Ite [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AdaptivePool2DAttrs.html">AdaptivePool2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1CostModelNode.html">CostModelNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMapResult.html">It [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AdaptivePool3DAttrs.html">AdaptivePool3DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1CountNode.html">CountNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMapResultNod [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Add.html">Add</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1CropAndResizeAttrs.html">CropAndResizeAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMark.html">IterMark</a> (<a class="el" href="namespacetvm_1_1arith.html">tv [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AddNode.html">AddNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_d"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  d  </div></td></tr></table>
@@ -131,8 +131,8 @@ $(function() {
<tr><td valign="top"><a class="el" href="structtvm_1_1detail_1_1AttrInitEntry.html">AttrInitEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1EinsumAttrs.html">EinsumAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MatchBufferRegionNode.html">MatchBufferRegionNode</a> (<a class=" [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrInitVisitor.html">AttrInitVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1EnvFunc.html">EnvFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1MatchNode.html">MatchNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>) [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrNonDefaultVisitor.html">AttrNonDefaultVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1EnvFuncNode.html">EnvFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MatmulAttrs.html">MatmulAttrs</a> (<a class="el" href="namespacetvm_1_1re [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1detail_1_1AttrNopEntry.html">AttrNopEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EQ.html">EQ</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html">MatrixSetDiagAttrs</a> (<a class="el" href="namespacetvm_1_1rela [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrNormalVisitor.html">AttrNormalVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EQNode.html">EQNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Max.html">Max</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</ [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1detail_1_1AttrNopEntry.html">AttrNopEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EQ.html">EQ</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html">MatrixSetDiagAttrs</a> (<a class="el" href="namespacetvm_1_1rela [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrNormalVisitor.html">AttrNormalVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EQNode.html">EQNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Max.html">Max</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</ [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AttrPattern.html">AttrPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1ErrorBuilder.html">ErrorBuilder</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MaxNode.html">MaxNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)  [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AttrPatternNode.html">AttrPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1ErrorReporter.html">ErrorReporter</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool1DAttrs.html">MaxPool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.h [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1AttrRegistry.html">AttrRegistry</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Evaluate.html">Evaluate</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool2DAttrs.html">MaxPool2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)&# [...]
@@ -177,15 +177,15 @@ $(function() {
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Block.html">Block</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1FloorModNode.html">FloorModNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Mul.html">Mul</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)    [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1tir_1_1BlockInfo.html">BlockInfo</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowFusedSplitStep.html">FollowFusedSplitStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MulNode.html">MulNode</a> (<a class= [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockNode.html">BlockNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowFusedSplitStepNode.html">FollowFusedSplitStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MultiBoxPriorAttrs.html">M [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRealize.html">BlockRealize</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowSplitStep.html">FollowSplitStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html">MultiB [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRealizeNode.html">BlockRealizeNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowSplitStepNode.html">FollowSplitStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1Mutator.html"> [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRealize.html">BlockRealize</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowSplitStep.html">FollowSplitStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html">MultiB [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRealizeNode.html">BlockRealizeNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1FollowSplitStepNode.html">FollowSplitStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1Mutator.html"> [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRV.html">BlockRV</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1For.html">For</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1MutatorNode.html">MutatorNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::me [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockRVNode.html">BlockRVNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ForNode.html">ForNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_n"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  n &# [...]
</td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1RunnerInput.html">RunnerInput</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1TVMArgValue.html">TVMArgValue</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td></tr>
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockScope.html">BlockScope</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1micro__rpc_1_1FrameBuffer.html">FrameBuffer</a> (<a class="el" href="namespacetvm_1_1runtime_1_1micro__rpc.html">tvm::runtime::micro_rpc</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1RunnerInputNode.html">Runn [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BlockScopeNode.html">BlockScopeNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1micro__rpc_1_1Framer.html">Framer</a> (<a class="el" href="namespacetvm_1_1runtime_1_1micro__rpc.html">tvm::runtime::micro_rpc</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1NDArray.html">NDArray</a> (<a class [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1Bool.html">Bool</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ShapeTupleObj_1_1FromStd.html">ShapeTupleObj::FromStd</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1NDArrayContainerTrait.html">NDArrayContainerTrait</a> (<a class="el" href="namespacetvm.h [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Broadcast.html">Broadcast</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1StringObj_1_1FromStd.html">StringObj::FromStd</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1NdarraySizeAttrs.html">NdarraySizeAttrs</a> (<a class="el" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1Bool.html">Bool</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1StringObj_1_1FromStd.html">StringObj::FromStd</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1NDArrayContainerTrait.html">NDArrayContainerTrait</a> (<a class="el" href="namespacetvm.html">tvm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Broadcast.html">Broadcast</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ShapeTupleObj_1_1FromStd.html">ShapeTupleObj::FromStd</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1NdarraySizeAttrs.html">NdarraySizeAttrs</a> (<a cla [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html">BroadcastAttrs</a> (<a class="el" href="namespacetvm_1_1relay_1_1qnn.html">tvm::relay::qnn</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Function.html">Function</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1NE.html">NE</a> (<a class="el" href="namespacetvm_1_1t [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BroadcastNode.html">BroadcastNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1FunctionNode.html">FunctionNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1NENode.html">NENode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1vm_1_1Buffer.html">Buffer</a> (<a class="el" href="namespacetvm_1_1runtime_1_1vm.html">tvm::runtime::vm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1FunctionPattern.html">FunctionPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1NLLLossAttrs.html">NLLLossAttrs</a> (<a class="el" [...]
@@ -200,8 +200,8 @@ $(function() {
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferNode.html">BufferNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_g"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  g  </div></td></tr></table>
</td><td rowspan="2" valign="bottom"><a name="letter_o"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  o  </div></td></tr></table>
</td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ScatterNDAttrs.html">ScatterNDAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="unionTVMValue.html">TVMValue</a>   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRealize.html">BufferRealize</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1Schedule.html">Schedule</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1Type.html">Type</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRealizeNode.html">BufferRealizeNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1GatherAttrs.html">GatherAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ObjAllocatorBase.html">ObjAllocatorBase</a> (<a class="el" href [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRealize.html">BufferRealize</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Schedule.html">Schedule</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1Type.html">Type</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRealizeNode.html">BufferRealizeNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1GatherAttrs.html">GatherAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ObjAllocatorBase.html">ObjAllocatorBase</a> (<a class="el" href [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRegion.html">BufferRegion</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1GatherNDAttrs.html">GatherNDAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1Object.html">Object</a> (<a class="el" href="namespacetvm_1_1runtime. [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferRegionNode.html">BufferRegionNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1GE.html">GE</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1ObjectEqual.html">ObjectEqual</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm: [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferStore.html">BufferStore</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1GenericFunc.html">GenericFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1ObjectHash.html">ObjectHash</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>) [...]
@@ -251,11 +251,11 @@ $(function() {
<tr><td valign="top"><a class="el" href="classtvm_1_1CompilationConfigNode.html">CompilationConfigNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1detail_1_1ImplSHashReduce_3_01T_00_01true_01_4.html">ImplSHashReduce< T, true ></a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1Pass.html">Pass</a> (<a [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1CompileError.html">CompileError</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1detail_1_1ImplVisitAttrs.html">ImplVisitAttrs</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassContext.html">PassContext</a> (<a class="el" href="namespacetvm_1_1transform. [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1CompilerAttrs.html">CompilerAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1detail_1_1ImplVisitAttrs_3_01T_00_01true_01_4.html">ImplVisitAttrs< T, true ></a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassContextNode [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeAtStep.html">ComputeAtStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IncompleteType.html">IncompleteType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassInfo.html">PassInfo</a> (<a class="el" href="names [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeAtStepNode.html">ComputeAtStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IncompleteTypeNode.html">IncompleteTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassInfoNode.html">PassInfoNode</a> (< [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeAtStep.html">ComputeAtStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IncompleteType.html">IncompleteType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassInfo.html">PassInfo</a> (<a class="el" href="names [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeAtStepNode.html">ComputeAtStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IncompleteTypeNode.html">IncompleteTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassInfoNode.html">PassInfoNode</a> (< [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeDAG.html">ComputeDAG</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IndexMap.html">IndexMap</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1instrument_1_1PassInstrument.html">PassInstrument</a> (<a class="e [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeDAGNode.html">ComputeDAGNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IndexMapNode.html">IndexMapNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1instrument_1_1PassInstrumentNode.html">PassInstrum [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeInlineStep.html">ComputeInlineStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1InitOpAttrs.html">InitOpAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassNode.html">PassNode</a [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeDAGNode.html">ComputeDAGNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IndexMapNode.html">IndexMapNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1instrument_1_1PassInstrumentNode.html">PassInstrum [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeInlineStep.html">ComputeInlineStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1InitOpAttrs.html">InitOpAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassNode.html">PassNode</a [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ComputeInlineStepNode.html">ComputeInlineStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1InplaceArrayBase.html">InplaceArrayBase</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Pattern [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1te_1_1ComputeOp.html">ComputeOp</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1InstanceNormAttrs.html">InstanceNormAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternConstructor.html">PatternConstructor</a> (<a class="el" href="nam [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1te_1_1ComputeOpNode.html">ComputeOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html">Instruction</a> (<a class="el" href="namespacetvm_1_1runtime_1_1vm.html">tvm::runtime::vm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternConstructorNode.html">PatternConstructorNode</a [...]
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database-members.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database-members.html
index 0d3788902..3d70d0a77 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database-members.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database-members.html
@@ -86,7 +86,7 @@ $(function() {
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a3deeeac5827a88f375b8c6ae1039c219">operator-></a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a4744bf4a1b48f202d41b51dc5e08e6ee">operator<</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#affdf1b8cdb36e140de7b3ad7064e4617">operator==</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#a9c152a6d89c789adf13047d50d57aa49">PyDatabase</a>(PyDatabaseNode::FHasWorkload f_has_workload, PyDatabaseNode::FCommitWorkload f_commit_workload, PyDatabaseNode::FCommitTuningRecord f_commit_tuning_record, PyDatabaseNode::FGetTopK f_get_top_k, PyDatabaseNode::FSize f_size)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">tvm::meta_schedule::Database</a></td><td cl [...]
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#ae81f559342e4628ea1bffce6db36e547">PyDatabase</a>(PyDatabaseNode::FHasWorkload f_has_workload, PyDatabaseNode::FCommitWorkload f_commit_workload, PyDatabaseNode::FCommitTuningRecord f_commit_tuning_record, PyDatabaseNode::FGetTopK f_get_top_k, PyDatabaseNode::FGetAllTuningRecords f_get_all_tuning_records, PyDatabaseNode::FSize f_size)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedul [...]
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#ae31a5b9f40781d60a2901994ead700e8">same_as</a>(const ObjectRef &other) const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#afb40a32e35f299ee0c6cd6f99f1ed44a">TVM_DEFINE_MUTABLE_NOTNULLABLE_OBJECT_REF_METHODS</a>(Database, runtime::ObjectRef, DatabaseNode)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">tvm::meta_schedule::Database</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#a4e7cdb1574b93a59e784d70aa47b8da7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database.html
index 1fdac4947..d67d33e75 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1Database.html
@@ -131,9 +131,9 @@ Static Public Member Functions</h2></td></tr>
<tr class="memitem:a9eba4e789ead8b3ffd53280390660d1e"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">Database</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#a9eba4e789ead8b3ffd53280390660d1e">JSONDatabase</a> (<a class="el" href="classtvm_1_1runtime_1_1String.html">String</a> path_workload, <a class="el" href="classtvm_1_1runtime_1_1String.ht [...]
<tr class="memdesc:a9eba4e789ead8b3ffd53280390660d1e"><td class="mdescLeft"> </td><td class="mdescRight">Create a default database that uses JSON file for tuning records. <a href="#a9eba4e789ead8b3ffd53280390660d1e">More...</a><br /></td></tr>
<tr class="separator:a9eba4e789ead8b3ffd53280390660d1e"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:a9c152a6d89c789adf13047d50d57aa49"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">Database</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#a9c152a6d89c789adf13047d50d57aa49">PyDatabase</a> (<a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#afb177ebca29227e94c3b3036b4908bad">PyDatabaseNode::FHasWorkload</a [...]
-<tr class="memdesc:a9c152a6d89c789adf13047d50d57aa49"><td class="mdescLeft"> </td><td class="mdescRight">Create a database with customized methods on the python-side. <a href="#a9c152a6d89c789adf13047d50d57aa49">More...</a><br /></td></tr>
-<tr class="separator:a9c152a6d89c789adf13047d50d57aa49"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ae81f559342e4628ea1bffce6db36e547"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">Database</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#ae81f559342e4628ea1bffce6db36e547">PyDatabase</a> (<a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#afb177ebca29227e94c3b3036b4908bad">PyDatabaseNode::FHasWorkload</a [...]
+<tr class="memdesc:ae81f559342e4628ea1bffce6db36e547"><td class="mdescLeft"> </td><td class="mdescRight">Create a database with customized methods on the python-side. <a href="#ae81f559342e4628ea1bffce6db36e547">More...</a><br /></td></tr>
+<tr class="separator:ae81f559342e4628ea1bffce6db36e547"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
@@ -220,8 +220,8 @@ Additional Inherited Members</h2></td></tr>
</div>
</div>
-<a id="a9c152a6d89c789adf13047d50d57aa49"></a>
-<h2 class="memtitle"><span class="permalink"><a href="#a9c152a6d89c789adf13047d50d57aa49">◆ </a></span>PyDatabase()</h2>
+<a id="ae81f559342e4628ea1bffce6db36e547"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#ae81f559342e4628ea1bffce6db36e547">◆ </a></span>PyDatabase()</h2>
<div class="memitem">
<div class="memproto">
@@ -253,6 +253,12 @@ Additional Inherited Members</h2></td></tr>
<td class="paramtype"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">PyDatabaseNode::FGetTopK</a> </td>
<td class="paramname"><em>f_get_top_k</em>, </td>
</tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">PyDatabaseNode::FGetAllTuningRecords</a> </td>
+ <td class="paramname"><em>f_get_all_tuning_records</em>, </td>
+ </tr>
<tr>
<td class="paramkey"></td>
<td></td>
@@ -279,6 +285,7 @@ Additional Inherited Members</h2></td></tr>
<tr><td class="paramname">f_commit_workload</td><td>The packed function of <code>CommitWorkload</code>. </td></tr>
<tr><td class="paramname">f_commit_tuning_record</td><td>The packed function of <code>CommitTuningRecord</code>. </td></tr>
<tr><td class="paramname">f_get_top_k</td><td>The packed function of <code>GetTopK</code>. </td></tr>
+ <tr><td class="paramname">f_get_all_tuning_records</td><td>The packed function of <code>GetAllTuningRecords</code>. </td></tr>
<tr><td class="paramname">f_size</td><td>The packed function of <code>Size</code>. </td></tr>
</table>
</dd>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode-members.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode-members.html
index 29bf0d462..06e3d73de 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode-members.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode-members.html
@@ -83,30 +83,31 @@ $(function() {
<tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a70fb5361147634605d6595bb89381f03">DecRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#af4407d2b59132e803ff791482dbe0145">deleter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a9e84841ca982bff376a978ade0132631">FDeleter</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span [...]
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a27a9519109fd970572be75bc277a1fb2">GetTopK</a>(const Workload &workload, int top_k)=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a04b2ddf6acb509d5cc848c8636f9619d">HasWorkload</a>(const IRModule &mod)=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aae5b9ab9f7e497654b90c23a2159a5cc">Size</a>()=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#ae7ea55bfa3703dfb6452573afc31a45e">TVM_DECLARE_BASE_OBJECT_INFO</a>(DatabaseNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a776359f44ac6b51e337d4a1efc3f04a9">~DatabaseNode</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">virtual</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aa0b963a127d514ff78295b4f75c88872">GetAllTuningRecords</a>()=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a27a9519109fd970572be75bc277a1fb2">GetTopK</a>(const Workload &workload, int top_k)=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a04b2ddf6acb509d5cc848c8636f9619d">HasWorkload</a>(const IRModule &mod)=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aae5b9ab9f7e497654b90c23a2159a5cc">Size</a>()=0</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">pure virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#ae7ea55bfa3703dfb6452573afc31a45e">TVM_DECLARE_BASE_OBJECT_INFO</a>(DatabaseNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a776359f44ac6b51e337d4a1efc3f04a9">~DatabaseNode</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">virtual</span></td></tr>
</table></div><!-- contents -->
<!-- start footer part -->
<hr class="footer"/><address class="footer"><small>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode.html
index 1d4fc727f..f16fb6c08 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode.html
@@ -75,13 +75,13 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::meta_schedule::DatabaseNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1DatabaseNode__inherit__graph.svg" width="290" height="1072"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1DatabaseNode__inherit__graph.svg" width="290" height="1116"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::meta_schedule::DatabaseNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg" width="364" height="758"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg" width="364" height="772"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<table class="memberdecls">
@@ -102,6 +102,9 @@ Public Member Functions</h2></td></tr>
<tr class="memitem:a27a9519109fd970572be75bc277a1fb2"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a27a9519109fd970572be75bc277a1fb2">GetTopK</a> (const <a class="el" href="classtvm_1_1meta__schedule [...]
