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Posted to commits@tvm.apache.org by tq...@apache.org on 2022/04/05 20:43:04 UTC
[tvm-site] branch asf-site updated: deploying docs (apache/tvm@5ec061f9766d40c9ef27662b48485b80075142a3)
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 3861c6560 deploying docs (apache/tvm@5ec061f9766d40c9ef27662b48485b80075142a3)
3861c6560 is described below
commit 3861c6560548a3756d35bd02d4ab1d19e39cb28d
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Tue Apr 5 20:42:58 2022 +0000
deploying docs (apache/tvm@5ec061f9766d40c9ef27662b48485b80075142a3)
---
.../how_to/compile_models/from_mxnet.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 | 20 +-
.../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 | 18 +-
.../extend_tvm/bring_your_own_datatypes.rst.txt | 2 +-
.../how_to/extend_tvm/sg_execution_times.rst.txt | 10 +-
.../how_to/extend_tvm/use_pass_instrument.rst.txt | 16 +-
.../optimize_operators/opt_conv_cuda.rst.txt | 2 +-
.../optimize_operators/opt_conv_tensorcore.rst.txt | 2 +-
.../how_to/optimize_operators/opt_gemm.rst.txt | 16 +-
.../optimize_operators/sg_execution_times.rst.txt | 8 +-
.../sg_execution_times.rst.txt | 16 +-
.../tune_conv2d_layer_cuda.rst.txt | 352 +-
.../tune_network_cuda.rst.txt | 2 +-
.../tune_network_x86.rst.txt | 4 +-
.../tune_sparse_x86.rst.txt | 82 +-
.../tune_with_autotvm/sg_execution_times.rst.txt | 12 +-
.../tune_with_autotvm/tune_conv2d_cuda.rst.txt | 34 +-
.../work_with_microtvm/micro_autotune.rst.txt | 16 +-
.../work_with_microtvm/sg_execution_times.rst.txt | 12 +-
.../work_with_relay/sg_execution_times.rst.txt | 8 +-
.../work_with_schedules/sg_execution_times.rst.txt | 18 +-
.../how_to/work_with_schedules/tensorize.rst.txt | 4 +-
.../tutorials/autotvm/sg_execution_times.rst.txt | 6 +-
.../frontend/deploy_classification.rst.txt | 2 +-
.../tutorials/frontend/deploy_detection.rst.txt | 2 +-
.../tutorials/frontend/sg_execution_times.rst.txt | 6 +-
.../tutorials/optimize/sg_execution_times.rst.txt | 6 +-
.../topic/vta/tutorials/sg_execution_times.rst.txt | 6 +-
.../tutorial/auto_scheduler_matmul_x86.rst.txt | 9 +-
docs/_sources/tutorial/autotvm_relay_x86.rst.txt | 55 +-
.../tutorial/cross_compilation_and_rpc.rst.txt | 2 +-
docs/_sources/tutorial/intro_topi.rst.txt | 2 +-
docs/_sources/tutorial/sg_execution_times.rst.txt | 26 +-
.../tutorial/tensor_expr_get_started.rst.txt | 47 +-
docs/commit_hash | 2 +-
docs/how_to/compile_models/from_mxnet.html | 2 +-
docs/how_to/compile_models/from_paddle.html | 2 +-
docs/how_to/compile_models/from_pytorch.html | 50 +-
docs/how_to/compile_models/from_tensorflow.html | 2 +-
docs/how_to/compile_models/sg_execution_times.html | 20 +-
.../deploy_models/deploy_model_on_android.html | 2 +-
.../deploy_object_detection_pytorch.html | 19 +-
docs/how_to/deploy_models/deploy_prequantized.html | 11 +-
.../deploy_models/deploy_prequantized_tflite.html | 4 +-
docs/how_to/deploy_models/deploy_quantized.html | 2 +-
docs/how_to/deploy_models/deploy_ssd_gluoncv.html | 38 +-
docs/how_to/deploy_models/sg_execution_times.html | 18 +-
.../extend_tvm/bring_your_own_datatypes.html | 2 +-
docs/how_to/extend_tvm/sg_execution_times.html | 10 +-
docs/how_to/extend_tvm/use_pass_instrument.html | 16 +-
docs/how_to/optimize_operators/opt_conv_cuda.html | 2 +-
.../optimize_operators/opt_conv_tensorcore.html | 2 +-
docs/how_to/optimize_operators/opt_gemm.html | 16 +-
.../optimize_operators/sg_execution_times.html | 8 +-
.../sg_execution_times.html | 14 +-
.../tune_conv2d_layer_cuda.html | 352 +-
.../tune_with_autoscheduler/tune_network_cuda.html | 2 +-
.../tune_with_autoscheduler/tune_network_x86.html | 4 +-
.../tune_with_autoscheduler/tune_sparse_x86.html | 82 +-