<tr class="memdesc:a27a9519109fd970572be75bc277a1fb2"><td class="mdescLeft"> </td><td class="mdescRight">Get the top K tuning records of given workload from the database. <a href="#a27a9519109fd970572be75bc277a1fb2">More...</a><br /></td></tr>
<tr class="separator:a27a9519109fd970572be75bc277a1fb2"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aa0b963a127d514ff78295b4f75c88872"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aa0b963a127d514ff78295b4f75c88872">GetAllTuningRecords</a> ()=0</td></tr>
+<tr class="memdesc:aa0b963a127d514ff78295b4f75c88872"><td class="mdescLeft"> </td><td class="mdescRight">Get all tuning records from the database. <a href="#aa0b963a127d514ff78295b4f75c88872">More...</a><br /></td></tr>
+<tr class="separator:aa0b963a127d514ff78295b4f75c88872"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aae5b9ab9f7e497654b90c23a2159a5cc"><td class="memItemLeft" align="right" valign="top">virtual int64_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aae5b9ab9f7e497654b90c23a2159a5cc">Size</a> ()=0</td></tr>
<tr class="memdesc:aae5b9ab9f7e497654b90c23a2159a5cc"><td class="mdescLeft"> </td><td class="mdescRight">Get the size of the database. <a href="#aae5b9ab9f7e497654b90c23a2159a5cc">More...</a><br /></td></tr>
<tr class="separator:aae5b9ab9f7e497654b90c23a2159a5cc"><td class="memSeparator" colspan="2"> </td></tr>
@@ -296,6 +299,36 @@ Additional Inherited Members</h2></td></tr>
<p>Implemented in <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a12d64aa44d3d2ab37a6600d17be3e708">tvm::meta_schedule::PyDatabaseNode</a>.</p>
+</div>
+</div>
+<a id="aa0b963a127d514ff78295b4f75c88872"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#aa0b963a127d514ff78295b4f75c88872">◆ </a></span>GetAllTuningRecords()</h2>
+
+<div class="memitem">
+<div class="memproto">
+<table class="mlabels">
+ <tr>
+ <td class="mlabels-left">
+ <table class="memname">
+ <tr>
+ <td class="memname">virtual <a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a><<a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a>> tvm::meta_schedule::DatabaseNode::GetAllTuningRecords </td>
+ <td>(</td>
+ <td class="paramname"></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+ </td>
+ <td class="mlabels-right">
+<span class="mlabels"><span class="mlabel">pure virtual</span></span> </td>
+ </tr>
+</table>
+</div><div class="memdoc">
+
+<p>Get all tuning records from the database. </p>
+<dl class="section return"><dt>Returns</dt><dd>An Array of all the tuning records in the database. </dd></dl>
+
+<p>Implemented in <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">tvm::meta_schedule::PyDatabaseNode</a>.</p>
+
</div>
</div>
<a id="a27a9519109fd970572be75bc277a1fb2"></a>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg
index 3e98eb41b..187864a41 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode__coll__graph.svg
@@ -4,25 +4,26 @@
<!-- Generated by graphviz version 2.40.1 (20161225.0304)
-->
<!-- Title: tvm::meta_schedule::DatabaseNode Pages: 1 -->
-<svg width="273pt" height="568pt"
- viewBox="0.00 0.00 273.00 568.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
-<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 564)">
+<svg width="273pt" height="579pt"
+ viewBox="0.00 0.00 273.00 579.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 575)">
<title>tvm::meta_schedule::DatabaseNode</title>
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+<polygon fill="#ffffff" stroke="transparent" points="-4,4 -4,-575 269,-575 269,4 -4,4"/>
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<g id="node1" class="node">
<title>Node3</title>
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-<text text-anchor="start" x="8" y="-92.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
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-<text text-anchor="start" x="8" y="-73.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~DatabaseNode()</text>
-<text text-anchor="start" x="8" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
-<text text-anchor="start" x="8" y="-51.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
-<text text-anchor="start" x="8" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
-<text text-anchor="start" x="8" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<polygon fill="#bfbfbf" stroke="#000000" points="0,-.5 0,-145.5 207,-145.5 207,-.5 0,-.5"/>
+<text text-anchor="start" x="8" y="-133.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
+<text text-anchor="middle" x="103.5" y="-122.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::DatabaseNode</text>
+<polyline fill="none" stroke="#000000" points="0,-115.5 207,-115.5 "/>
+<text text-anchor="start" x="8" y="-103.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<polyline fill="none" stroke="#000000" points="0,-96.5 207,-96.5 "/>
+<text text-anchor="start" x="8" y="-84.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~DatabaseNode()</text>
+<text text-anchor="start" x="8" y="-73.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
+<text text-anchor="start" x="8" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
+<text text-anchor="start" x="8" y="-51.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
+<text text-anchor="start" x="8" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<text text-anchor="start" x="8" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetAllTuningRecords()</text>
<text text-anchor="start" x="8" y="-18.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Size()</text>
<text text-anchor="start" x="8" y="-7.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_BASE_OBJECT_INFO()</text>
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<g id="node2" class="node">
<title>Node4</title>
<g id="a_node2"><a xlink:href="classtvm_1_1runtime_1_1Object.html" target="_top" xlink:title="base class of all object containers. ">
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-<text text-anchor="start" x="20" y="-528.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
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-<text text-anchor="start" x="20" y="-385.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
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-<text text-anchor="start" x="20" y="-366.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
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-<text text-anchor="start" x="20" y="-322.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<polygon fill="#ffffff" stroke="#000000" points="12,-183.5 12,-570.5 195,-570.5 195,-183.5 12,-183.5"/>
+<text text-anchor="middle" x="103.5" y="-558.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
+<polyline fill="none" stroke="#000000" points="12,-551.5 195,-551.5 "/>
+<text text-anchor="start" x="20" y="-539.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<text text-anchor="start" x="20" y="-528.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
+<text text-anchor="start" x="20" y="-517.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
+<text text-anchor="start" x="20" y="-506.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots_can</text>
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+<text text-anchor="start" x="20" y="-473.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_attrs</text>
+<text text-anchor="start" x="20" y="-462.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
+<text text-anchor="start" x="20" y="-451.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="20" y="-440.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
+<text text-anchor="start" x="20" y="-429.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="20" y="-418.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_index</text>
+<text text-anchor="start" x="20" y="-407.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
+<text text-anchor="start" x="20" y="-396.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
+<polyline fill="none" stroke="#000000" points="12,-389.5 195,-389.5 "/>
+<text text-anchor="start" x="20" y="-377.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
+<text text-anchor="start" x="20" y="-366.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKey()</text>
+<text text-anchor="start" x="20" y="-355.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
+<text text-anchor="start" x="20" y="-344.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
+<text text-anchor="start" x="20" y="-333.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="20" y="-322.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
<text text-anchor="start" x="20" y="-311.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
<text text-anchor="start" x="20" y="-300.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
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+<text text-anchor="start" x="20" y="-289.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
<text text-anchor="start" x="20" y="-278.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
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-<text text-anchor="start" x="20" y="-201.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
-<text text-anchor="start" x="20" y="-190.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
-<text text-anchor="start" x="20" y="-179.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-267.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
+<text text-anchor="start" x="20" y="-256.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
+<text text-anchor="start" x="20" y="-245.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
+<text text-anchor="start" x="20" y="-234.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-223.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-212.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
+<text text-anchor="start" x="20" y="-201.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
+<text text-anchor="start" x="20" y="-190.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
</a>
</g>
</g>
<!-- Node4->Node3 -->
<g id="edge1" class="edge">
<title>Node4->Node3</title>
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-<polygon fill="none" stroke="#191970" points="100.0001,-162.3202 103.5,-172.3202 107.0001,-162.3202 100.0001,-162.3202"/>
+<path fill="none" stroke="#191970" d="M103.5,-173.1654C103.5,-163.6544 103.5,-154.4511 103.5,-145.731"/>
+<polygon fill="none" stroke="#191970" points="100.0001,-173.1808 103.5,-183.1808 107.0001,-173.1808 100.0001,-173.1808"/>
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<!-- Node4->Node4 -->
<g id="edge2" class="edge">
<title>Node4->Node4</title>
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-<text text-anchor="middle" x="239" y="-363.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
+<path fill="none" stroke="#404040" d="M195.3625,-410.9248C206.0482,-404.6637 213,-393.3555 213,-377 213,-366.0112 209.8618,-357.3007 204.5615,-350.8687"/>
+<polygon fill="none" stroke="#404040" points="204.5184,-350.8322 197.3548,-350.0056 195.3625,-343.0752 202.5261,-343.9017 204.5184,-350.8322"/>
+<text text-anchor="middle" x="239" y="-374.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
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index 1ca1cf901..9c0893413 100644
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+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1DatabaseNode__inherit__graph.svg
@@ -4,48 +4,51 @@
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+<svg width="217pt" height="837pt"
+ viewBox="0.00 0.00 217.00 837.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 833)">
<title>tvm::meta_schedule::DatabaseNode</title>
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+<polygon fill="#ffffff" stroke="transparent" points="-4,4 -4,-833 213,-833 213,4 -4,4"/>
<!-- Node0 -->
<g id="node1" class="node">
<title>Node0</title>
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-<text text-anchor="start" x="9" y="-318.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
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-<text text-anchor="start" x="9" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~DatabaseNode()</text>
-<text text-anchor="start" x="9" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
-<text text-anchor="start" x="9" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
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-<text text-anchor="start" x="9" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
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-<text text-anchor="start" x="9" y="-233.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_BASE_OBJECT_INFO()</text>
+<polygon fill="#bfbfbf" stroke="#000000" points="1,-248.5 1,-393.5 208,-393.5 208,-248.5 1,-248.5"/>
+<text text-anchor="start" x="9" y="-381.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
+<text text-anchor="middle" x="104.5" y="-370.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::DatabaseNode</text>
+<polyline fill="none" stroke="#000000" points="1,-363.5 208,-363.5 "/>
+<text text-anchor="start" x="9" y="-351.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<polyline fill="none" stroke="#000000" points="1,-344.5 208,-344.5 "/>
+<text text-anchor="start" x="9" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~DatabaseNode()</text>
+<text text-anchor="start" x="9" y="-321.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
+<text text-anchor="start" x="9" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
+<text text-anchor="start" x="9" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
+<text text-anchor="start" x="9" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<text text-anchor="start" x="9" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetAllTuningRecords()</text>
+<text text-anchor="start" x="9" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Size()</text>
+<text text-anchor="start" x="9" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_BASE_OBJECT_INFO()</text>
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-<text text-anchor="start" x="8" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
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+<text text-anchor="start" x="8" y="-199.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
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+<text text-anchor="start" x="8" y="-136.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ f_get_top_k</text>
+<text text-anchor="start" x="8" y="-125.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ f_get_all_tuning_records</text>
+<text text-anchor="start" x="8" y="-114.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ f_size</text>
+<text text-anchor="start" x="8" y="-103.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<polyline fill="none" stroke="#000000" points="0,-96.5 209,-96.5 "/>
+<text text-anchor="start" x="8" y="-84.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ VisitAttrs()</text>
+<text text-anchor="start" x="8" y="-73.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
+<text text-anchor="start" x="8" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
+<text text-anchor="start" x="8" y="-51.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
+<text text-anchor="start" x="8" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<text text-anchor="start" x="8" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetAllTuningRecords()</text>
<text text-anchor="start" x="8" y="-18.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Size()</text>
<text text-anchor="start" x="8" y="-7.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_FINAL_OBJECT_INFO()</text>
</a>
@@ -54,58 +57,58 @@
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<g id="edge2" class="edge">
<title>Node0->Node2</title>
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+<polygon fill="none" stroke="#191970" points="101.0001,-238.2108 104.5,-248.2108 108.0001,-238.2108 101.0001,-238.2108"/>
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<g id="node2" class="node">
<title>Node1</title>
<g id="a_node2"><a xlink:href="classtvm_1_1runtime_1_1Object.html" target="_top" xlink:title="base class of all object containers. ">
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-<text text-anchor="start" x="21" y="-764.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
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-<text text-anchor="start" x="21" y="-687.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
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-<text text-anchor="start" x="21" y="-591.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
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+<text text-anchor="start" x="21" y="-797.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<text text-anchor="start" x="21" y="-786.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
+<text text-anchor="start" x="21" y="-775.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
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+<text text-anchor="start" x="21" y="-720.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
+<text text-anchor="start" x="21" y="-709.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="21" y="-698.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
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+<text text-anchor="start" x="21" y="-665.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
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+<text text-anchor="start" x="21" y="-624.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
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+<text text-anchor="start" x="21" y="-602.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
+<text text-anchor="start" x="21" y="-591.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
+<text text-anchor="start" x="21" y="-580.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="21" y="-569.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
+<text text-anchor="start" x="21" y="-558.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
+<text text-anchor="start" x="21" y="-547.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
+<text text-anchor="start" x="21" y="-536.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
+<text text-anchor="start" x="21" y="-525.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
+<text text-anchor="start" x="21" y="-514.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
+<text text-anchor="start" x="21" y="-503.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
+<text text-anchor="start" x="21" y="-492.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
+<text text-anchor="start" x="21" y="-481.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="21" y="-470.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
+<text text-anchor="start" x="21" y="-459.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
+<text text-anchor="start" x="21" y="-448.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
+<text text-anchor="start" x="21" y="-437.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
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<!-- Node1->Node0 -->
<g id="edge1" class="edge">
<title>Node1->Node0</title>
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-<polygon fill="none" stroke="#191970" points="101.0001,-387.3515 104.5,-397.3515 108.0001,-387.3515 101.0001,-387.3515"/>
+<path fill="none" stroke="#191970" d="M104.5,-420.116C104.5,-410.9251 104.5,-402.0349 104.5,-393.6022"/>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode-members.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode-members.html
index 3a6c191c6..d5139bf13 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode-members.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode-members.html
@@ -84,41 +84,44 @@ $(function() {
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#af4407d2b59132e803ff791482dbe0145">deleter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a7d7d50ae9b6c43e064b38db91bc8123d">f_commit_tuning_record</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aa0bd64983cde2fc6ef1547448352981c">f_commit_workload</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">f_get_top_k</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#add146bf1e2006f72ed1534b2004bcb06">f_has_workload</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ac7ae1a05fe5c7858f5860133a82bc7b7">f_size</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a653d04c0c6349350489c0ea5f68563f1">FCommitTuningRecord</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a44b8d5e2721f12bdaf1a457b85f23124">FCommitWorkload</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a9e84841ca982bff376a978ade0132631">FDeleter</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f">f_get_all_tuning_records</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">f_get_top_k</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#add146bf1e2006f72ed1534b2004bcb06">f_has_workload</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ac7ae1a05fe5c7858f5860133a82bc7b7">f_size</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a653d04c0c6349350489c0ea5f68563f1">FCommitTuningRecord</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a44b8d5e2721f12bdaf1a457b85f23124">FCommitWorkload</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a9e84841ca982bff376a978ade0132631">FDeleter</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">FGetAllTuningRecords</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">FGetTopK</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#afb177ebca29227e94c3b3036b4908bad">FHasWorkload</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a34efc3d18473d179b13332abe5c63324">FSize</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span [...]
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#adebe3a6bfb55e5ce0807b97f12a6c39e">GetTopK</a>(const Workload &workload, int top_k) final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a38195f2c3aea9ae4890477393ab2c624">HasWorkload</a>(const IRModule &mod) final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a36817d04978253571fef7d01427ce9c0">Size</a>() final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#ae7ea55bfa3703dfb6452573afc31a45e">TVM_DECLARE_BASE_OBJECT_INFO</a>(DatabaseNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad4256c83aa0af3514af963a073811b2b">TVM_DECLARE_FINAL_OBJECT_INFO</a>(PyDatabaseNode, DatabaseNode)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a1a24b977e3d25a7ffab704e12457fb66">VisitAttrs</a>(tvm::AttrVisitor *v)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a776359f44ac6b51e337d4a1efc3f04a9">~DatabaseNode</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">virtual</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">GetAllTuningRecords</a>() final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#adebe3a6bfb55e5ce0807b97f12a6c39e">GetTopK</a>(const Workload &workload, int top_k) final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a38195f2c3aea9ae4890477393ab2c624">HasWorkload</a>(const IRModule &mod) final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a36817d04978253571fef7d01427ce9c0">Size</a>() final</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">virtual</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#ae7ea55bfa3703dfb6452573afc31a45e">TVM_DECLARE_BASE_OBJECT_INFO</a>(DatabaseNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad4256c83aa0af3514af963a073811b2b">TVM_DECLARE_FINAL_OBJECT_INFO</a>(PyDatabaseNode, DatabaseNode)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a1a24b977e3d25a7ffab704e12457fb66">VisitAttrs</a>(tvm::AttrVisitor *v)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a776359f44ac6b51e337d4a1efc3f04a9">~DatabaseNode</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></td><td class="entry"><span class="mlabel">virtual</span></td></tr>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode.html
index 2b6092ee1..6ac5a8f34 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1PyDatabaseNode.html
@@ -80,13 +80,13 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::meta_schedule::PyDatabaseNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1PyDatabaseNode__inherit__graph.svg" width="290" height="1072"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1PyDatabaseNode__inherit__graph.svg" width="290" height="1116"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::meta_schedule::PyDatabaseNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1PyDatabaseNode__coll__graph.svg" width="1554" height="1000"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1PyDatabaseNode__coll__graph.svg" width="1816" height="1030"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<table class="memberdecls">
@@ -104,6 +104,9 @@ Public Types</h2></td></tr>
<tr class="memitem:ad5e04e950cd2a63f439d95285b5674b6"><td class="memItemLeft" align="right" valign="top">using </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">FGetTopK</a> = <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html">runtime::TypedPackedFunc</a>< <a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_1meta__sched [...]
<tr class="memdesc:ad5e04e950cd2a63f439d95285b5674b6"><td class="mdescLeft"> </td><td class="mdescRight">The function type of <code>GetTopK</code> method. <a href="#ad5e04e950cd2a63f439d95285b5674b6">More...</a><br /></td></tr>
<tr class="separator:ad5e04e950cd2a63f439d95285b5674b6"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a574d90736eda21019540d4a26c155b28"><td class="memItemLeft" align="right" valign="top">using </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">FGetAllTuningRecords</a> = <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html">runtime::TypedPackedFunc</a>< <a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_ [...]
+<tr class="memdesc:a574d90736eda21019540d4a26c155b28"><td class="mdescLeft"> </td><td class="mdescRight">The function type of <code>GetAllTuningRecords</code> method. <a href="#a574d90736eda21019540d4a26c155b28">More...</a><br /></td></tr>
+<tr class="separator:a574d90736eda21019540d4a26c155b28"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a34efc3d18473d179b13332abe5c63324"><td class="memItemLeft" align="right" valign="top">using </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a34efc3d18473d179b13332abe5c63324">FSize</a> = <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html">runtime::TypedPackedFunc</a>< int64_t()></td></tr>
<tr class="memdesc:a34efc3d18473d179b13332abe5c63324"><td class="mdescLeft"> </td><td class="mdescRight">The function type of <code>Size</code> method. <a href="#a34efc3d18473d179b13332abe5c63324">More...</a><br /></td></tr>
<tr class="separator:a34efc3d18473d179b13332abe5c63324"><td class="memSeparator" colspan="2"> </td></tr>
@@ -130,6 +133,9 @@ Public Member Functions</h2></td></tr>
<tr class="memitem:adebe3a6bfb55e5ce0807b97f12a6c39e"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#adebe3a6bfb55e5ce0807b97f12a6c39e">GetTopK</a> (const <a class="el" href="classtvm_1_1meta__schedule_1_1Wo [...]
<tr class="memdesc:adebe3a6bfb55e5ce0807b97f12a6c39e"><td class="mdescLeft"> </td><td class="mdescRight">Get the top K tuning records of given workload from the database. <a href="#adebe3a6bfb55e5ce0807b97f12a6c39e">More...</a><br /></td></tr>
<tr class="separator:adebe3a6bfb55e5ce0807b97f12a6c39e"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:ad07d7d9e78771eaa2e6e65f84e032401"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a>< <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">GetAllTuningRecords</a> () final</td></tr>
+<tr class="memdesc:ad07d7d9e78771eaa2e6e65f84e032401"><td class="mdescLeft"> </td><td class="mdescRight">Get all tuning records from the database. <a href="#ad07d7d9e78771eaa2e6e65f84e032401">More...</a><br /></td></tr>
+<tr class="separator:ad07d7d9e78771eaa2e6e65f84e032401"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a36817d04978253571fef7d01427ce9c0"><td class="memItemLeft" align="right" valign="top">int64_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a36817d04978253571fef7d01427ce9c0">Size</a> () final</td></tr>
<tr class="memdesc:a36817d04978253571fef7d01427ce9c0"><td class="mdescLeft"> </td><td class="mdescRight">Get the size of the database. <a href="#a36817d04978253571fef7d01427ce9c0">More...</a><br /></td></tr>
<tr class="separator:a36817d04978253571fef7d01427ce9c0"><td class="memSeparator" colspan="2"> </td></tr>
@@ -178,6 +184,9 @@ Public Attributes</h2></td></tr>
<tr class="memitem:a52fb1116090619e95fb6b28352308eed"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">FGetTopK</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">f_get_top_k</a></td></tr>
<tr class="memdesc:a52fb1116090619e95fb6b28352308eed"><td class="mdescLeft"> </td><td class="mdescRight">The packed function to the <code>GetTopK</code> function. <a href="#a52fb1116090619e95fb6b28352308eed">More...</a><br /></td></tr>
<tr class="separator:a52fb1116090619e95fb6b28352308eed"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aafdd0874be052072521b2aa8a6c56d5f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">FGetAllTuningRecords</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f">f_get_all_tuning_records</a></td></tr>
+<tr class="memdesc:aafdd0874be052072521b2aa8a6c56d5f"><td class="mdescLeft"> </td><td class="mdescRight">The packed function to the <code>GetAllTuningRecords</code> function. <a href="#aafdd0874be052072521b2aa8a6c56d5f">More...</a><br /></td></tr>
+<tr class="separator:aafdd0874be052072521b2aa8a6c56d5f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac7ae1a05fe5c7858f5860133a82bc7b7"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a34efc3d18473d179b13332abe5c63324">FSize</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ac7ae1a05fe5c7858f5860133a82bc7b7">f_size</a></td></tr>
<tr class="memdesc:ac7ae1a05fe5c7858f5860133a82bc7b7"><td class="mdescLeft"> </td><td class="mdescRight">The packed function to the <code>Size</code> function. <a href="#ac7ae1a05fe5c7858f5860133a82bc7b7">More...</a><br /></td></tr>
<tr class="separator:ac7ae1a05fe5c7858f5860133a82bc7b7"><td class="memSeparator" colspan="2"> </td></tr>
@@ -291,6 +300,23 @@ Additional Inherited Members</h2></td></tr>
</dl>
<dl class="section return"><dt>Returns</dt><dd>The workload corresponding to the given <a class="el" href="classtvm_1_1IRModule.html" title="Managed reference class to IRModuleNode. ">IRModule</a>. </dd></dl>
+</div>
+</div>
+<a id="a574d90736eda21019540d4a26c155b28"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#a574d90736eda21019540d4a26c155b28">◆ </a></span>FGetAllTuningRecords</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname">using <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">tvm::meta_schedule::PyDatabaseNode::FGetAllTuningRecords</a> = <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html">runtime::TypedPackedFunc</a><<a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a><<a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a>>()></td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+<p>The function type of <code>GetAllTuningRecords</code> method. </p>
+<dl class="section return"><dt>Returns</dt><dd>An Array of all the tuning records in the database. </dd></dl>
+
</div>
</div>
<a id="ad5e04e950cd2a63f439d95285b5674b6"></a>
@@ -429,6 +455,36 @@ Additional Inherited Members</h2></td></tr>
<p>Implements <a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#a833752c0069eb976028425751df6e9ac">tvm::meta_schedule::DatabaseNode</a>.</p>
+</div>
+</div>
+<a id="ad07d7d9e78771eaa2e6e65f84e032401"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#ad07d7d9e78771eaa2e6e65f84e032401">◆ </a></span>GetAllTuningRecords()</h2>
+
+<div class="memitem">
+<div class="memproto">
+<table class="mlabels">
+ <tr>
+ <td class="mlabels-left">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a><<a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecord.html">TuningRecord</a>> tvm::meta_schedule::PyDatabaseNode::GetAllTuningRecords </td>
+ <td>(</td>
+ <td class="paramname"></td><td>)</td>
+ <td></td>
+ </tr>
+ </table>
+ </td>
+ <td class="mlabels-right">
+<span class="mlabels"><span class="mlabel">inline</span><span class="mlabel">final</span><span class="mlabel">virtual</span></span> </td>
+ </tr>
+</table>
+</div><div class="memdoc">
+
+<p>Get all tuning records from the database. </p>
+<dl class="section return"><dt>Returns</dt><dd>An Array of all the tuning records in the database. </dd></dl>
+
+<p>Implements <a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aa0b963a127d514ff78295b4f75c88872">tvm::meta_schedule::DatabaseNode</a>.</p>
+
</div>
</div>
<a id="adebe3a6bfb55e5ce0807b97f12a6c39e"></a>
@@ -653,6 +709,22 @@ Additional Inherited Members</h2></td></tr>
<p>The packed function to the <code>CommitWorkload</code> function. </p>
+</div>
+</div>
+<a id="aafdd0874be052072521b2aa8a6c56d5f"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#aafdd0874be052072521b2aa8a6c56d5f">◆ </a></span>f_get_all_tuning_records</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">FGetAllTuningRecords</a> tvm::meta_schedule::PyDatabaseNode::f_get_all_tuning_records</td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+<p>The packed function to the <code>GetAllTuningRecords</code> function. </p>
+
</div>
</div>
<a id="a52fb1116090619e95fb6b28352308eed"></a>
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+<text text-anchor="middle" x="103.5" y="-315.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::DatabaseNode</text>
+<polyline fill="none" stroke="#000000" points="0,-308.5 207,-308.5 "/>
+<text text-anchor="start" x="8" y="-296.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<polyline fill="none" stroke="#000000" points="0,-289.5 207,-289.5 "/>
+<text text-anchor="start" x="8" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ~DatabaseNode()</text>
+<text text-anchor="start" x="8" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ HasWorkload()</text>
+<text text-anchor="start" x="8" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitWorkload()</text>
+<text text-anchor="start" x="8" y="-244.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
+<text text-anchor="start" x="8" y="-233.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<text text-anchor="start" x="8" y="-222.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetAllTuningRecords()</text>
+<text text-anchor="start" x="8" y="-211.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Size()</text>
+<text text-anchor="start" x="8" y="-200.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_BASE_OBJECT_INFO()</text>
</a>
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<g id="edge1" class="edge">
<title>Node4->Node3</title>
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-<polygon fill="none" stroke="#191970" points="214.7579,-178.6558 207.0937,-185.971 217.6469,-185.0319 214.7579,-178.6558"/>
+<path fill="none" stroke="#191970" d="M216.6183,-192.7213C337.4347,-140.3739 473.7236,-108.5452 565.6681,-90.7505"/>
+<polygon fill="none" stroke="#191970" points="214.9565,-189.6284 207.2083,-196.8545 217.7716,-196.0375 214.9565,-189.6284"/>
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<g id="node3" class="node">
<title>Node5</title>
<g id="a_node3"><a xlink:href="classtvm_1_1runtime_1_1Object.html" target="_top" xlink:title="base class of all object containers. ">
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-<text text-anchor="middle" x="103.5" y="-729.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
-<polyline fill="none" stroke="#000000" points="12,-722.5 195,-722.5 "/>
-<text text-anchor="start" x="20" y="-710.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
-<text text-anchor="start" x="20" y="-699.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
-<text text-anchor="start" x="20" y="-688.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
-<text text-anchor="start" x="20" y="-677.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots_can</text>
-<text text-anchor="start" x="20" y="-666.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_overflow</text>
-<text text-anchor="start" x="20" y="-655.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_visit</text>
-<text text-anchor="start" x="20" y="-644.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_attrs</text>
-<text text-anchor="start" x="20" y="-633.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
+<polygon fill="#ffffff" stroke="#000000" points="12,-376.5 12,-763.5 195,-763.5 195,-376.5 12,-376.5"/>
+<text text-anchor="middle" x="103.5" y="-751.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
+<polyline fill="none" stroke="#000000" points="12,-744.5 195,-744.5 "/>
+<text text-anchor="start" x="20" y="-732.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<text text-anchor="start" x="20" y="-721.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
+<text text-anchor="start" x="20" y="-710.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
+<text text-anchor="start" x="20" y="-699.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots_can</text>
+<text text-anchor="start" x="20" y="-688.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_overflow</text>
+<text text-anchor="start" x="20" y="-677.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_visit</text>
+<text text-anchor="start" x="20" y="-666.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_attrs</text>
+<text text-anchor="start" x="20" y="-655.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
+<text text-anchor="start" x="20" y="-644.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="20" y="-633.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
<text text-anchor="start" x="20" y="-622.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
-<text text-anchor="start" x="20" y="-611.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
-<text text-anchor="start" x="20" y="-600.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
-<text text-anchor="start" x="20" y="-589.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_index</text>
-<text text-anchor="start" x="20" y="-578.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
-<text text-anchor="start" x="20" y="-567.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
-<polyline fill="none" stroke="#000000" points="12,-560.5 195,-560.5 "/>
-<text text-anchor="start" x="20" y="-548.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
-<text text-anchor="start" x="20" y="-537.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKey()</text>
-<text text-anchor="start" x="20" y="-526.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
-<text text-anchor="start" x="20" y="-515.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
-<text text-anchor="start" x="20" y="-504.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="20" y="-611.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_index</text>
+<text text-anchor="start" x="20" y="-600.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
+<text text-anchor="start" x="20" y="-589.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
+<polyline fill="none" stroke="#000000" points="12,-582.5 195,-582.5 "/>
+<text text-anchor="start" x="20" y="-570.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
+<text text-anchor="start" x="20" y="-559.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKey()</text>
+<text text-anchor="start" x="20" y="-548.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
+<text text-anchor="start" x="20" y="-537.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
+<text text-anchor="start" x="20" y="-526.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="20" y="-515.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
+<text text-anchor="start" x="20" y="-504.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
<text text-anchor="start" x="20" y="-493.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
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-<text text-anchor="start" x="20" y="-471.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
-<text text-anchor="start" x="20" y="-460.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="20" y="-449.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="20" y="-438.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
-<text text-anchor="start" x="20" y="-427.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
-<text text-anchor="start" x="20" y="-416.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
-<text text-anchor="start" x="20" y="-405.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
-<text text-anchor="start" x="20" y="-394.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
-<text text-anchor="start" x="20" y="-383.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
-<text text-anchor="start" x="20" y="-372.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
-<text text-anchor="start" x="20" y="-361.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-482.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
+<text text-anchor="start" x="20" y="-471.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
+<text text-anchor="start" x="20" y="-460.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
+<text text-anchor="start" x="20" y="-449.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
+<text text-anchor="start" x="20" y="-438.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
+<text text-anchor="start" x="20" y="-427.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-416.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
+<text text-anchor="start" x="20" y="-405.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
+<text text-anchor="start" x="20" y="-394.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
+<text text-anchor="start" x="20" y="-383.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
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<!-- Node5->Node4 -->
<g id="edge2" class="edge">
<title>Node5->Node4</title>
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-<polygon fill="none" stroke="#191970" points="100.0001,-344.3202 103.5,-354.3202 107.0001,-344.3202 100.0001,-344.3202"/>
+<path fill="none" stroke="#191970" d="M103.5,-366.1654C103.5,-356.6544 103.5,-347.4511 103.5,-338.731"/>
+<polygon fill="none" stroke="#191970" points="100.0001,-366.1808 103.5,-376.1808 107.0001,-366.1808 100.0001,-366.1808"/>
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-<text text-anchor="middle" x="239" y="-545.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
+<path fill="none" stroke="#404040" d="M195.3625,-603.9248C206.0482,-597.6637 213,-586.3555 213,-570 213,-559.0112 209.8618,-550.3007 204.5615,-543.8687"/>
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+<text text-anchor="middle" x="239" y="-567.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
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<g id="node4" class="node">
<title>Node6</title>
<g id="a_node4"><a xlink:href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_top" xlink:title="{tvm::runtime::TypedPacked\lFunc\< int64_t()\>\n||}">
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-<text text-anchor="start" x="233" y="-271.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TypedPacked</text>
-<text text-anchor="middle" x="299.5" y="-260.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Func< int64_t()></text>
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-<text text-anchor="middle" x="299.5" y="-241.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
-<polyline fill="none" stroke="#000000" points="225,-234.5 374,-234.5 "/>
-<text text-anchor="middle" x="299.5" y="-222.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polygon fill="#ffffff" stroke="#000000" points="225,-232 225,-300 374,-300 374,-232 225,-232"/>
+<text text-anchor="start" x="233" y="-288" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TypedPacked</text>
+<text text-anchor="middle" x="299.5" y="-277" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Func< int64_t()></text>
+<polyline fill="none" stroke="#000000" points="225,-270 374,-270 "/>
+<text text-anchor="middle" x="299.5" y="-258" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polyline fill="none" stroke="#000000" points="225,-251 374,-251 "/>
+<text text-anchor="middle" x="299.5" y="-239" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
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<title>Node6->Node3</title>
-<path fill="none" stroke="#404040" d="M339.214,-215.4725C352.6689,-204.4149 367.9726,-192.3382 382.5,-182 404.6164,-166.2612 428.8947,-150.3356 452.3782,-135.5685"/>
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-<text text-anchor="middle" x="442.5" y="-156" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> +f_size</text>
+<path fill="none" stroke="#404040" d="M333.4198,-231.649C347.7246,-218.4107 365.0821,-203.8738 382.5,-193 435.9064,-159.659 500.1863,-131.8563 554.4563,-111.4359"/>
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+<text text-anchor="middle" x="447.5" y="-167" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> +f_size</text>
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<g id="node5" class="node">
<title>Node7</title>
<g id="a_node5"><a xlink:href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_top" xlink:title="{tvm::runtime::TypedPacked\lFunc\< bool(const IRModule &)\>\n||}">
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-<text text-anchor="start" x="400" y="-271.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TypedPacked</text>
-<text text-anchor="middle" x="477.5" y="-260.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Func< bool(const IRModule &)></text>
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-<text text-anchor="middle" x="477.5" y="-241.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
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-<text text-anchor="middle" x="477.5" y="-222.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polygon fill="#ffffff" stroke="#000000" points="392,-232 392,-300 563,-300 563,-232 392,-232"/>
+<text text-anchor="start" x="400" y="-288" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TypedPacked</text>
+<text text-anchor="middle" x="477.5" y="-277" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Func< bool(const IRModule &)></text>
+<polyline fill="none" stroke="#000000" points="392,-270 563,-270 "/>
+<text text-anchor="middle" x="477.5" y="-258" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polyline fill="none" stroke="#000000" points="392,-251 563,-251 "/>
+<text text-anchor="middle" x="477.5" y="-239" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
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<g id="edge5" class="edge">
<title>Node7->Node3</title>
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-<text text-anchor="middle" x="569.5" y="-156" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> +f_has_workload</text>
+<path fill="none" stroke="#404040" d="M511.0786,-231.9123C530.6881,-212.0498 555.9381,-186.5498 578.5,-164 581.6234,-160.8783 584.8095,-157.6995 588.0303,-154.4908"/>
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<g id="node6" class="node">
<title>Node8</title>
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-<text text-anchor="start" x="589.5" y="-266" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Func< Array< TuningRecord</text>
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+<text text-anchor="start" x="9" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ CommitTuningRecord()</text>
+<text text-anchor="start" x="9" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTopK()</text>
+<text text-anchor="start" x="9" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetAllTuningRecords()</text>
+<text text-anchor="start" x="9" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Size()</text>
+<text text-anchor="start" x="9" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_BASE_OBJECT_INFO()</text>
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+<text text-anchor="start" x="21" y="-624.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
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+<text text-anchor="start" x="21" y="-591.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
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+<text text-anchor="start" x="21" y="-481.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="21" y="-470.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
+<text text-anchor="start" x="21" y="-459.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode-members.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode-members.html
index 6803959ac..fd9da4a42 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode-members.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode-members.html
@@ -80,34 +80,35 @@ $(function() {
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#aa90a4ab949484eac753ff45a7693a829">_type_key</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
<tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a09f1921d607d7ef4397876c15d2f0b08">args_info</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ac2e3ed776662e66112c37ec4fcb091d1">AsJSON</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a70fb5361147634605d6595bb89381f03">DecRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#af4407d2b59132e803ff791482dbe0145">deleter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a9e84841ca982bff376a978ade0132631">FDeleter</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span [...]
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a00aeeedbe4d1d6008224d98c62739581">run_secs</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a45a380cfa2edfd63056fb1a00f9aac35">target</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a8cc2d64f796593a1a774eef259f17b29">trace</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a6270ef8a153eca3d2571ee2d34feb4ff">TVM_DECLARE_FINAL_OBJECT_INFO</a>(TuningRecordNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ad023a7eb8d2ff99ddbae3e1fcb5bcce8">VisitAttrs</a>(tvm::AttrVisitor *v)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a42c87f1ec62dae6806c3fe9629c5e7f0">workload</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#aa4f013b36ab008650dea4fb62d523c43">AsMeasureCandidate</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a70fb5361147634605d6595bb89381f03">DecRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#af4407d2b59132e803ff791482dbe0145">deleter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a9e84841ca982bff376a978ade0132631">FDeleter</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a726972ff315c446192df94027ddea032">GetOrAllocRuntimeTypeIndex</a>(const std::string &key, uint32_t static_tindex, uint32_t parent_tindex, uint32_t type_child_slots, bool type_child_slots_can_overflow)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4d951e51832081b85875669eac90e940">GetTypeKey</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a5693cbadcc1168b96db7b1cc5c200b86">GetTypeKeyHash</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ac9e5eed7719e322117bde996a171e33a">IncRef</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">protected</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a90e90b3f4ba8a590baff78c75807bbc7">IsInstance</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a133436a9ec5c4a768b94102bf95a660b">Object</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ab7968feb6ad38ecaffc320e13819d826">Object</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#aa1612f69ea5b4225d4cda759cd517323">Object</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a69c32fbd96181f5c21d2c878ab285e4f">operator=</a>(const Object &other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ae341e561272ff43cdcbc927bc29ac50d">operator=</a>(Object &&other)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a0d492efee331e2239a093f4b2017c10f">ref_counter_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a55549a6c23987890246248682560a03d">RefCounterType</a> typedef</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a00aeeedbe4d1d6008224d98c62739581">run_secs</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#ad94d79729ac85aa7c976e23d39066383">RuntimeTypeIndex</a>()</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a45a380cfa2edfd63056fb1a00f9aac35">target</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a8cc2d64f796593a1a774eef259f17b29">trace</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a6270ef8a153eca3d2571ee2d34feb4ff">TVM_DECLARE_FINAL_OBJECT_INFO</a>(TuningRecordNode, runtime::Object)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a481f01923b14e1851ebd38506e9c66ea">type_index</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a4bfc2586cb55f2af47728187b3256255">type_index_</a></td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">TypeIndex2Key</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6ee32a02dd44257da105fbbe5d9c8622">TypeIndex2KeyHash</a>(uint32_t tindex)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#a6841f97e06e6614dd7e82c6dd41b818a">TypeKey2Index</a>(const std::string &key)</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html#afd548730a6139d19fe24473ad66026d7">unique</a>() const</td><td class="entry"><a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ad023a7eb8d2ff99ddbae3e1fcb5bcce8">VisitAttrs</a>(tvm::AttrVisitor *v)</td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
+ <tr><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a42c87f1ec62dae6806c3fe9629c5e7f0">workload</a></td><td class="entry"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></td><td class="entry"></td></tr>
</table></div><!-- contents -->
<!-- start footer part -->
<hr class="footer"/><address class="footer"><small>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode.html b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode.html
index e384b8a40..2834811d9 100644
--- a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode.html
+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode.html
@@ -79,13 +79,13 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::meta_schedule::TuningRecordNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1TuningRecordNode__inherit__graph.svg" width="290" height="786"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1TuningRecordNode__inherit__graph.svg" width="290" height="800"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::meta_schedule::TuningRecordNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1TuningRecordNode__coll__graph.svg" width="1478" height="1360"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1meta__schedule_1_1TuningRecordNode__coll__graph.svg" width="1478" height="1375"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
<table class="memberdecls">
@@ -95,6 +95,9 @@ Public Member Functions</h2></td></tr>
<tr class="separator:ad023a7eb8d2ff99ddbae3e1fcb5bcce8"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a6270ef8a153eca3d2571ee2d34feb4ff"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a6270ef8a153eca3d2571ee2d34feb4ff">TVM_DECLARE_FINAL_OBJECT_INFO</a> (<a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">TuningRecordNode</a>, <a class="el" href="classtvm_1_1runtime_1_1Object.html">runtime::Object</a>)</td></tr>
<tr class="separator:a6270ef8a153eca3d2571ee2d34feb4ff"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:aa4f013b36ab008650dea4fb62d523c43"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1MeasureCandidate.html">MeasureCandidate</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#aa4f013b36ab008650dea4fb62d523c43">AsMeasureCandidate</a> () const</td></tr>
+<tr class="memdesc:aa4f013b36ab008650dea4fb62d523c43"><td class="mdescLeft"> </td><td class="mdescRight">Construct the measure candidate given the initial IR module and trace stored in the tuning record. <a href="#aa4f013b36ab008650dea4fb62d523c43">More...</a><br /></td></tr>
+<tr class="separator:aa4f013b36ab008650dea4fb62d523c43"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac2e3ed776662e66112c37ec4fcb091d1"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html">ObjectRef</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ac2e3ed776662e66112c37ec4fcb091d1">AsJSON</a> () const</td></tr>
<tr class="memdesc:ac2e3ed776662e66112c37ec4fcb091d1"><td class="mdescLeft"> </td><td class="mdescRight">Export the tuning record to a JSON string. <a href="#ac2e3ed776662e66112c37ec4fcb091d1">More...</a><br /></td></tr>
<tr class="separator:ac2e3ed776662e66112c37ec4fcb091d1"><td class="memSeparator" colspan="2"> </td></tr>
@@ -226,6 +229,25 @@ Additional Inherited Members</h2></td></tr>
<p>Export the tuning record to a JSON string. </p>
<dl class="section return"><dt>Returns</dt><dd>An array containing the trace, running secs, serialized target, and argument information. </dd></dl>
+</div>
+</div>
+<a id="aa4f013b36ab008650dea4fb62d523c43"></a>
+<h2 class="memtitle"><span class="permalink"><a href="#aa4f013b36ab008650dea4fb62d523c43">◆ </a></span>AsMeasureCandidate()</h2>
+
+<div class="memitem">
+<div class="memproto">
+ <table class="memname">
+ <tr>
+ <td class="memname"><a class="el" href="classtvm_1_1meta__schedule_1_1MeasureCandidate.html">MeasureCandidate</a> tvm::meta_schedule::TuningRecordNode::AsMeasureCandidate </td>
+ <td>(</td>
+ <td class="paramname"></td><td>)</td>
+ <td> const</td>
+ </tr>
+ </table>
+</div><div class="memdoc">
+
+<p>Construct the measure candidate given the initial IR module and trace stored in the tuning record. </p>
+
</div>
</div>
<a id="a6270ef8a153eca3d2571ee2d34feb4ff"></a>
diff --git a/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode__coll__graph.svg b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode__coll__graph.svg
index 7a9dc864a..d92169874 100644
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+++ b/docs/reference/api/doxygen/classtvm_1_1meta__schedule_1_1TuningRecordNode__coll__graph.svg
@@ -4,150 +4,152 @@
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+<text text-anchor="start" x="512" y="-89.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
+<text text-anchor="middle" x="608.5" y="-78.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::TuningRecordNode</text>
+<polyline fill="none" stroke="#000000" points="504,-71.5 713,-71.5 "/>
+<text text-anchor="start" x="512" y="-59.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<polyline fill="none" stroke="#000000" points="504,-52.5 713,-52.5 "/>
+<text text-anchor="start" x="512" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ VisitAttrs()</text>
+<text text-anchor="start" x="512" y="-29.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DECLARE_FINAL_OBJECT_INFO()</text>
+<text text-anchor="start" x="512" y="-18.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ AsMeasureCandidate()</text>
<text text-anchor="start" x="512" y="-7.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ AsJSON()</text>
</g>
<!-- Node3 -->
<g id="node2" class="node">
<title>Node3</title>
<g id="a_node2"><a xlink:href="classtvm_1_1runtime_1_1Object.html" target="_top" xlink:title="base class of all object containers. ">
-<polygon fill="#ffffff" stroke="#000000" points="0,-138.5 0,-525.5 183,-525.5 183,-138.5 0,-138.5"/>
-<text text-anchor="middle" x="91.5" y="-513.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
-<polyline fill="none" stroke="#000000" points="0,-506.5 183,-506.5 "/>
-<text text-anchor="start" x="8" y="-494.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
-<text text-anchor="start" x="8" y="-483.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
-<text text-anchor="start" x="8" y="-472.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
-<text text-anchor="start" x="8" y="-461.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots_can</text>
-<text text-anchor="start" x="8" y="-450.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_overflow</text>
-<text text-anchor="start" x="8" y="-439.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_visit</text>
-<text text-anchor="start" x="8" y="-428.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_attrs</text>
-<text text-anchor="start" x="8" y="-417.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
-<text text-anchor="start" x="8" y="-406.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
-<text text-anchor="start" x="8" y="-395.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
-<text text-anchor="start" x="8" y="-384.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
-<text text-anchor="start" x="8" y="-373.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_index</text>
-<text text-anchor="start" x="8" y="-362.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
-<text text-anchor="start" x="8" y="-351.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
-<polyline fill="none" stroke="#000000" points="0,-344.5 183,-344.5 "/>
-<text text-anchor="start" x="8" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
-<text text-anchor="start" x="8" y="-321.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKey()</text>
-<text text-anchor="start" x="8" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
-<text text-anchor="start" x="8" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
-<text text-anchor="start" x="8" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<polygon fill="#ffffff" stroke="#000000" points="0,-149.5 0,-536.5 183,-536.5 183,-149.5 0,-149.5"/>
+<text text-anchor="middle" x="91.5" y="-524.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
+<polyline fill="none" stroke="#000000" points="0,-517.5 183,-517.5 "/>
+<text text-anchor="start" x="8" y="-505.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_key</text>
+<text text-anchor="start" x="8" y="-494.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_final</text>
+<text text-anchor="start" x="8" y="-483.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots</text>
+<text text-anchor="start" x="8" y="-472.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_child_slots_can</text>
+<text text-anchor="start" x="8" y="-461.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_overflow</text>
+<text text-anchor="start" x="8" y="-450.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_visit</text>
+<text text-anchor="start" x="8" y="-439.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_attrs</text>
+<text text-anchor="start" x="8" y="-428.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_sequal</text>
+<text text-anchor="start" x="8" y="-417.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="8" y="-406.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_has_method_shash</text>
+<text text-anchor="start" x="8" y="-395.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_reduce</text>
+<text text-anchor="start" x="8" y="-384.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_index</text>
+<text text-anchor="start" x="8" y="-373.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># type_index_</text>
+<text text-anchor="start" x="8" y="-362.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># ref_counter_</text>
+<polyline fill="none" stroke="#000000" points="0,-355.5 183,-355.5 "/>
+<text text-anchor="start" x="8" y="-343.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ type_index()</text>
+<text text-anchor="start" x="8" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKey()</text>
+<text text-anchor="start" x="8" y="-321.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ GetTypeKeyHash()</text>
+<text text-anchor="start" x="8" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ IsInstance()</text>
+<text text-anchor="start" x="8" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="8" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
<text text-anchor="start" x="8" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
<text text-anchor="start" x="8" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
-<text text-anchor="start" x="8" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Object()</text>
+<text text-anchor="start" x="8" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
<text text-anchor="start" x="8" y="-244.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="8" y="-233.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="8" y="-222.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
-<text text-anchor="start" x="8" y="-211.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
-<text text-anchor="start" x="8" y="-200.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
-<text text-anchor="start" x="8" y="-189.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
-<text text-anchor="start" x="8" y="-178.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
-<text text-anchor="start" x="8" y="-167.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
-<text text-anchor="start" x="8" y="-156.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
-<text text-anchor="start" x="8" y="-145.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="8" y="-233.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2Key()</text>
+<text text-anchor="start" x="8" y="-222.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeIndex2KeyHash()</text>
+<text text-anchor="start" x="8" y="-211.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TypeKey2Index()</text>
+<text text-anchor="start" x="8" y="-200.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _GetOrAllocRuntimeTypeIndex()</text>
+<text text-anchor="start" x="8" y="-189.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ RuntimeTypeIndex()</text>
+<text text-anchor="start" x="8" y="-178.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># IncRef()</text>
+<text text-anchor="start" x="8" y="-167.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
+<text text-anchor="start" x="8" y="-156.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
</a>
</g>
</g>
<!-- Node3->Node2 -->
<g id="edge1" class="edge">
<title>Node3->Node2</title>
-<path fill="none" stroke="#191970" d="M190.1775,-198.3855C211.9076,-175.6694 236.3285,-154.2185 262.5,-138 335.9659,-92.473 431.6584,-69.1151 503.782,-57.2741"/>
-<polygon fill="none" stroke="#191970" points="187.5097,-196.1136 183.218,-205.8003 192.6137,-200.9042 187.5097,-196.1136"/>
+<path fill="none" stroke="#191970" d="M190.1571,-209.9202C211.9238,-187.0937 236.3633,-165.4654 262.5,-149 335.9256,-102.7438 431.6216,-77.827 503.7568,-64.7135"/>
+<polygon fill="none" stroke="#191970" points="187.4637,-207.676 183.1852,-217.3685 192.5742,-212.4596 187.4637,-207.676"/>
</g>
<!-- Node3->Node3 -->
<g id="edge2" class="edge">
<title>Node3->Node3</title>
-<path fill="none" stroke="#404040" d="M183.3625,-365.9248C194.0482,-359.6637 201,-348.3555 201,-332 201,-321.0112 197.8618,-312.3007 192.5615,-305.8687"/>
-<polygon fill="none" stroke="#404040" points="192.5184,-305.8322 185.3548,-305.0056 183.3625,-298.0752 190.5261,-298.9017 192.5184,-305.8322"/>
-<text text-anchor="middle" x="227" y="-329.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
+<path fill="none" stroke="#404040" d="M183.3625,-376.9248C194.0482,-370.6637 201,-359.3555 201,-343 201,-332.0112 197.8618,-323.3007 192.5615,-316.8687"/>
+<polygon fill="none" stroke="#404040" points="192.5184,-316.8322 185.3548,-316.0056 183.3625,-309.0752 190.5261,-309.9017 192.5184,-316.8322"/>
+<text text-anchor="middle" x="227" y="-340.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
</g>
<!-- Node4 -->
<g id="node3" class="node">
<title>Node4</title>
<g id="a_node3"><a xlink:href="classtvm_1_1meta__schedule_1_1Workload.html" target="_top" xlink:title="Managed reference to WorkloadNode. ">
-<polygon fill="#ffffff" stroke="#000000" points="271.5,-276 271.5,-388 437.5,-388 437.5,-276 271.5,-276"/>
-<text text-anchor="start" x="279.5" y="-376" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
-<text text-anchor="middle" x="354.5" y="-365" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::Workload</text>
-<polyline fill="none" stroke="#000000" points="271.5,-358 437.5,-358 "/>
-<text text-anchor="middle" x="354.5" y="-346" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
-<polyline fill="none" stroke="#000000" points="271.5,-339 437.5,-339 "/>
+<polygon fill="#ffffff" stroke="#000000" points="271.5,-287 271.5,-399 437.5,-399 437.5,-287 271.5,-287"/>
+<text text-anchor="start" x="279.5" y="-387" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::meta_schedule</text>
+<text text-anchor="middle" x="354.5" y="-376" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">::Workload</text>
+<polyline fill="none" stroke="#000000" points="271.5,-369 437.5,-369 "/>
+<text text-anchor="middle" x="354.5" y="-357" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polyline fill="none" stroke="#000000" points="271.5,-350 437.5,-350 "/>
+<text text-anchor="start" x="279.5" y="-338" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Workload()</text>
<text text-anchor="start" x="279.5" y="-327" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Workload()</text>
-<text text-anchor="start" x="279.5" y="-316" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Workload()</text>
-<text text-anchor="start" x="279.5" y="-305" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_NOTNULLABLE</text>
-<text text-anchor="start" x="279.5" y="-294" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_OBJECT_REF_METHODS()</text>
-<text text-anchor="start" x="279.5" y="-283" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ FromJSON()</text>
+<text text-anchor="start" x="279.5" y="-316" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_NOTNULLABLE</text>
+<text text-anchor="start" x="279.5" y="-305" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_OBJECT_REF_METHODS()</text>
+<text text-anchor="start" x="279.5" y="-294" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ FromJSON()</text>
</a>
</g>
</g>
<!-- Node4->Node2 -->
<g id="edge3" class="edge">
<title>Node4->Node2</title>
-<path fill="none" stroke="#404040" d="M370.9688,-275.6998C385.4651,-233.8316 410.0137,-177.3701 446.5,-138 460.9883,-122.3666 478.7338,-108.658 497.1044,-96.9176"/>
-<polygon fill="none" stroke="#404040" points="497.1423,-96.8943 500.1513,-90.341 507.3579,-90.598 504.3489,-97.1513 497.1423,-96.8943"/>
-<text text-anchor="middle" x="505" y="-112" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> +workload</text>
+<path fill="none" stroke="#404040" d="M371.2557,-286.9623C385.9022,-245.2316 410.5133,-188.8272 446.5,-149 460.2244,-133.811 476.8585,-120.2124 494.1745,-108.3292"/>
+<polygon fill="none" stroke="#404040" points="494.4289,-108.1607 497.2208,-101.5119 504.4319,-101.5318 501.64,-108.1806 494.4289,-108.1607"/>
+<text text-anchor="middle" x="505" y="-123" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> +workload</text>
</g>
<!-- Node5 -->
<g id="node4" class="node">
<title>Node5</title>
<g id="a_node4"><a xlink:href="classtvm_1_1runtime_1_1ObjectRef.html" target="_top" xlink:title="Base class of all object reference. ">
-<polygon fill="#ffffff" stroke="#000000" points="630.5,-563.5 630.5,-785.5 764.5,-785.5 764.5,-563.5 630.5,-563.5"/>
-<text text-anchor="middle" x="697.5" y="-773.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectRef</text>
-<polyline fill="none" stroke="#000000" points="630.5,-766.5 764.5,-766.5 "/>
-<text text-anchor="start" x="638.5" y="-754.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
-<polyline fill="none" stroke="#000000" points="630.5,-747.5 764.5,-747.5 "/>
+<polygon fill="#ffffff" stroke="#000000" points="630.5,-574.5 630.5,-796.5 764.5,-796.5 764.5,-574.5 630.5,-574.5"/>
+<text text-anchor="middle" x="697.5" y="-784.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::ObjectRef</text>
+<polyline fill="none" stroke="#000000" points="630.5,-777.5 764.5,-777.5 "/>
+<text text-anchor="start" x="638.5" y="-765.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<polyline fill="none" stroke="#000000" points="630.5,-758.5 764.5,-758.5 "/>
+<text text-anchor="start" x="638.5" y="-746.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
<text text-anchor="start" x="638.5" y="-735.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
-<text text-anchor="start" x="638.5" y="-724.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ObjectRef()</text>
-<text text-anchor="start" x="638.5" y="-713.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ same_as()</text>
-<text text-anchor="start" x="638.5" y="-702.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator==()</text>
-<text text-anchor="start" x="638.5" y="-691.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator!=()</text>
-<text text-anchor="start" x="638.5" y="-680.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator<()</text>
-<text text-anchor="start" x="638.5" y="-669.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ defined()</text>
-<text text-anchor="start" x="638.5" y="-658.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
-<text text-anchor="start" x="638.5" y="-647.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
-<text text-anchor="start" x="638.5" y="-636.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
-<text text-anchor="start" x="638.5" y="-625.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ use_count()</text>
-<text text-anchor="start" x="638.5" y="-614.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ as()</text>
-<text text-anchor="start" x="638.5" y="-603.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># get_mutable()</text>
-<text text-anchor="start" x="638.5" y="-592.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DowncastNoCheck()</text>
-<text text-anchor="start" x="638.5" y="-581.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># FFIClearAfterMove()</text>
-<text text-anchor="start" x="638.5" y="-570.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetDataPtr()</text>
+<text text-anchor="start" x="638.5" y="-724.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ same_as()</text>
+<text text-anchor="start" x="638.5" y="-713.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator==()</text>
+<text text-anchor="start" x="638.5" y="-702.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator!=()</text>
+<text text-anchor="start" x="638.5" y="-691.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator<()</text>
+<text text-anchor="start" x="638.5" y="-680.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ defined()</text>
+<text text-anchor="start" x="638.5" y="-669.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ get()</text>
+<text text-anchor="start" x="638.5" y="-658.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator->()</text>
+<text text-anchor="start" x="638.5" y="-647.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ unique()</text>
+<text text-anchor="start" x="638.5" y="-636.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ use_count()</text>
+<text text-anchor="start" x="638.5" y="-625.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ as()</text>
+<text text-anchor="start" x="638.5" y="-614.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># get_mutable()</text>
+<text text-anchor="start" x="638.5" y="-603.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DowncastNoCheck()</text>
+<text text-anchor="start" x="638.5" y="-592.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># FFIClearAfterMove()</text>
+<text text-anchor="start" x="638.5" y="-581.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetDataPtr()</text>
</a>
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<title>Node5->Node4</title>
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-<polygon fill="none" stroke="#191970" points="619.8137,-647.1282 630.3676,-648.0593 622.6979,-640.7499 619.8137,-647.1282"/>
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<!-- Node7 -->
<g id="node6" class="node">
<title>Node7</title>
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-<text text-anchor="start" x="463.5" y="-414.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
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-<text text-anchor="middle" x="519.5" y="-392.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::FloatImm > ></text>
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-<text text-anchor="start" x="463.5" y="-373.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
-<polyline fill="none" stroke="#000000" points="455.5,-366.5 583.5,-366.5 "/>
+<polygon fill="#ffffff" stroke="#000000" points="455.5,-248.5 455.5,-437.5 583.5,-437.5 583.5,-248.5 455.5,-248.5"/>
+<text text-anchor="start" x="463.5" y="-425.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
+<text text-anchor="start" x="463.5" y="-414.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::runtime::Array</text>
+<text text-anchor="middle" x="519.5" y="-403.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::FloatImm > ></text>
+<polyline fill="none" stroke="#000000" points="455.5,-396.5 583.5,-396.5 "/>
+<text text-anchor="start" x="463.5" y="-384.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<polyline fill="none" stroke="#000000" points="455.5,-377.5 583.5,-377.5 "/>
+<text text-anchor="start" x="463.5" y="-365.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="463.5" y="-354.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="463.5" y="-343.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="463.5" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
@@ -155,30 +157,30 @@
<text text-anchor="start" x="463.5" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="463.5" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="463.5" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
-<text text-anchor="start" x="463.5" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
+<text text-anchor="start" x="463.5" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
<text text-anchor="start" x="463.5" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="463.5" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="463.5" y="-244.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
+<text text-anchor="start" x="463.5" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
</a>
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<!-- Node5->Node7 -->
<g id="edge7" class="edge">
<title>Node5->Node7</title>
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-<polygon fill="none" stroke="#191970" points="621.7958,-579.7131 630.2807,-586.058 627.6045,-575.8067 621.7958,-579.7131"/>
+<path fill="none" stroke="#191970" d="M624.4582,-588.4002C613.3678,-571.6904 602.6055,-554.1668 593.5,-537 576.9467,-505.7916 562.2227,-470.0474 550.3532,-437.8134"/>
+<polygon fill="none" stroke="#191970" points="621.7958,-590.7131 630.2807,-597.058 627.6045,-586.8067 621.7958,-590.7131"/>
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<!-- Node8 -->
<g id="node7" class="node">
<title>Node8</title>
<g id="a_node7"><a xlink:href="classtvm_1_1runtime_1_1Optional.html" target="_top" xlink:title="{tvm::runtime::Optional\l\< tvm::runtime::Array\l\< tvm::meta_schedule::ArgInfo \> \>\n|+ _type_is_nullable\l|+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ operator=()\l+ operator=()\land 15 more...\l}">
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-<text text-anchor="start" x="610" y="-414.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
-<text text-anchor="start" x="610" y="-403.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::runtime::Array</text>
-<text text-anchor="middle" x="697.5" y="-392.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::meta_schedule::ArgInfo > ></text>
-<polyline fill="none" stroke="#000000" points="602,-385.5 793,-385.5 "/>
-<text text-anchor="start" x="610" y="-373.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
-<polyline fill="none" stroke="#000000" points="602,-366.5 793,-366.5 "/>
+<polygon fill="#ffffff" stroke="#000000" points="602,-248.5 602,-437.5 793,-437.5 793,-248.5 602,-248.5"/>
+<text text-anchor="start" x="610" y="-425.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
+<text text-anchor="start" x="610" y="-414.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::runtime::Array</text>
+<text text-anchor="middle" x="697.5" y="-403.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::meta_schedule::ArgInfo > ></text>
+<polyline fill="none" stroke="#000000" points="602,-396.5 793,-396.5 "/>
+<text text-anchor="start" x="610" y="-384.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<polyline fill="none" stroke="#000000" points="602,-377.5 793,-377.5 "/>
+<text text-anchor="start" x="610" y="-365.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="610" y="-354.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="610" y="-343.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="610" y="-332.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
@@ -186,29 +188,29 @@
<text text-anchor="start" x="610" y="-310.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="610" y="-299.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="610" y="-288.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
-<text text-anchor="start" x="610" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
+<text text-anchor="start" x="610" y="-277.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
<text text-anchor="start" x="610" y="-266.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="610" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="610" y="-244.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
+<text text-anchor="start" x="610" y="-255.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
</a>
</g>
</g>
<!-- Node5->Node8 -->
<g id="edge9" class="edge">
<title>Node5->Node8</title>
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-<polygon fill="none" stroke="#191970" points="694.0001,-553.3 697.5,-563.3001 701.0001,-553.3001 694.0001,-553.3"/>
+<path fill="none" stroke="#191970" d="M697.5,-564.1125C697.5,-522.5481 697.5,-476.6904 697.5,-437.5637"/>
+<polygon fill="none" stroke="#191970" points="694.0001,-564.3 697.5,-574.3001 701.0001,-564.3001 694.0001,-564.3"/>
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<!-- Node9 -->
<g id="node8" class="node">
<title>Node9</title>
<g id="a_node8"><a xlink:href="classtvm_1_1runtime_1_1Optional.html" target="_top" xlink:title="{tvm::runtime::Optional\l\< tvm::Target \>\n|+ _type_is_nullable\l|+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ Optional()\l+ operator=()\l+ operator=()\land 15 more...\l}">
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-<text text-anchor="start" x="819.5" y="-409" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
-<text text-anchor="middle" x="875.5" y="-398" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::Target ></text>
-<polyline fill="none" stroke="#000000" points="811.5,-391 939.5,-391 "/>
-<text text-anchor="start" x="819.5" y="-379" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
-<polyline fill="none" stroke="#000000" points="811.5,-372 939.5,-372 "/>
+<polygon fill="#ffffff" stroke="#000000" points="811.5,-254 811.5,-432 939.5,-432 939.5,-254 811.5,-254"/>
+<text text-anchor="start" x="819.5" y="-420" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Optional</text>
+<text text-anchor="middle" x="875.5" y="-409" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">< tvm::Target ></text>
+<polyline fill="none" stroke="#000000" points="811.5,-402 939.5,-402 "/>
+<text text-anchor="start" x="819.5" y="-390" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ _type_is_nullable</text>
+<polyline fill="none" stroke="#000000" points="811.5,-383 939.5,-383 "/>
+<text text-anchor="start" x="819.5" y="-371" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="819.5" y="-360" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="819.5" y="-349" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="819.5" y="-338" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
@@ -216,101 +218,100 @@
<text text-anchor="start" x="819.5" y="-316" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="819.5" y="-305" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
<text text-anchor="start" x="819.5" y="-294" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
-<text text-anchor="start" x="819.5" y="-283" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Optional()</text>
+<text text-anchor="start" x="819.5" y="-283" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
<text text-anchor="start" x="819.5" y="-272" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="819.5" y="-261" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ operator=()</text>
-<text text-anchor="start" x="819.5" y="-250" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
+<text text-anchor="start" x="819.5" y="-261" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">and 15 more...</text>
</a>
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<g id="edge11" class="edge">
<title>Node5->Node9</title>
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+<path fill="none" stroke="#191970" d="M770.3361,-589.9997C781.8774,-572.8284 793.0912,-554.7389 802.5,-537 819.9524,-504.0963 835.2252,-466.0879 847.2281,-432.4807"/>
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<g id="node9" class="node">
<title>Node10</title>
<g id="a_node9"><a xlink:href="classtvm_1_1tir_1_1Trace.html" target="_top" xlink:title="Managed reference to TraceNode. ">
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-<text text-anchor="middle" x="1028.5" y="-376" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::tir::Trace</text>
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-<text text-anchor="middle" x="1028.5" y="-357" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
-<polyline fill="none" stroke="#000000" points="957.5,-350 1099.5,-350 "/>
+<polygon fill="#ffffff" stroke="#000000" points="957.5,-287 957.5,-399 1099.5,-399 1099.5,-287 957.5,-287"/>
+<text text-anchor="middle" x="1028.5" y="-387" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::tir::Trace</text>
+<polyline fill="none" stroke="#000000" points="957.5,-380 1099.5,-380 "/>
+<text text-anchor="middle" x="1028.5" y="-368" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> </text>
+<polyline fill="none" stroke="#000000" points="957.5,-361 1099.5,-361 "/>
+<text text-anchor="start" x="965.5" y="-349" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Trace()</text>
<text text-anchor="start" x="965.5" y="-338" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Trace()</text>
-<text text-anchor="start" x="965.5" y="-327" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ Trace()</text>
-<text text-anchor="start" x="965.5" y="-316" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_MUTABLE</text>
-<text text-anchor="start" x="965.5" y="-305" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_NOTNULLABLE_OBJECT</text>
-<text text-anchor="start" x="965.5" y="-294" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_REF_METHODS()</text>
-<text text-anchor="start" x="965.5" y="-283" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ApplyJSONToSchedule()</text>
+<text text-anchor="start" x="965.5" y="-327" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ TVM_DEFINE_MUTABLE</text>
+<text text-anchor="start" x="965.5" y="-316" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_NOTNULLABLE_OBJECT</text>
+<text text-anchor="start" x="965.5" y="-305" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">_REF_METHODS()</text>
+<text text-anchor="start" x="965.5" y="-294" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ ApplyJSONToSchedule()</text>
</a>
</g>
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<g id="edge13" class="edge">
<title>Node5->Node10</title>
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<g id="node5" class="node">
<title>Node6</title>
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diff --git a/docs/reference/api/doxygen/database_8h_source.html b/docs/reference/api/doxygen/database_8h_source.html
index bc66872b3..2aa6b4a1a 100644
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@@ -66,9 +66,9 @@ $(function() {
<div class="title">database.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="database_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more co [...]
+<a href="database_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more co [...]
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_a93d2f3debadefcc713bbc045127ca8f7"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#a93d2f3debadefcc713bbc045127ca8f7">tvm::meta_schedule::WorkloadNode::TVM_DECLARE_FINAL_OBJECT_INFO</a></div><div class="ttdeci">TVM_DECLARE_FINAL_OBJECT_INFO(WorkloadNode, runtime::Object)</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a7d7d50ae9b6c43e064b38db91bc8123d"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a7d7d50ae9b6c43e064b38db91bc8123d">tvm::meta_schedule::PyDatabaseNode::f_commit_tuning_record</a></div><div class="ttdeci">FCommitTuningRecord f_commit_tuning_record</div><div class="ttdoc">The packed function to the CommitTuningRecord function. </div><div class="ttdef"><b>Definition:</b> database.h:238</d [...]
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a7d7d50ae9b6c43e064b38db91bc8123d"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a7d7d50ae9b6c43e064b38db91bc8123d">tvm::meta_schedule::PyDatabaseNode::f_commit_tuning_record</a></div><div class="ttdeci">FCommitTuningRecord f_commit_tuning_record</div><div class="ttdoc">The packed function to the CommitTuningRecord function. </div><div class="ttdef"><b>Definition:</b> database.h:254</d [...]
<div class="ttc" id="trace_8h_html"><div class="ttname"><a href="trace_8h.html">trace.h</a></div></div>
<div class="ttc" id="object_8h_html_a98fa3013ab23958a9f05200330e35805"><div class="ttname"><a href="object_8h.html#a98fa3013ab23958a9f05200330e35805">TVM_DEFINE_MUTABLE_NOTNULLABLE_OBJECT_REF_METHODS</a></div><div class="ttdeci">#define TVM_DEFINE_MUTABLE_NOTNULLABLE_OBJECT_REF_METHODS(TypeName, ParentType, ObjectName)</div><div class="ttdef"><b>Definition:</b> object.h:758</div></div>
<div class="ttc" id="structtvm_1_1meta__schedule_1_1WorkloadHash_html"><div class="ttname"><a href="structtvm_1_1meta__schedule_1_1WorkloadHash.html">tvm::meta_schedule::WorkloadHash</a></div><div class="ttdoc">The hash method for Workload. </div><div class="ttdef"><b>Definition:</b> database.h:90</div></div>
@@ -76,55 +76,58 @@ $(function() {
<div class="ttc" id="ir_2expr_8h_html"><div class="ttname"><a href="ir_2expr_8h.html">expr.h</a></div><div class="ttdoc">Base expr nodes in TVM. </div></div>
<div class="ttc" id="ir_2module_8h_html"><div class="ttname"><a href="ir_2module_8h.html">module.h</a></div><div class="ttdoc">IRModule that holds the functions and type definitions. </div></div>
<div class="ttc" id="namespacetvm_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="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a45a380cfa2edfd63056fb1a00f9aac35"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a45a380cfa2edfd63056fb1a00f9aac35">tvm::meta_schedule::TuningRecordNode::target</a></div><div class="ttdeci">Optional< Target > target</div><div class="ttdoc">The target for tuning. </div><div class="ttdef"><b>Definition:</b> database.h:111</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a45a380cfa2edfd63056fb1a00f9aac35"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a45a380cfa2edfd63056fb1a00f9aac35">tvm::meta_schedule::TuningRecordNode::target</a></div><div class="ttdeci">Optional< Target > target</div><div class="ttdoc">The target for tuning. </div><div class="ttdef"><b>Definition:</b> database.h:114</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_aad19a5cb8e2c623e355ca5e2a98c4c18"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#aad19a5cb8e2c623e355ca5e2a98c4c18">tvm::meta_schedule::WorkloadNode::THashCode</a></div><div class="ttdeci">size_t THashCode</div><div class="ttdoc">The type of structural hash. </div><div class="ttdef"><b>Definition:</b> database.h:40</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1DatabaseNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></div><div class="ttdef"><b>Definition:</b> database.h:162</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a52fb1116090619e95fb6b28352308eed"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">tvm::meta_schedule::PyDatabaseNode::f_get_top_k</a></div><div class="ttdeci">FGetTopK f_get_top_k</div><div class="ttdoc">The packed function to the GetTopK function. </div><div class="ttdef"><b>Definition:</b> database.h:240</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1DatabaseNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">tvm::meta_schedule::DatabaseNode</a></div><div class="ttdef"><b>Definition:</b> database.h:168</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a52fb1116090619e95fb6b28352308eed"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">tvm::meta_schedule::PyDatabaseNode::f_get_top_k</a></div><div class="ttdeci">FGetTopK f_get_top_k</div><div class="ttdoc">The packed function to the GetTopK function. </div><div class="ttdef"><b>Definition:</b> database.h:256</div></div>
<div class="ttc" id="structtvm_1_1meta__schedule_1_1WorkloadHash_html_a7cb09ddc6c76d9d00ddbeab8502d97cb"><div class="ttname"><a href="structtvm_1_1meta__schedule_1_1WorkloadHash.html#a7cb09ddc6c76d9d00ddbeab8502d97cb">tvm::meta_schedule::WorkloadHash::operator()</a></div><div class="ttdeci">size_t operator()(const Workload &a) const</div><div class="ttdef"><b>Definition:</b> database.h:91</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Object_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a></div><div class="ttdoc">base class of all object containers. </div><div class="ttdef"><b>Definition:</b> object.h:167</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></div><div class="ttdoc">The database with customized methods on the python-side. </div><div class="ttdef"><b>Definition:</b> database.h:201</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html">tvm::meta_schedule::PyDatabaseNode</a></div><div class="ttdoc">The database with customized methods on the python-side. </div><div class="ttdef"><b>Definition:</b> database.h:212</div></div>
<div class="ttc" id="classtvm_1_1StructuralEqual_html"><div class="ttname"><a href="classtvm_1_1StructuralEqual.html">tvm::StructuralEqual</a></div><div class="ttdoc">Content-aware structural equality comparator for objects. </div><div class="ttdef"><b>Definition:</b> structural_equal.h:81</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a8cc2d64f796593a1a774eef259f17b29"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a8cc2d64f796593a1a774eef259f17b29">tvm::meta_schedule::TuningRecordNode::trace</a></div><div class="ttdeci">tir::Trace trace</div><div class="ttdoc">The trace tuned. </div><div class="ttdef"><b>Definition:</b> database.h:105</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a8cc2d64f796593a1a774eef259f17b29"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a8cc2d64f796593a1a774eef259f17b29">tvm::meta_schedule::TuningRecordNode::trace</a></div><div class="ttdeci">tir::Trace trace</div><div class="ttdoc">The trace tuned. </div><div class="ttdef"><b>Definition:</b> database.h:108</div></div>
<div class="ttc" id="arg__info_8h_html"><div class="ttname"><a href="arg__info_8h.html">arg_info.h</a></div></div>
<div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Runtime Array container types. </div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_ac7ae1a05fe5c7858f5860133a82bc7b7"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ac7ae1a05fe5c7858f5860133a82bc7b7">tvm::meta_schedule::PyDatabaseNode::f_size</a></div><div class="ttdeci">FSize f_size</div><div class="ttdoc">The packed function to the Size function. </div><div class="ttdef"><b>Definition:</b> database.h:242</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_ac7ae1a05fe5c7858f5860133a82bc7b7"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ac7ae1a05fe5c7858f5860133a82bc7b7">tvm::meta_schedule::PyDatabaseNode::f_size</a></div><div class="ttdeci">FSize f_size</div><div class="ttdoc">The packed function to the Size function. </div><div class="ttdef"><b>Definition:</b> database.h:260</div></div>
<div class="ttc" id="classtvm_1_1AttrVisitor_html"><div class="ttname"><a href="classtvm_1_1AttrVisitor.html">tvm::AttrVisitor</a></div><div class="ttdoc">Visitor class to get the attributes of an AST/IR node. The content is going to be called for each fie...</div><div class="ttdef"><b>Definition:</b> reflection.h:52</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a09f1921d607d7ef4397876c15d2f0b08"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a09f1921d607d7ef4397876c15d2f0b08">tvm::meta_schedule::TuningRecordNode::args_info</a></div><div class="ttdeci">Optional< Array< ArgInfo > > args_info</div><div class="ttdoc">The argument information. </div><div class="ttdef"><b>Definition:</b> database.h:113</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a09f1921d607d7ef4397876c15d2f0b08"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a09f1921d607d7ef4397876c15d2f0b08">tvm::meta_schedule::TuningRecordNode::args_info</a></div><div class="ttdeci">Optional< Array< ArgInfo > > args_info</div><div class="ttdoc">The argument information. </div><div class="ttdef"><b>Definition:</b> database.h:116</div></div>
<div class="ttc" id="structtvm_1_1meta__schedule_1_1WorkloadEqual_html_aa29256c62e52bef8c9a0f7881d3fc601"><div class="ttname"><a href="structtvm_1_1meta__schedule_1_1WorkloadEqual.html#aa29256c62e52bef8c9a0f7881d3fc601">tvm::meta_schedule::WorkloadEqual::operator()</a></div><div class="ttdeci">bool operator()(const Workload &a, const Workload &b) const</div><div class="ttdef"><b>Definition:</b> database.h:96</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1Database_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1Database.html">tvm::meta_schedule::Database</a></div><div class="ttdoc">Managed reference to DatabaseNode. </div><div class="ttdef"><b>Definition:</b> database.h:289</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1Database_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1Database.html">tvm::meta_schedule::Database</a></div><div class="ttdoc">Managed reference to DatabaseNode. </div><div class="ttdef"><b>Definition:</b> database.h:314</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Array_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Array.html">tvm::runtime::Array</a></div><div class="ttdoc">Array, container representing a contiguous sequence of ObjectRefs. </div><div class="ttdef"><b>Definition:</b> array.h:270</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a38195f2c3aea9ae4890477393ab2c624"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a38195f2c3aea9ae4890477393ab2c624">tvm::meta_schedule::PyDatabaseNode::HasWorkload</a></div><div class="ttdeci">bool HasWorkload(const IRModule &mod) final</div><div class="ttdoc">Check if the database has the given workload. </div><div class="ttdef"><b>Definition:</b> database.h:255</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a38195f2c3aea9ae4890477393ab2c624"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a38195f2c3aea9ae4890477393ab2c624">tvm::meta_schedule::PyDatabaseNode::HasWorkload</a></div><div class="ttdeci">bool HasWorkload(const IRModule &mod) final</div><div class="ttdoc">Check if the database has the given workload. </div><div class="ttdef"><b>Definition:</b> database.h:274</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_a3929f2761c168c25de6be2247b913911"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#a3929f2761c168c25de6be2247b913911">tvm::meta_schedule::WorkloadNode::mod</a></div><div class="ttdeci">IRModule mod</div><div class="ttdoc">The workload&#39;s IRModule. </div><div class="ttdef"><b>Definition:</b> database.h:42</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a00aeeedbe4d1d6008224d98c62739581"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a00aeeedbe4d1d6008224d98c62739581">tvm::meta_schedule::TuningRecordNode::run_secs</a></div><div class="ttdeci">Optional< Array< FloatImm > > run_secs</div><div class="ttdoc">The profiling result in seconds. </div><div class="ttdef"><b>Definition:</b> database.h:109</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_a00aeeedbe4d1d6008224d98c62739581"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#a00aeeedbe4d1d6008224d98c62739581">tvm::meta_schedule::TuningRecordNode::run_secs</a></div><div class="ttdeci">Optional< Array< FloatImm > > run_secs</div><div class="ttdoc">The profiling result in seconds. </div><div class="ttdef"><b>Definition:</b> database.h:112</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1String_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1String.html">tvm::runtime::String</a></div><div class="ttdoc">Reference to string objects. </div><div class="ttdef"><b>Definition:</b> string.h:129</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1TypedPackedFunc_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1TypedPackedFunc.html">tvm::runtime::TypedPackedFunc< bool(const IRModule &)></a></div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a36817d04978253571fef7d01427ce9c0"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a36817d04978253571fef7d01427ce9c0">tvm::meta_schedule::PyDatabaseNode::Size</a></div><div class="ttdeci">int64_t Size() final</div><div class="ttdoc">Get the size of the database. </div><div class="ttdef"><b>Definition:</b> database.h:276</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a36817d04978253571fef7d01427ce9c0"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a36817d04978253571fef7d01427ce9c0">tvm::meta_schedule::PyDatabaseNode::Size</a></div><div class="ttdeci">int64_t Size() final</div><div class="ttdoc">Get the size of the database. </div><div class="ttdef"><b>Definition:</b> database.h:301</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_ab533ae06bb310ffbd8acb954e253b7db"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#ab533ae06bb310ffbd8acb954e253b7db">tvm::meta_schedule::WorkloadNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> database.h:46</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_ad07d7d9e78771eaa2e6e65f84e032401"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">tvm::meta_schedule::PyDatabaseNode::GetAllTuningRecords</a></div><div class="ttdeci">Array< TuningRecord > GetAllTuningRecords() final</div><div class="ttdoc">Get all tuning records from the database. </div><div class="ttdef"><b>Definition:</b> database.h:295</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1ObjectRef_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1ObjectRef.html">tvm::runtime::ObjectRef</a></div><div class="ttdoc">Base class of all object reference. </div><div class="ttdef"><b>Definition:</b> object.h:511</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></div><div class="ttdoc">The class of tuning records. </div><div class="ttdef"><b>Definition:</b> database.h:102</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1MeasureCandidate_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1MeasureCandidate.html">tvm::meta_schedule::MeasureCandidate</a></div><div class="ttdoc">Managed reference to MeasureCandidateNode. </div><div class="ttdef"><b>Definition:</b> measure_candidate.h:53</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html">tvm::meta_schedule::TuningRecordNode</a></div><div class="ttdoc">The class of tuning records. </div><div class="ttdef"><b>Definition:</b> database.h:105</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_ad6ac6e9052f30846d72489ced86a7690"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#ad6ac6e9052f30846d72489ced86a7690">tvm::meta_schedule::WorkloadNode::_type_key</a></div><div class="ttdeci">static constexpr const char * _type_key</div><div class="ttdef"><b>Definition:</b> database.h:51</div></div>
<div class="ttc" id="object_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="classtvm_1_1IRModule_html"><div class="ttname"><a href="classtvm_1_1IRModule.html">tvm::IRModule</a></div><div class="ttdoc">Managed reference class to IRModuleNode. </div><div class="ttdef"><b>Definition:</b> module.h:360</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_aa0ee452b287813b9509e649397846a3c"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#aa0ee452b287813b9509e649397846a3c">tvm::meta_schedule::WorkloadNode::AsJSON</a></div><div class="ttdeci">ObjectRef AsJSON() const</div><div class="ttdoc">Export the workload to a JSON string. </div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_add146bf1e2006f72ed1534b2004bcb06"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#add146bf1e2006f72ed1534b2004bcb06">tvm::meta_schedule::PyDatabaseNode::f_has_workload</a></div><div class="ttdeci">FHasWorkload f_has_workload</div><div class="ttdoc">The packed function to the HasWorkload function. </div><div class="ttdef"><b>Definition:</b> database.h:234</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a00614b22bd1cae147dc0d83cdd071187"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a00614b22bd1cae147dc0d83cdd071187">tvm::meta_schedule::PyDatabaseNode::CommitTuningRecord</a></div><div class="ttdeci">void CommitTuningRecord(const TuningRecord &record) final</div><div class="ttdoc">Add a tuning record to the database. </div><div class="ttdef"><b>Definition:</b> database.h:265</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_aa0bd64983cde2fc6ef1547448352981c"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aa0bd64983cde2fc6ef1547448352981c">tvm::meta_schedule::PyDatabaseNode::f_commit_workload</a></div><div class="ttdeci">FCommitWorkload f_commit_workload</div><div class="ttdoc">The packed function to the CommitWorkload function. </div><div class="ttdef"><b>Definition:</b> database.h:236</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_add146bf1e2006f72ed1534b2004bcb06"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#add146bf1e2006f72ed1534b2004bcb06">tvm::meta_schedule::PyDatabaseNode::f_has_workload</a></div><div class="ttdeci">FHasWorkload f_has_workload</div><div class="ttdoc">The packed function to the HasWorkload function. </div><div class="ttdef"><b>Definition:</b> database.h:250</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a00614b22bd1cae147dc0d83cdd071187"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a00614b22bd1cae147dc0d83cdd071187">tvm::meta_schedule::PyDatabaseNode::CommitTuningRecord</a></div><div class="ttdeci">void CommitTuningRecord(const TuningRecord &record) final</div><div class="ttdoc">Add a tuning record to the database. </div><div class="ttdef"><b>Definition:</b> database.h:284</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_aa0bd64983cde2fc6ef1547448352981c"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aa0bd64983cde2fc6ef1547448352981c">tvm::meta_schedule::PyDatabaseNode::f_commit_workload</a></div><div class="ttdeci">FCommitWorkload f_commit_workload</div><div class="ttdoc">The packed function to the CommitWorkload function. </div><div class="ttdef"><b>Definition:</b> database.h:252</div></div>
<div class="ttc" id="target_8h_html"><div class="ttname"><a href="target_8h.html">target.h</a></div><div class="ttdoc">Compilation target object. </div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a12d64aa44d3d2ab37a6600d17be3e708"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a12d64aa44d3d2ab37a6600d17be3e708">tvm::meta_schedule::PyDatabaseNode::CommitWorkload</a></div><div class="ttdeci">Workload CommitWorkload(const IRModule &mod) final</div><div class="ttdoc">Look up or add workload to the database if missing. </div><div class="ttdef"><b>Definition:</b> database.h:260</d [...]
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a12d64aa44d3d2ab37a6600d17be3e708"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a12d64aa44d3d2ab37a6600d17be3e708">tvm::meta_schedule::PyDatabaseNode::CommitWorkload</a></div><div class="ttdeci">Workload CommitWorkload(const IRModule &mod) final</div><div class="ttdoc">Look up or add workload to the database if missing. </div><div class="ttdef"><b>Definition:</b> database.h:279</d [...]
<div class="ttc" id="classtvm_1_1tir_1_1Trace_html"><div class="ttname"><a href="classtvm_1_1tir_1_1Trace.html">tvm::tir::Trace</a></div><div class="ttdoc">Managed reference to TraceNode. </div><div class="ttdef"><b>Definition:</b> trace.h:141</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_aafdd0874be052072521b2aa8a6c56d5f"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f">tvm::meta_schedule::PyDatabaseNode::f_get_all_tuning_records</a></div><div class="ttdeci">FGetAllTuningRecords f_get_all_tuning_records</div><div class="ttdoc">The packed function to the GetAllTuningRecords function. </div><div class="ttdef"><b>Definition:</b> database.h: [...]
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html_a96812f1418c68d5aeb11331fd76aab1c"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html#a96812f1418c68d5aeb11331fd76aab1c">tvm::meta_schedule::WorkloadNode::shash</a></div><div class="ttdeci">THashCode shash</div><div class="ttdoc">The workload&#39;s structural hash. </div><div class="ttdef"><b>Definition:</b> database.h:44</div></div>
<div class="ttc" id="classtvm_1_1runtime_1_1Optional_html"><div class="ttname"><a href="classtvm_1_1runtime_1_1Optional.html">tvm::runtime::Optional</a></div><div class="ttdoc">Optional container that to represent to a Nullable variant of T. </div><div class="ttdef"><b>Definition:</b> optional.h:51</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1Workload_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1Workload.html">tvm::meta_schedule::Workload</a></div><div class="ttdoc">Managed reference to WorkloadNode. </div><div class="ttdef"><b>Definition:</b> database.h:65</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_adebe3a6bfb55e5ce0807b97f12a6c39e"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#adebe3a6bfb55e5ce0807b97f12a6c39e">tvm::meta_schedule::PyDatabaseNode::GetTopK</a></div><div class="ttdeci">Array< TuningRecord > GetTopK(const Workload &workload, int top_k) final</div><div class="ttdoc">Get the top K tuning records of given workload from the database. </div><div class="ttdef">< [...]
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_adebe3a6bfb55e5ce0807b97f12a6c39e"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#adebe3a6bfb55e5ce0807b97f12a6c39e">tvm::meta_schedule::PyDatabaseNode::GetTopK</a></div><div class="ttdeci">Array< TuningRecord > GetTopK(const Workload &workload, int top_k) final</div><div class="ttdoc">Get the top K tuning records of given workload from the database. </div><div class="ttdef">< [...]
<div class="ttc" id="reflection_8h_html"><div class="ttname"><a href="reflection_8h.html">reflection.h</a></div><div class="ttdoc">Reflection and serialization of compiler IR/AST nodes. </div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a1a24b977e3d25a7ffab704e12457fb66"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a1a24b977e3d25a7ffab704e12457fb66">tvm::meta_schedule::PyDatabaseNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> database.h:244</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecord_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecord.html">tvm::meta_schedule::TuningRecord</a></div><div class="ttdoc">The managed reference of TuningRecordNode. </div><div class="ttdef"><b>Definition:</b> database.h:138</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1PyDatabaseNode_html_a1a24b977e3d25a7ffab704e12457fb66"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a1a24b977e3d25a7ffab704e12457fb66">tvm::meta_schedule::PyDatabaseNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> database.h:262</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecord_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecord.html">tvm::meta_schedule::TuningRecord</a></div><div class="ttdoc">The managed reference of TuningRecordNode. </div><div class="ttdef"><b>Definition:</b> database.h:144</div></div>
<div class="ttc" id="object_8h_html_ac2b7418e9549512b5db0126cf2a716f1"><div class="ttname"><a href="object_8h.html#ac2b7418e9549512b5db0126cf2a716f1">TVM_DECLARE_BASE_OBJECT_INFO</a></div><div class="ttdeci">#define TVM_DECLARE_BASE_OBJECT_INFO(TypeName, ParentType)</div><div class="ttdoc">helper macro to declare a base object type that can be inherited. </div><div class="ttdef"><b>Definition:</b> object.h:648</div></div>
<div class="ttc" id="object_8h_html_a782d0de62fbf75736e29c1e79c22c7f1"><div class="ttname"><a href="object_8h.html#a782d0de62fbf75736e29c1e79c22c7f1">TVM_DEFINE_NOTNULLABLE_OBJECT_REF_METHODS</a></div><div class="ttdeci">#define TVM_DEFINE_NOTNULLABLE_OBJECT_REF_METHODS(TypeName, ParentType, ObjectName)</div><div class="ttdef"><b>Definition:</b> object.h:728</div></div>
<div class="ttc" id="packed__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="structtvm_1_1meta__schedule_1_1WorkloadEqual_html"><div class="ttname"><a href="structtvm_1_1meta__schedule_1_1WorkloadEqual.html">tvm::meta_schedule::WorkloadEqual</a></div><div class="ttdoc">The equality check for Workload. </div><div class="ttdef"><b>Definition:</b> database.h:95</div></div>
<div class="ttc" id="classtvm_1_1meta__schedule_1_1WorkloadNode_html"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1WorkloadNode.html">tvm::meta_schedule::WorkloadNode</a></div><div class="ttdoc">A workload, i.e. an IRModule and its structural hash. </div><div class="ttdef"><b>Definition:</b> database.h:37</div></div>
-<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_ad023a7eb8d2ff99ddbae3e1fcb5bcce8"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ad023a7eb8d2ff99ddbae3e1fcb5bcce8">tvm::meta_schedule::TuningRecordNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> database.h:115</div></div>
+<div class="ttc" id="classtvm_1_1meta__schedule_1_1TuningRecordNode_html_ad023a7eb8d2ff99ddbae3e1fcb5bcce8"><div class="ttname"><a href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#ad023a7eb8d2ff99ddbae3e1fcb5bcce8">tvm::meta_schedule::TuningRecordNode::VisitAttrs</a></div><div class="ttdeci">void VisitAttrs(tvm::AttrVisitor *v)</div><div class="ttdef"><b>Definition:</b> database.h:118</div></div>
</div><!-- fragment --></div><!-- contents -->
<!-- start footer part -->
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diff --git a/docs/reference/api/doxygen/functions_a.html b/docs/reference/api/doxygen/functions_a.html
index 14700eaaa..a96d2778a 100644
--- a/docs/reference/api/doxygen/functions_a.html
+++ b/docs/reference/api/doxygen/functions_a.html
@@ -395,6 +395,9 @@ $(function() {
, <a class="el" href="classtvm_1_1runtime_1_1profiling_1_1ReportNode.html#a14a4f9e4ab99622474e423f7adbd26e3">tvm::runtime::profiling::ReportNode</a>
, <a class="el" href="classtvm_1_1tir_1_1TraceNode.html#a6d3d290467daace39806455b618340e1">tvm::tir::TraceNode</a>
</li>
+<li>AsMeasureCandidate()
+: <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#aa4f013b36ab008650dea4fb62d523c43">tvm::meta_schedule::TuningRecordNode</a>
+</li>
<li>AsObjectRef()
: <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_</a>
</li>
@@ -429,7 +432,7 @@ $(function() {
, <a class="el" href="classtvm_1_1runtime_1_1Map.html#a7fbfe0e01b0fa54e151bd481956dcfec">tvm::runtime::Map< K, V, typename, typename ></a>
, <a class="el" href="classtvm_1_1runtime_1_1MapNode.html#a49edd4ddc34a4e0b097c34560b9b3b4e">tvm::runtime::MapNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1ShapeTuple.html#a07d50937020663f46ce9b1f31f066a7a">tvm::runtime::ShapeTuple</a>
-, <a class="el" href="classtvm_1_1runtime_1_1SmallMapNode.html#a866679f23f724edc2d165f530f058b09">tvm::runtime::SmallMapNode</a>
+, <a class="el" href="classtvm_1_1runtime_1_1SmallMapNode.html#a0593c84ceb05afb1a3f87045a3dc3a59">tvm::runtime::SmallMapNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1String.html#aaeda6a88310d41a22ce884fb1570b0d2">tvm::runtime::String</a>
</li>
<li>attach_ivar
@@ -454,7 +457,7 @@ $(function() {
: <a class="el" href="structtvm_1_1AttrError.html#a3285db0171872bc2fdde8243f6e801d9">tvm::AttrError</a>
</li>
<li>AttrInitEntry()
-: <a class="el" href="structtvm_1_1detail_1_1AttrInitEntry.html#af07c4a3a8f4663ac03ae238ab7b9d791">tvm::detail::AttrInitEntry< T ></a>
+: <a class="el" href="structtvm_1_1detail_1_1AttrInitEntry.html#ad68ac350b0d49e97caab8443cc8fb08b">tvm::detail::AttrInitEntry< T ></a>
</li>
<li>AttrInitVisitor()
: <a class="el" href="classtvm_1_1detail_1_1AttrInitVisitor.html#ac3c800c9249fee195db2a5fa473fe960">tvm::detail::AttrInitVisitor< FFind ></a>
diff --git a/docs/reference/api/doxygen/functions_f.html b/docs/reference/api/doxygen/functions_f.html
index 71f06b538..4df56bf96 100644
--- a/docs/reference/api/doxygen/functions_f.html
+++ b/docs/reference/api/doxygen/functions_f.html
@@ -111,6 +111,9 @@ $(function() {
<li>f_generate_measure_candidates
: <a class="el" href="classtvm_1_1meta__schedule_1_1PySearchStrategyNode.html#a5fdfb43b58d50fc34d8c515c9c9b7398">tvm::meta_schedule::PySearchStrategyNode</a>
</li>
+<li>f_get_all_tuning_records
+: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>f_get_top_k
: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">tvm::meta_schedule::PyDatabaseNode</a>
</li>
@@ -264,6 +267,9 @@ $(function() {
<li>FGenerateMeasureCandidates
: <a class="el" href="classtvm_1_1meta__schedule_1_1PySearchStrategyNode.html#a87e2f696bcd7ab1c4066487f4cba7d29">tvm::meta_schedule::PySearchStrategyNode</a>
</li>
+<li>FGetAllTuningRecords
+: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>FGetTopK
: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">tvm::meta_schedule::PyDatabaseNode</a>
</li>
@@ -618,7 +624,7 @@ $(function() {
: <a class="el" href="classtvm_1_1auto__scheduler_1_1FuseStepNode.html#a19c1a7b47f59a4f004a2dd9f354835eb">tvm::auto_scheduler::FuseStepNode</a>
</li>
<li>FuseStep()
-: <a class="el" href="classtvm_1_1auto__scheduler_1_1FuseStep.html#a345e30fc54e9782faa9b8744c9ed5d14">tvm::auto_scheduler::FuseStep</a>
+: <a class="el" href="classtvm_1_1auto__scheduler_1_1FuseStep.html#a77c478295e170275d7d5da7345a03546">tvm::auto_scheduler::FuseStep</a>
</li>
<li>FVisitAttrs
: <a class="el" href="classtvm_1_1ReflectionVTable.html#a486eb682af89ac025c0db1f8f6045b95">tvm::ReflectionVTable</a>
diff --git a/docs/reference/api/doxygen/functions_func_a.html b/docs/reference/api/doxygen/functions_func_a.html
index ad547f6c4..a1d0fbefe 100644
--- a/docs/reference/api/doxygen/functions_func_a.html
+++ b/docs/reference/api/doxygen/functions_func_a.html
@@ -242,7 +242,7 @@ $(function() {
: <a class="el" href="classtvm_1_1meta__schedule_1_1ArgInfo.html#af2be498a4c11d470e2cd1f1474cc4839">tvm::meta_schedule::ArgInfo</a>
</li>
<li>Array()
-: <a class="el" href="classtvm_1_1runtime_1_1Array.html#a87edbe5dfbdd7deda742bd187ebee234">tvm::runtime::Array< T, typename ></a>
+: <a class="el" href="classtvm_1_1runtime_1_1Array.html#a7c03ae71aa89ec2591ae9ba7b3acc9d1">tvm::runtime::Array< T, typename ></a>
</li>
<li>ArrayAccessor()
: <a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor.html#aa66d3f34e83f90c133bc1df9b0c3acd2">tvm::runtime::metadata::ArrayAccessor< C, Ref ></a>
@@ -265,6 +265,9 @@ $(function() {
, <a class="el" href="classtvm_1_1runtime_1_1profiling_1_1ReportNode.html#a14a4f9e4ab99622474e423f7adbd26e3">tvm::runtime::profiling::ReportNode</a>
, <a class="el" href="classtvm_1_1tir_1_1TraceNode.html#a6d3d290467daace39806455b618340e1">tvm::tir::TraceNode</a>
</li>
+<li>AsMeasureCandidate()
+: <a class="el" href="classtvm_1_1meta__schedule_1_1TuningRecordNode.html#aa4f013b36ab008650dea4fb62d523c43">tvm::meta_schedule::TuningRecordNode</a>
+</li>
<li>AsObjectRef()
: <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#a289a65bf255e3d192c60d7b5a8dcf097">tvm::runtime::TVMPODValue_</a>
</li>
@@ -294,7 +297,7 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1ArrayNode.html#a410953f5ac23f6ca5caa257def8b08bd">tvm::runtime::ArrayNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1DenseMapNode.html#a6071908cdeb00617d3b28a70d05ac649">tvm::runtime::DenseMapNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1Map.html#a7fbfe0e01b0fa54e151bd481956dcfec">tvm::runtime::Map< K, V, typename, typename ></a>
-, <a class="el" href="classtvm_1_1runtime_1_1MapNode.html#a49edd4ddc34a4e0b097c34560b9b3b4e">tvm::runtime::MapNode</a>
+, <a class="el" href="classtvm_1_1runtime_1_1MapNode.html#a29503ec61af7a5bb9b030a00cfdff01a">tvm::runtime::MapNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1ShapeTuple.html#a07d50937020663f46ce9b1f31f066a7a">tvm::runtime::ShapeTuple</a>
, <a class="el" href="classtvm_1_1runtime_1_1SmallMapNode.html#a866679f23f724edc2d165f530f058b09">tvm::runtime::SmallMapNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1String.html#aaeda6a88310d41a22ce884fb1570b0d2">tvm::runtime::String</a>
@@ -306,7 +309,7 @@ $(function() {
: <a class="el" href="structtvm_1_1AttrError.html#a3285db0171872bc2fdde8243f6e801d9">tvm::AttrError</a>
</li>
<li>AttrInitEntry()
-: <a class="el" href="structtvm_1_1detail_1_1AttrInitEntry.html#ad68ac350b0d49e97caab8443cc8fb08b">tvm::detail::AttrInitEntry< T ></a>
+: <a class="el" href="structtvm_1_1detail_1_1AttrInitEntry.html#af07c4a3a8f4663ac03ae238ab7b9d791">tvm::detail::AttrInitEntry< T ></a>
</li>
<li>AttrInitVisitor()
: <a class="el" href="classtvm_1_1detail_1_1AttrInitVisitor.html#ac3c800c9249fee195db2a5fa473fe960">tvm::detail::AttrInitVisitor< FFind ></a>
diff --git a/docs/reference/api/doxygen/functions_func_g.html b/docs/reference/api/doxygen/functions_func_g.html
index 742e94835..94a1e472b 100644
--- a/docs/reference/api/doxygen/functions_func_g.html
+++ b/docs/reference/api/doxygen/functions_func_g.html
@@ -145,6 +145,10 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1vm_1_1MemoryManager.html#aeaa1e35590fd9bcbceea389d3dc1c3c3">tvm::runtime::vm::MemoryManager</a>
, <a class="el" href="classtvm_1_1runtime_1_1vm_1_1VirtualMachine.html#a50ed3e6162aa0c446d9c3b229eb7a984">tvm::runtime::vm::VirtualMachine</a>
</li>
+<li>GetAllTuningRecords()
+: <a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aa0b963a127d514ff78295b4f75c88872">tvm::meta_schedule::DatabaseNode</a>
+, <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>GetArrayNode()
: <a class="el" href="classtvm_1_1runtime_1_1Array.html#a50385ee3535af422c478d91166331a3c">tvm::runtime::Array< T, typename ></a>
</li>
@@ -156,8 +160,8 @@ $(function() {
, <a class="el" href="classtvm_1_1DictAttrs.html#a4bff303c0d4e87ed01ffe4cdb36b05d0">tvm::DictAttrs</a>
, <a class="el" href="classtvm_1_1IRModuleNode.html#a3fc3b5d49de0e20a5e7a28d5b462232a">tvm::IRModuleNode</a>
, <a class="el" href="classtvm_1_1ReflectionVTable.html#a800ed4d832ef6cb9f1cbf8d5ef01fc78">tvm::ReflectionVTable</a>
-, <a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html#a7f123ca7dfec3ad6bb0dfd2aecaf468f">tvm::relay::ExecutorNode</a>
-, <a class="el" href="classtvm_1_1relay_1_1RuntimeNode.html#a00b4e3bb7a649c7cb730382a8c374ead">tvm::relay::RuntimeNode</a>
+, <a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html#af376babb39ea146d407de2a009b5995b">tvm::relay::ExecutorNode</a>
+, <a class="el" href="classtvm_1_1relay_1_1RuntimeNode.html#a272b4a534f93f1aa7304bc20b8f124a1">tvm::relay::RuntimeNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#abc5161577ee6c41a6dfe269a9ab1db61">tvm::runtime::DeviceAPI</a>
, <a class="el" href="classtvm_1_1TargetNode.html#a008fae4839d63a3a7a9bc7e0f0e40480">tvm::TargetNode</a>
</li>
@@ -181,7 +185,7 @@ $(function() {
: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#ab47f456cb12d24b89fe4432d0304d506">tvm::tir::ScheduleNode</a>
</li>
<li>GetConfig()
-: <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#abc4e20b2148514b0e205095883c6268c">tvm::transform::PassContextNode</a>
+: <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#a34609e3ea0d3eb42c6a571536ed667a7">tvm::transform::PassContextNode</a>
</li>
<li>GetConstants()
: <a class="el" href="classtvm_1_1runtime_1_1vm_1_1Executable.html#af89ade803e9ef425bad26ff5888d033d">tvm::runtime::vm::Executable</a>
@@ -235,7 +239,7 @@ $(function() {
</li>
<li>GetFunction()
: <a class="el" href="classtvm_1_1runtime_1_1Module.html#a1233f7b896bb299ef07f9e41a4ffdc17">tvm::runtime::Module</a>
-, <a class="el" href="classtvm_1_1runtime_1_1ModuleNode.html#af16bc90e6265eb5492b028308dbb1a25">tvm::runtime::ModuleNode</a>
+, <a class="el" href="classtvm_1_1runtime_1_1ModuleNode.html#abd6d000714e0ed2b3b2f435ea5bd9a43">tvm::runtime::ModuleNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1vm_1_1Executable.html#af052de1610aae050d4363b6625265e86">tvm::runtime::vm::Executable</a>
, <a class="el" href="classtvm_1_1runtime_1_1vm_1_1VirtualMachine.html#a8d1e7cdc6412eae8dea9c2c08c7f48ec">tvm::runtime::vm::VirtualMachine</a>
</li>
@@ -318,7 +322,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeReporterNode.html#a06af835a761aaa10627a88ac4b712a15">tvm::TypeReporterNode</a>
</li>
<li>GetSRef()
-: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a08f7ed1ef1470fb1c9cfc272e14a1e32">tvm::tir::ScheduleNode</a>
+: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a34d50e4b429557302c5c6575bcc706d5">tvm::tir::ScheduleNode</a>
</li>
<li>GetTag()
: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a8b46d1eb3853555b6d3a85f2ef9c0868">tvm::runtime::vm::Instruction</a>
diff --git a/docs/reference/api/doxygen/functions_func_p.html b/docs/reference/api/doxygen/functions_func_p.html
index 05f251135..90d83b5e2 100644
--- a/docs/reference/api/doxygen/functions_func_p.html
+++ b/docs/reference/api/doxygen/functions_func_p.html
@@ -281,7 +281,7 @@ $(function() {
: <a class="el" href="classtvm_1_1meta__schedule_1_1CostModel.html#aa824ead03b1c61470daee67989ba4967">tvm::meta_schedule::CostModel</a>
</li>
<li>PyDatabase()
-: <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#a9c152a6d89c789adf13047d50d57aa49">tvm::meta_schedule::Database</a>
+: <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#ae81f559342e4628ea1bffce6db36e547">tvm::meta_schedule::Database</a>
</li>
<li>PyFeatureExtractor()
: <a class="el" href="classtvm_1_1meta__schedule_1_1FeatureExtractor.html#ac4b355e78ec150c5d067f78638f2da82">tvm::meta_schedule::FeatureExtractor</a>
diff --git a/docs/reference/api/doxygen/functions_func_s.html b/docs/reference/api/doxygen/functions_func_s.html
index 671cfbe44..8bead2b58 100644
--- a/docs/reference/api/doxygen/functions_func_s.html
+++ b/docs/reference/api/doxygen/functions_func_s.html
@@ -592,7 +592,7 @@ $(function() {
, <a class="el" href="classtvm_1_1tir_1_1SeqStmtNode.html#a0b17eae7cf993b7e3c3e5b50b4fa5982">tvm::tir::SeqStmtNode</a>
</li>
<li>SizeVar()
-: <a class="el" href="classtvm_1_1tir_1_1SizeVar.html#a0f8cb8a92feb96343939d223db90f7cd">tvm::tir::SizeVar</a>
+: <a class="el" href="classtvm_1_1tir_1_1SizeVar.html#ac470249315d9e395ad581d35dd5dcb05">tvm::tir::SizeVar</a>
</li>
<li>Slice()
: <a class="el" href="classtvm_1_1te_1_1Tensor_1_1Slice.html#ab314819e8bcca6421e9a4f33e48578c3">tvm::te::Tensor::Slice</a>
@@ -611,7 +611,7 @@ $(function() {
</li>
<li>Span()
: <a class="el" href="classtvm_1_1Span.html#a5216631b639e8c802263d87d3fe9e5f6">tvm::Span</a>
-, <a class="el" href="classtvm_1_1support_1_1Span.html#a3c22dd06856e7029e7107adf38eb72f5">tvm::support::Span< T, W ></a>
+, <a class="el" href="classtvm_1_1support_1_1Span.html#a77653730a2542edf93b7c4413a72f3ec">tvm::support::Span< T, W ></a>
</li>
<li>SpecializedCondition()
: <a class="el" href="classtvm_1_1te_1_1SpecializedCondition.html#a48d119ee1c6033929a5592cfc2592e60">tvm::te::SpecializedCondition</a>
@@ -706,7 +706,7 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#ac29b9295c432a87658392872c644864f">tvm::runtime::DeviceAPI</a>
</li>
<li>String()
-: <a class="el" href="classtvm_1_1runtime_1_1String.html#ac5d930b522e9fef9c07e51819d96d2f3">tvm::runtime::String</a>
+: <a class="el" href="classtvm_1_1runtime_1_1String.html#acf549b3c43142639879e0fc31ea5cd77">tvm::runtime::String</a>
</li>
<li>StringImm()
: <a class="el" href="classtvm_1_1tir_1_1StringImm.html#a0f2830290e055f677c5d5dea98aab726">tvm::tir::StringImm</a>
diff --git a/docs/reference/api/doxygen/functions_func_t.html b/docs/reference/api/doxygen/functions_func_t.html
index c45461fe7..f61a7d9be 100644
--- a/docs/reference/api/doxygen/functions_func_t.html
+++ b/docs/reference/api/doxygen/functions_func_t.html
@@ -1066,7 +1066,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeRelation.html#ac26b1897eab8197ed26606ab81b7403b">tvm::TypeRelation</a>
</li>
<li>TypeReporter()
-: <a class="el" href="classtvm_1_1TypeReporter.html#a8e7e05a07f9f7ad9bea91f27afac9051">tvm::TypeReporter</a>
+: <a class="el" href="classtvm_1_1TypeReporter.html#aa3dc38a3c84d324d0b3a9f358460a091">tvm::TypeReporter</a>
</li>
<li>TypeVar()
: <a class="el" href="classtvm_1_1TypeVar.html#adf5ef8e89d162735519b5d125c89e3e3">tvm::TypeVar</a>
diff --git a/docs/reference/api/doxygen/functions_func_v.html b/docs/reference/api/doxygen/functions_func_v.html
index d1ec4ed9f..626acc417 100644
--- a/docs/reference/api/doxygen/functions_func_v.html
+++ b/docs/reference/api/doxygen/functions_func_v.html
@@ -426,8 +426,8 @@ $(function() {
</li>
<li>VisitType_()
: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#ae03e50b74b8bd7551b55205976be592e">tvm::TypeFunctor< R(const Type &n, Args...)></a>
-, <a class="el" href="classtvm_1_1TypeMutator.html#ab270cb7a0d9af50362137c1d68d32276">tvm::TypeMutator</a>
-, <a class="el" href="classtvm_1_1TypeVisitor.html#ac8845fbf58c1a1f0ebc23c7ee403aaab">tvm::TypeVisitor</a>
+, <a class="el" href="classtvm_1_1TypeMutator.html#a9c2d7e1a52faac66f55896ecde3f2211">tvm::TypeMutator</a>
+, <a class="el" href="classtvm_1_1TypeVisitor.html#ae699be9a6ed94a635c315506e0c2a6d2">tvm::TypeVisitor</a>
</li>
<li>VisitTypeDefault_()
: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#a91553f9e04c39b3821a70ae4f7b0c597">tvm::TypeFunctor< R(const Type &n, Args...)></a>
diff --git a/docs/reference/api/doxygen/functions_g.html b/docs/reference/api/doxygen/functions_g.html
index 6dc00be40..4f246eb9c 100644
--- a/docs/reference/api/doxygen/functions_g.html
+++ b/docs/reference/api/doxygen/functions_g.html
@@ -151,6 +151,10 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1vm_1_1MemoryManager.html#aeaa1e35590fd9bcbceea389d3dc1c3c3">tvm::runtime::vm::MemoryManager</a>
, <a class="el" href="classtvm_1_1runtime_1_1vm_1_1VirtualMachine.html#a50ed3e6162aa0c446d9c3b229eb7a984">tvm::runtime::vm::VirtualMachine</a>
</li>
+<li>GetAllTuningRecords()
+: <a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html#aa0b963a127d514ff78295b4f75c88872">tvm::meta_schedule::DatabaseNode</a>
+, <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad07d7d9e78771eaa2e6e65f84e032401">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>GetArrayNode()
: <a class="el" href="classtvm_1_1runtime_1_1Array.html#a50385ee3535af422c478d91166331a3c">tvm::runtime::Array< T, typename ></a>
</li>
@@ -162,7 +166,7 @@ $(function() {
, <a class="el" href="classtvm_1_1DictAttrs.html#a4bff303c0d4e87ed01ffe4cdb36b05d0">tvm::DictAttrs</a>
, <a class="el" href="classtvm_1_1IRModuleNode.html#a3fc3b5d49de0e20a5e7a28d5b462232a">tvm::IRModuleNode</a>
, <a class="el" href="classtvm_1_1ReflectionVTable.html#a800ed4d832ef6cb9f1cbf8d5ef01fc78">tvm::ReflectionVTable</a>
-, <a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html#af376babb39ea146d407de2a009b5995b">tvm::relay::ExecutorNode</a>
+, <a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html#a7f123ca7dfec3ad6bb0dfd2aecaf468f">tvm::relay::ExecutorNode</a>
, <a class="el" href="classtvm_1_1relay_1_1RuntimeNode.html#a272b4a534f93f1aa7304bc20b8f124a1">tvm::relay::RuntimeNode</a>
, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#abc5161577ee6c41a6dfe269a9ab1db61">tvm::runtime::DeviceAPI</a>
, <a class="el" href="classtvm_1_1TargetNode.html#a008fae4839d63a3a7a9bc7e0f0e40480">tvm::TargetNode</a>
@@ -330,7 +334,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeReporterNode.html#a06af835a761aaa10627a88ac4b712a15">tvm::TypeReporterNode</a>
</li>
<li>GetSRef()
-: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a2a52c8522a4bfc7d42a189250a462ce8">tvm::tir::ScheduleNode</a>
+: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a08f7ed1ef1470fb1c9cfc272e14a1e32">tvm::tir::ScheduleNode</a>
</li>
<li>GetTag()
: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a8b46d1eb3853555b6d3a85f2ef9c0868">tvm::runtime::vm::Instruction</a>
diff --git a/docs/reference/api/doxygen/functions_m.html b/docs/reference/api/doxygen/functions_m.html
index cccff13aa..a7c2978ca 100644
--- a/docs/reference/api/doxygen/functions_m.html
+++ b/docs/reference/api/doxygen/functions_m.html
@@ -306,7 +306,7 @@ $(function() {
: <a class="el" href="classtvm_1_1DiagnosticContextNode.html#adea7e38a6e47cbab7fb5639f208aa536">tvm::DiagnosticContextNode</a>
</li>
<li>Module()
-: <a class="el" href="classtvm_1_1runtime_1_1Module.html#abd1380b3f813c2b6acefca3aaef425f4">tvm::runtime::Module</a>
+: <a class="el" href="classtvm_1_1runtime_1_1Module.html#abfbc619b3b3166d63ec52e399c24bed9">tvm::runtime::Module</a>
, <a class="el" href="classtvm_1_1runtime_1_1ModuleNode.html#a21f639900c480510650969df9c74d17d">tvm::runtime::ModuleNode</a>
</li>
<li>module_handle
diff --git a/docs/reference/api/doxygen/functions_p.html b/docs/reference/api/doxygen/functions_p.html
index ea9a08c84..af2f26db2 100644
--- a/docs/reference/api/doxygen/functions_p.html
+++ b/docs/reference/api/doxygen/functions_p.html
@@ -481,7 +481,7 @@ $(function() {
: <a class="el" href="classtvm_1_1meta__schedule_1_1CostModel.html#aa824ead03b1c61470daee67989ba4967">tvm::meta_schedule::CostModel</a>
</li>
<li>PyDatabase()
-: <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#a9c152a6d89c789adf13047d50d57aa49">tvm::meta_schedule::Database</a>
+: <a class="el" href="classtvm_1_1meta__schedule_1_1Database.html#ae81f559342e4628ea1bffce6db36e547">tvm::meta_schedule::Database</a>
</li>
<li>PyFeatureExtractor()
: <a class="el" href="classtvm_1_1meta__schedule_1_1FeatureExtractor.html#ac4b355e78ec150c5d067f78638f2da82">tvm::meta_schedule::FeatureExtractor</a>
diff --git a/docs/reference/api/doxygen/functions_t.html b/docs/reference/api/doxygen/functions_t.html
index d85ca7103..ae4acb9e9 100644
--- a/docs/reference/api/doxygen/functions_t.html
+++ b/docs/reference/api/doxygen/functions_t.html
@@ -1287,7 +1287,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypedEnvFunc_3_01R_07Args_8_8_8_08_4.html#a0d72a6fa7263821c14bcd37837998ed9">tvm::TypedEnvFunc< R(Args...)></a>
</li>
<li>TypedPackedFunc()
-: <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a36ca0d1876544463ee848766e70e5e96">tvm::runtime::TypedPackedFunc< R(Args...)></a>
+: <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a8941c80982a1b2a289440f3c79bb0ac8">tvm::runtime::TypedPackedFunc< R(Args...)></a>
</li>
<li>TypeIndex2Key()
: <a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">tvm::runtime::Object</a>
@@ -1310,7 +1310,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeRelation.html#ac26b1897eab8197ed26606ab81b7403b">tvm::TypeRelation</a>
</li>
<li>TypeReporter()
-: <a class="el" href="classtvm_1_1TypeReporter.html#a8e7e05a07f9f7ad9bea91f27afac9051">tvm::TypeReporter</a>
+: <a class="el" href="classtvm_1_1TypeReporter.html#aa3dc38a3c84d324d0b3a9f358460a091">tvm::TypeReporter</a>
</li>
<li>types
: <a class="el" href="classtvm_1_1TupleAffineTypeNode.html#a30c834b7e1cb64467e6587ac16ebb187">tvm::TupleAffineTypeNode</a>
diff --git a/docs/reference/api/doxygen/functions_type.html b/docs/reference/api/doxygen/functions_type.html
index d8c2f376a..b4e453512 100644
--- a/docs/reference/api/doxygen/functions_type.html
+++ b/docs/reference/api/doxygen/functions_type.html
@@ -159,6 +159,9 @@ $(function() {
<li>FGenerateMeasureCandidates
: <a class="el" href="classtvm_1_1meta__schedule_1_1PySearchStrategyNode.html#a87e2f696bcd7ab1c4066487f4cba7d29">tvm::meta_schedule::PySearchStrategyNode</a>
</li>
+<li>FGetAllTuningRecords
+: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a574d90736eda21019540d4a26c155b28">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>FGetTopK
: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#ad5e04e950cd2a63f439d95285b5674b6">tvm::meta_schedule::PyDatabaseNode</a>
</li>
diff --git a/docs/reference/api/doxygen/functions_v.html b/docs/reference/api/doxygen/functions_v.html
index 0672aa841..65276c35d 100644
--- a/docs/reference/api/doxygen/functions_v.html
+++ b/docs/reference/api/doxygen/functions_v.html
@@ -552,7 +552,7 @@ $(function() {
</li>
<li>VisitStmt_()
: <a class="el" href="classtvm_1_1tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6n_00_01Args_8_8_8_01args_08_4.html#ab10dd3ea7414d0c6c415857be5b5ad7b">tvm::tir::StmtFunctor< R(const Stmt &n, Args... args)></a>
-, <a class="el" href="classtvm_1_1tir_1_1StmtMutator.html#ab094e88d4bda5882756d136c15db6260">tvm::tir::StmtMutator</a>
+, <a class="el" href="classtvm_1_1tir_1_1StmtMutator.html#aaf5a2292da207073d637cc4d1a0704ce">tvm::tir::StmtMutator</a>
, <a class="el" href="classtvm_1_1tir_1_1StmtVisitor.html#ae842e15f24937f456d0e42aeb53965df">tvm::tir::StmtVisitor</a>
</li>
<li>VisitStmtDefault_()
@@ -568,8 +568,8 @@ $(function() {
</li>
<li>VisitType_()
: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#a40e3787a169f391bda4852aa7caf33cb">tvm::TypeFunctor< R(const Type &n, Args...)></a>
-, <a class="el" href="classtvm_1_1TypeMutator.html#a8171dc89a947d6224e83e86ce5d06d11">tvm::TypeMutator</a>
-, <a class="el" href="classtvm_1_1TypeVisitor.html#a11378b4db6f704c04a97bec1c8ea8261">tvm::TypeVisitor</a>
+, <a class="el" href="classtvm_1_1TypeMutator.html#a89bd7a76f5a736defc7f3b0dda664761">tvm::TypeMutator</a>
+, <a class="el" href="classtvm_1_1TypeVisitor.html#a2d6a319537d4d3dba04054f3ef8f32f9">tvm::TypeVisitor</a>
</li>
<li>VisitTypeDefault_()
: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#a91553f9e04c39b3821a70ae4f7b0c597">tvm::TypeFunctor< R(const Type &n, Args...)></a>
diff --git a/docs/reference/api/doxygen/functions_vars_f.html b/docs/reference/api/doxygen/functions_vars_f.html
index 79bd70079..56dd9b83f 100644
--- a/docs/reference/api/doxygen/functions_vars_f.html
+++ b/docs/reference/api/doxygen/functions_vars_f.html
@@ -111,6 +111,9 @@ $(function() {
<li>f_generate_measure_candidates
: <a class="el" href="classtvm_1_1meta__schedule_1_1PySearchStrategyNode.html#a5fdfb43b58d50fc34d8c515c9c9b7398">tvm::meta_schedule::PySearchStrategyNode</a>
</li>
+<li>f_get_all_tuning_records
+: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f">tvm::meta_schedule::PyDatabaseNode</a>
+</li>
<li>f_get_top_k
: <a class="el" href="classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed">tvm::meta_schedule::PyDatabaseNode</a>
</li>
diff --git a/docs/reference/api/doxygen/hierarchy.html b/docs/reference/api/doxygen/hierarchy.html
index e929e60f5..1423ddacb 100644
--- a/docs/reference/api/doxygen/hierarchy.html
+++ b/docs/reference/api/doxygen/hierarchy.html
@@ -1272,8 +1272,8 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_154_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1is__specialized_3_01Container_3_01Args_8_8_8_01_4_00_01Container_01_4.html" target="_self">tvm::detail::is_specialized< Container< Args... >, Container ></a></td><td class="desc"></td></tr>
<tr id="row_155_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm__workspace__t.html" target="_self">tvm_workspace_t</a></td><td class="desc"></td></tr>
<tr id="row_156_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structTVMAotExecutor.html" target="_self">TVMAotExecutor</a></td><td class="desc"></td></tr>
-<tr id="row_157_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structTVMArgs.html" target="_self">TVMArgs</a></td><td class="desc"></td></tr>
-<tr id="row_158_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TVMArgs.html" target="_self">tvm::runtime::TVMArgs</a></td><td class="desc">Arguments into TVM functions </td></tr>
+<tr id="row_157_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TVMArgs.html" target="_self">tvm::runtime::TVMArgs</a></td><td class="desc">Arguments into TVM functions </td></tr>
+<tr id="row_158_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structTVMArgs.html" target="_self">TVMArgs</a></td><td class="desc"></td></tr>
<tr id="row_159_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TVMArgsSetter.html" target="_self">tvm::runtime::TVMArgsSetter</a></td><td class="desc"></td></tr>
<tr id="row_160_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structTVMByteArray.html" target="_self">TVMByteArray</a></td><td class="desc">Byte array type used to pass in byte array When kTVMBytes is used as data type </td></tr>
<tr id="row_161_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structTVMFuncRegistry.html" target="_self">TVMFuncRegistry</a></td><td class="desc">A data structure that facilitates function lookup by C-string name </td></tr>
@@ -1300,61 +1300,62 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_179_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< te::Tensor >(const Attrs &attrs, const Array< te::Tensor > &inputs, const Type &out_type)></a></td><td class="desc"></td></tr>
<tr id="row_180_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< tir::Schedule >(const IRModule &)></a></td><td class="desc"></td></tr>
<tr id="row_181_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< tir::Schedule >(const tir::Schedule &, const tir::BlockRV &)></a></td><td class="desc"></td></tr>
-<tr id="row_182_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< TuningRecord >(const Workload &, int)></a></td><td class="desc"></td></tr>
-<tr id="row_183_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< tvm::runtime::NDArray >(const TuneContext &context, const Array< MeasureCandidate > &candidates)></a></td><td class="desc"></td></tr>
-<tr id="row_184_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool()></a></td><td class="desc"></td></tr>
-<tr id="row_185_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool(const IRModule &)></a></td><td class="desc"></td></tr>
-<tr id="row_186_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool(const tir::Schedule &)></a></td><td class="desc"></td></tr>
-<tr id="row_187_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< int()></a></td><td class="desc"></td></tr>
-<tr id="row_188_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< int64_t()></a></td><td class="desc"></td></tr>
-<tr id="row_189_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< ObjectRef(Array< ObjectRef > attrs)></a></td><td class="desc"></td></tr>
-<tr id="row_190_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< Array< MeasureCandidate > >()></a></td><td class="desc"></td></tr>
-<tr id="row_191_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< tir::PrimFunc >(const Array< te::Tensor, void > &)></a></td><td class="desc"></td></tr>
-<tr id="row_192_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< tir::Trace >(const tir::Trace &, support::LinearCongruentialEngine::TRandState rand_state)></a></td><td class="desc"></td></tr>
-<tr id="row_193_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html" target="_self">tvm::runtime::TypedPackedFunc< R(Args...)></a></td><td class="desc">A <a class="el" href="classtvm_1_1runtime_1_1PackedFunc.html" title="Packed function is a type-erased function. The arguments are passed by packed format. ">PackedF [...]
-<tr id="row_194_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< RunnerResult()></a></td><td class="desc"></td></tr>
-<tr id="row_195_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< String()></a></td><td class="desc"></td></tr>
-<tr id="row_196_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< String(const Array< ObjectRef > &inputs, const Array< ObjectRef > &attrs, const Optional< ObjectRef > &decision, const Array< String > &outputs)></a></td><td class="desc">< [...]
-<tr id="row_197_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< te::Schedule(const Attrs &attrs, const Array< te::Tensor > &outs, const Target &target)></a></td><td class="desc"></td></tr>
-<tr id="row_198_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void()></a></td><td class="desc"></td></tr>
-<tr id="row_199_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const Array< MeasureCandidate > &, const Array< RunnerResult > &)></a></td><td class="desc"></td></tr>
-<tr id="row_200_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const Array< tir::Schedule > &, const Optional< Database > &, const Optional< CostModel > &)></a></td><td class="desc"></td></tr>
-<tr id="row_201_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TaskScheduler &task_scheduler, int task_id, const Array< MeasureCandidate > &measure_candidates, const Array< BuilderResult > &builds, const Array< RunnerResult > &results)></a></t [...]
-<tr id="row_202_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &)></a></td><td class="desc"></td></tr>
-<tr id="row_203_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &, const Array< MeasureCandidate > &, const Array< RunnerResult > &)></a></td><td class="desc"></td></tr>
-<tr id="row_204_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &, const Array< MeasureCandidate > &, void *p_addr)></a></td><td class="desc"></td></tr>
-<tr id="row_205_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuningRecord &)></a></td><td class="desc"></td></tr>
-<tr id="row_206_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(int)></a></td><td class="desc"></td></tr>
-<tr id="row_207_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(size_t, void *)></a></td><td class="desc"></td></tr>
-<tr id="row_208_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(String)></a></td><td class="desc"></td></tr>
-<tr id="row_209_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(tvm::DiagnosticContext ctx)></a></td><td class="desc"></td></tr>
-<tr id="row_210_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Workload(const IRModule &)></a></td><td class="desc"></td></tr>
-<tr id="row_211_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor.html" target="_self">tvm::TypeFunctor< FType ></a></td><td class="desc"></td></tr>
-<tr id="row_212_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html" target="_self">tvm::TypeFunctor< R(const Type &n, Args...)></a></td><td class="desc"></td></tr>
-<tr id="row_213_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_213_" class="arrow" onclick="toggleFolder('213_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor.html" target="_self">tvm::TypeFunctor< Type(const Type &n)></a></td><td class="desc"></td></tr>
-<tr id="row_213_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeMutator.html" target="_self">tvm::TypeMutator</a></td><td class="desc"><a class="el" href="classtvm_1_1TypeMutator.html" title="TypeMutator that mutates expressions. ">TypeMutator</a> that mutates expressions </td></tr>
-<tr id="row_214_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_214_" class="arrow" onclick="toggleFolder('214_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor.html" target="_self">tvm::TypeFunctor< void(const Type &n)></a></td><td class="desc"></td></tr>
-<tr id="row_214_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeVisitor.html" target="_self">tvm::TypeVisitor</a></td><td class="desc">A type visitor that recursively visit types </td></tr>
-<tr id="row_215_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1TypeIndex.html" target="_self">tvm::runtime::TypeIndex</a></td><td class="desc">Namespace for the list of type index </td></tr>
-<tr id="row_216_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName.html" target="_self">tvm::detail::TypeName< T ></a></td><td class="desc">Helper struct to get the type name known to tvm </td></tr>
-<tr id="row_217_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01bool_01_4.html" target="_self">tvm::detail::TypeName< bool ></a></td><td class="desc"></td></tr>
-<tr id="row_218_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01DataType_01_4.html" target="_self">tvm::detail::TypeName< DataType ></a></td><td class="desc"></td></tr>
-<tr id="row_219_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01double_01_4.html" target="_self">tvm::detail::TypeName< double ></a></td><td class="desc"></td></tr>
-<tr id="row_220_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01int_01_4.html" target="_self">tvm::detail::TypeName< int ></a></td><td class="desc"></td></tr>
-<tr id="row_221_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01int64__t_01_4.html" target="_self">tvm::detail::TypeName< int64_t ></a></td><td class="desc"></td></tr>
-<tr id="row_222_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01uint64__t_01_4.html" target="_self">tvm::detail::TypeName< uint64_t ></a></td><td class="desc"></td></tr>
-<tr id="row_223_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01void_01_5_01_4.html" target="_self">tvm::detail::TypeName< void * ></a></td><td class="desc"></td></tr>
-<tr id="row_224_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1micro__rpc_1_1Unframer.html" target="_self">tvm::runtime::micro_rpc::Unframer</a></td><td class="desc"></td></tr>
-<tr id="row_225_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1v__info.html" target="_self">tvm::relay::v_info</a></td><td class="desc">A struct to keep info of traversed expr in ExpandDataflow function </td></tr>
-<tr id="row_226_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1Array_1_1ValueConverter.html" target="_self">tvm::runtime::Array< T, typename >::ValueConverter</a></td><td class="desc"></td></tr>
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-<tr id="row_228_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1VirtualDeviceCache.html" target="_self">tvm::VirtualDeviceCache</a></td><td class="desc">A cache of <code>VirtualDevices</code>. This can be used: </td></tr>
-<tr id="row_229_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFrame.html" target="_self">tvm::runtime::vm::VMFrame</a></td><td class="desc">A representation of a stack frame </td></tr>
-<tr id="row_230_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFunction.html" target="_self">tvm::runtime::vm::VMFunction</a></td><td class="desc">A representation of a Relay function in the VM </td></tr>
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+<tr id="row_182_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< TuningRecord >()></a></td><td class="desc"></td></tr>
+<tr id="row_183_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< TuningRecord >(const Workload &, int)></a></td><td class="desc"></td></tr>
+<tr id="row_184_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Array< tvm::runtime::NDArray >(const TuneContext &context, const Array< MeasureCandidate > &candidates)></a></td><td class="desc"></td></tr>
+<tr id="row_185_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool()></a></td><td class="desc"></td></tr>
+<tr id="row_186_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool(const IRModule &)></a></td><td class="desc"></td></tr>
+<tr id="row_187_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< bool(const tir::Schedule &)></a></td><td class="desc"></td></tr>
+<tr id="row_188_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< int()></a></td><td class="desc"></td></tr>
+<tr id="row_189_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< int64_t()></a></td><td class="desc"></td></tr>
+<tr id="row_190_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< ObjectRef(Array< ObjectRef > attrs)></a></td><td class="desc"></td></tr>
+<tr id="row_191_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< Array< MeasureCandidate > >()></a></td><td class="desc"></td></tr>
+<tr id="row_192_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< tir::PrimFunc >(const Array< te::Tensor, void > &)></a></td><td class="desc"></td></tr>
+<tr id="row_193_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Optional< tir::Trace >(const tir::Trace &, support::LinearCongruentialEngine::TRandState rand_state)></a></td><td class="desc"></td></tr>
+<tr id="row_194_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html" target="_self">tvm::runtime::TypedPackedFunc< R(Args...)></a></td><td class="desc">A <a class="el" href="classtvm_1_1runtime_1_1PackedFunc.html" title="Packed function is a type-erased function. The arguments are passed by packed form [...]
+<tr id="row_195_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< RunnerResult()></a></td><td class="desc"></td></tr>
+<tr id="row_196_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< String()></a></td><td class="desc"></td></tr>
+<tr id="row_197_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< String(const Array< ObjectRef > &inputs, const Array< ObjectRef > &attrs, const Optional< ObjectRef > &decision, const Array< String > &outputs)></a></td><td class="desc"></td></tr>
+<tr id="row_198_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< te::Schedule(const Attrs &attrs, const Array< te::Tensor > &outs, const Target &target)></a></td><td class="desc"></td></tr>
+<tr id="row_199_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void()></a></td><td class="desc"></td></tr>
+<tr id="row_200_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const Array< MeasureCandidate > &, const Array< RunnerResult > &)></a></td><td class="desc"></td></tr>
+<tr id="row_201_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const Array< tir::Schedule > &, const Optional< Database > &, const Optional< CostModel > &)></a></td><td class="desc"></td></tr>
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+<tr id="row_203_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &)></a></td><td class="desc"></td></tr>
+<tr id="row_204_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &, const Array< MeasureCandidate > &, const Array< RunnerResult > &)></a></td><td class="desc"></td></tr>
+<tr id="row_205_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(const TuneContext &, const Array< MeasureCandidate > &, void *p_addr)></a></td><td class="desc"></td></tr>
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+<tr id="row_207_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(int)></a></td><td class="desc"></td></tr>
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+<tr id="row_209_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(String)></a></td><td class="desc"></td></tr>
+<tr id="row_210_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< void(tvm::DiagnosticContext ctx)></a></td><td class="desc"></td></tr>
+<tr id="row_211_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc.html" target="_self">tvm::runtime::TypedPackedFunc< Workload(const IRModule &)></a></td><td class="desc"></td></tr>
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+<tr id="row_213_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html" target="_self">tvm::TypeFunctor< R(const Type &n, Args...)></a></td><td class="desc"></td></tr>
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+<tr id="row_214_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeMutator.html" target="_self">tvm::TypeMutator</a></td><td class="desc"><a class="el" href="classtvm_1_1TypeMutator.html" title="TypeMutator that mutates expressions. ">TypeMutator</a> that mutates expressions </td></tr>
+<tr id="row_215_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_215_" class="arrow" onclick="toggleFolder('215_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1TypeFunctor.html" target="_self">tvm::TypeFunctor< void(const Type &n)></a></td><td class="desc"></td></tr>
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+<tr id="row_218_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01bool_01_4.html" target="_self">tvm::detail::TypeName< bool ></a></td><td class="desc"></td></tr>
+<tr id="row_219_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01DataType_01_4.html" target="_self">tvm::detail::TypeName< DataType ></a></td><td class="desc"></td></tr>
+<tr id="row_220_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01double_01_4.html" target="_self">tvm::detail::TypeName< double ></a></td><td class="desc"></td></tr>
+<tr id="row_221_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01int_01_4.html" target="_self">tvm::detail::TypeName< int ></a></td><td class="desc"></td></tr>
+<tr id="row_222_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01int64__t_01_4.html" target="_self">tvm::detail::TypeName< int64_t ></a></td><td class="desc"></td></tr>
+<tr id="row_223_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01uint64__t_01_4.html" target="_self">tvm::detail::TypeName< uint64_t ></a></td><td class="desc"></td></tr>
+<tr id="row_224_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1TypeName_3_01void_01_5_01_4.html" target="_self">tvm::detail::TypeName< void * ></a></td><td class="desc"></td></tr>
+<tr id="row_225_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1micro__rpc_1_1Unframer.html" target="_self">tvm::runtime::micro_rpc::Unframer</a></td><td class="desc"></td></tr>
+<tr id="row_226_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1v__info.html" target="_self">tvm::relay::v_info</a></td><td class="desc">A struct to keep info of traversed expr in ExpandDataflow function </td></tr>
+<tr id="row_227_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1Array_1_1ValueConverter.html" target="_self">tvm::runtime::Array< T, typename >::ValueConverter</a></td><td class="desc"></td></tr>
+<tr id="row_228_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1detail_1_1ValueTypeInfoMaker.html" target="_self">tvm::detail::ValueTypeInfoMaker< ValueType, IsArray, IsMap ></a></td><td class="desc"></td></tr>
+<tr id="row_229_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1VirtualDeviceCache.html" target="_self">tvm::VirtualDeviceCache</a></td><td class="desc">A cache of <code>VirtualDevices</code>. This can be used: </td></tr>
+<tr id="row_230_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFrame.html" target="_self">tvm::runtime::vm::VMFrame</a></td><td class="desc">A representation of a stack frame </td></tr>
+<tr id="row_231_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFunction.html" target="_self">tvm::runtime::vm::VMFunction</a></td><td class="desc">A representation of a Relay function in the VM </td></tr>
+<tr id="row_232_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1With.html" target="_self">tvm::With< ContextType ></a></td><td class="desc">RAII wrapper function to enter and exit a context object similar to python's with syntax </td></tr>
+<tr id="row_233_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1meta__schedule_1_1WorkloadEqual.html" target="_self">tvm::meta_schedule::WorkloadEqual</a></td><td class="desc">The equality check for <a class="el" href="classtvm_1_1meta__schedule_1_1Workload.html" title="Managed reference to WorkloadNode. ">Workload</a> </td></tr>
+<tr id="row_234_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1meta__schedule_1_1WorkloadHash.html" target="_self">tvm::meta_schedule::WorkloadHash</a></td><td class="desc">The hash method for <a class="el" href="classtvm_1_1meta__schedule_1_1Workload.html" title="Managed reference to WorkloadNode. ">Workload</a> </td></tr>
+<tr id="row_235_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1runtime_1_1micro__rpc_1_1WriteStream.html" target="_self">tvm::runtime::micro_rpc::WriteStream</a></td><td class="desc"></td></tr>
</table>
</div><!-- directory -->
</div><!-- contents -->
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+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_173.svg" width="211" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_174.svg" width="210" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_175.svg" width="272" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_175.svg" width="304" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_176.svg" width="192" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_176.svg" width="272" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_177.svg" width="214" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_177.svg" width="192" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_178.svg" width="194" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_178.svg" width="214" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_179.svg" width="224" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_179.svg" width="194" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_180.svg" width="208" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_180.svg" width="224" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_181.svg" width="215" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_181.svg" width="208" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
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-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_182.svg" width="230" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_182.svg" width="215" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_183.svg" width="163" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_183.svg" width="230" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_184.svg" width="160" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_184.svg" width="163" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_185.svg" width="168" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_185.svg" width="160" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_186.svg" width="247" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_186.svg" width="168" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_187.svg" width="156" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_187.svg" width="247" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_188.svg" width="356" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_188.svg" width="156" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_189.svg" width="194" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_189.svg" width="356" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_190.svg" width="187" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_190.svg" width="194" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_191.svg" width="170" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_191.svg" width="187" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_192.svg" width="162" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_192.svg" width="170" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_193.svg" width="150" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_193.svg" width="162" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_194.svg" width="188" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_194.svg" width="150" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_195.svg" width="166" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_195.svg" width="188" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_196.svg" width="186" height="67"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_196.svg" width="166" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_197.svg" width="187" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_197.svg" width="186" height="67"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_198.svg" width="162" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_198.svg" width="187" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_199.svg" width="152" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_199.svg" width="162" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_200.svg" width="167" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_200.svg" width="152" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_201.svg" width="203" height="67"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_201.svg" width="167" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_202.svg" width="683" height="118"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_202.svg" width="203" height="67"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_203.svg" width="636" height="118"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_203.svg" width="683" height="118"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_204.svg" width="162" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_204.svg" width="636" height="118"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_205.svg" width="204" height="96"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_205.svg" width="162" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_206.svg" width="170" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_206.svg" width="204" height="96"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_207.svg" width="211" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_207.svg" width="170" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_208.svg" width="194" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_208.svg" width="211" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_209.svg" width="374" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_209.svg" width="194" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_210.svg" width="363" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_210.svg" width="374" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_211.svg" width="195" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_211.svg" width="363" height="52"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_212.svg" width="208" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_212.svg" width="195" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_213.svg" width="148" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_213.svg" width="208" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_214.svg" width="140" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_214.svg" width="148" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_215.svg" width="90" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_215.svg" width="140" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_216.svg" width="126" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_216.svg" width="90" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_217.svg" width="143" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_217.svg" width="126" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_218.svg" width="220" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_218.svg" width="143" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_219.svg" width="122" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_219.svg" width="220" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_220.svg" width="108" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_220.svg" width="122" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_221.svg" width="195" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_221.svg" width="108" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_222.svg" width="120" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_222.svg" width="195" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_223.svg" width="136" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_223.svg" width="120" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_224.svg" width="172" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_224.svg" width="136" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_225.svg" width="128" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_225.svg" width="172" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
-<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_226.svg" width="98" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_226.svg" width="128" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
+</td></tr>
+<tr><td><iframe scrolling="no" frameborder="0" src="inherit_graph_227.svg" width="98" height="38"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</td></tr>
</table>
</div><!-- contents -->
diff --git a/docs/reference/api/doxygen/search/all_11.js b/docs/reference/api/doxygen/search/all_11.js
index 911351783..e91c994e2 100644
--- a/docs/reference/api/doxygen/search/all_11.js
+++ b/docs/reference/api/doxygen/search/all_11.js
@@ -227,7 +227,7 @@ var searchData=
['pybuildernode',['PyBuilderNode',['../classtvm_1_1meta__schedule_1_1PyBuilderNode.html',1,'tvm::meta_schedule']]],
['pycostmodel',['PyCostModel',['../classtvm_1_1meta__schedule_1_1CostModel.html#aa824ead03b1c61470daee67989ba4967',1,'tvm::meta_schedule::CostModel']]],
['pycostmodelnode',['PyCostModelNode',['../classtvm_1_1meta__schedule_1_1PyCostModelNode.html',1,'tvm::meta_schedule']]],
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['fhasworkload',['FHasWorkload',['../classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#afb177ebca29227e94c3b3036b4908bad',1,'tvm::meta_schedule::PyDatabaseNode']]],
['fidentity',['FIdentity',['../namespacetvm_1_1topi.html#a7dd84c370a3377aec67ce83f94605df9',1,'tvm::topi']]],
diff --git a/docs/reference/api/doxygen/search/variables_6.js b/docs/reference/api/doxygen/search/variables_6.js
index 63a659c55..33c5cd432 100644
--- a/docs/reference/api/doxygen/search/variables_6.js
+++ b/docs/reference/api/doxygen/search/variables_6.js
@@ -14,6 +14,7 @@ var searchData=
['f_5fextract_5ffrom',['f_extract_from',['../classtvm_1_1meta__schedule_1_1PyFeatureExtractorNode.html#ab994b701cd02fef4ebb9fecca29f23be',1,'tvm::meta_schedule::PyFeatureExtractorNode']]],
['f_5fgenerate_5fdesign_5fspace',['f_generate_design_space',['../classtvm_1_1meta__schedule_1_1PySpaceGeneratorNode.html#a941c64f01b6bb0b6fb87c2619af9d1e2',1,'tvm::meta_schedule::PySpaceGeneratorNode']]],
['f_5fgenerate_5fmeasure_5fcandidates',['f_generate_measure_candidates',['../classtvm_1_1meta__schedule_1_1PySearchStrategyNode.html#a5fdfb43b58d50fc34d8c515c9c9b7398',1,'tvm::meta_schedule::PySearchStrategyNode']]],
+ ['f_5fget_5fall_5ftuning_5frecords',['f_get_all_tuning_records',['../classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#aafdd0874be052072521b2aa8a6c56d5f',1,'tvm::meta_schedule::PyDatabaseNode']]],
['f_5fget_5ftop_5fk',['f_get_top_k',['../classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#a52fb1116090619e95fb6b28352308eed',1,'tvm::meta_schedule::PyDatabaseNode']]],
['f_5fhas_5fworkload',['f_has_workload',['../classtvm_1_1meta__schedule_1_1PyDatabaseNode.html#add146bf1e2006f72ed1534b2004bcb06',1,'tvm::meta_schedule::PyDatabaseNode']]],
['f_5finitialize_5ftask',['f_initialize_task',['../classtvm_1_1meta__schedule_1_1PyTaskSchedulerNode.html#a15dcbf2ff4c0fc6e57cf15ef02783c75',1,'tvm::meta_schedule::PyTaskSchedulerNode']]],
diff --git a/docs/reference/api/python/auto_scheduler.html b/docs/reference/api/python/auto_scheduler.html
index bf8ae26f3..ae612f6a8 100644
--- a/docs/reference/api/python/auto_scheduler.html
+++ b/docs/reference/api/python/auto_scheduler.html
@@ -1718,7 +1718,7 @@ Can be the a function or the function name.</p></li>
<dl class="py function">
<dt class="sig sig-object py" id="tvm.auto_scheduler.auto_schedule">
-<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
+<span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">auto_schedule</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">search_policy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em clas [...]
<dd><p>THIS API IS DEPRECATED.</p>
<p>Run auto scheduling search for a task.</p>
<dl class="field-list simple">
@@ -1755,7 +1755,7 @@ the initial naive schedule (state).</p>
<dl class="py class">
<dt class="sig sig-object py" id="tvm.auto_scheduler.SketchPolicy">
-<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
+<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">tvm.auto_scheduler.</span></span><span class="sig-name descname"><span class="pre">SketchPolicy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">program_cost_model</span></span><span class="o"><span class="pre">=</span></span><span class="defau [...]
<dd><p>The search policy that searches in a hierarchical search space defined by sketches.
The policy randomly samples programs from the space defined by sketches and use evolutionary
search to fine-tune them.</p>
diff --git a/docs/reference/api/typedoc/classes/bytestreamreader.html b/docs/reference/api/typedoc/classes/bytestreamreader.html
index 0dd6fd64c..8f9a0784d 100644
--- a/docs/reference/api/typedoc/classes/bytestreamreader.html
+++ b/docs/reference/api/typedoc/classes/bytestreamreader.html
@@ -119,7 +119,7 @@
<li class="tsd-description">
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/dffc3108b/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/0fdc0eab5/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
</ul>
</aside>
<h4 class="tsd-parameters-title">Parameters</h4>
@@ -141,7 +141,7 @@
<div class="tsd-signature tsd-kind-icon">bytes<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Uint8Array</span></div>
<aside class="tsd-sources">
<ul>
- <li>Defined in <a href="https://github.com/apache/tvm/blob/dffc3108b/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
+ <li>Defined in <a href="https://github.com/apache/tvm/blob/0fdc0eab5/web/src/rpc_server.ts#L43">rpc_server.ts:43</a></li>
</ul>
</aside>
</section>
@@ -151,7 +151,7 @@
<div class="tsd-signature tsd-kind-icon">offset<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> = 0</span></div>
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