.../tune_with_autotvm/sg_execution_times.html | 12 +-
.../how_to/tune_with_autotvm/tune_conv2d_cuda.html | 34 +-
docs/how_to/work_with_microtvm/micro_autotune.html | 16 +-
.../work_with_microtvm/sg_execution_times.html | 12 +-
.../how_to/work_with_relay/sg_execution_times.html | 8 +-
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docs/how_to/work_with_schedules/tensorize.html | 4 +-
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.../tutorials/frontend/deploy_classification.html | 2 +-
.../vta/tutorials/frontend/deploy_detection.html | 2 +-
.../vta/tutorials/frontend/sg_execution_times.html | 6 +-
.../vta/tutorials/optimize/sg_execution_times.html | 6 +-
docs/topic/vta/tutorials/sg_execution_times.html | 6 +-
docs/tutorial/auto_scheduler_matmul_x86.html | 5 +-
docs/tutorial/autotvm_relay_x86.html | 163 +-
docs/tutorial/cross_compilation_and_rpc.html | 2 +-
docs/tutorial/intro_topi.html | 2 +-
docs/tutorial/sg_execution_times.html | 26 +-
docs/tutorial/tensor_expr_get_started.html | 43 +-
169 files changed, 6493 insertions(+), 5220 deletions(-)
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 a9f8f1d77..e38d86319 100644
--- a/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_mxnet.rst.txt
@@ -98,7 +98,7 @@ In this section, we download a pretrained imagenet model and classify an image.
.. code-block:: none
- Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip44141c3a-0e11-4b6e-a8ba-8e947f92cdd1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+ Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipe32d3e85-a3e2-4077-b0f3-55553b5b0ee2 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_paddle.rst.txt b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
index db6cb6b24..c87aea09f 100644
--- a/docs/_sources/how_to/compile_models/from_paddle.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_paddle.rst.txt
@@ -201,7 +201,7 @@ Look up prediction top 1 index in 1000 class synset.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 4.093 seconds)
+ **Total running time of the script:** ( 1 minutes 5.575 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 bef2492b4..4bb6f77e2 100644
--- a/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_pytorch.rst.txt
@@ -79,7 +79,7 @@ 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
-
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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 c3a675a9a..39b61dd24 100644
--- a/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
+++ b/docs/_sources/how_to/compile_models/from_tensorflow.rst.txt
@@ -372,7 +372,7 @@ Run the corresponding model on tensorflow
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 1.045 seconds)
+ **Total running time of the script:** ( 1 minutes 0.955 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 ddff25b86..3fbfd4986 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
@@ -5,14 +5,14 @@
Computation times
=================
-**04:44.641** total execution time for **how_to_compile_models** files:
+**04:53.594** total execution time for **how_to_compile_models** files:
-- **01:04.093**: :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)
-- **01:01.045**: :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``)
-- **00:55.752**: :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)
-- **00:25.368**: :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)
-- **00:22.179**: :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)
-- **00:20.580**: :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)
-- **00:19.293**: :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)
-- **00:13.632**: :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)
-- **00:02.699**: :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)
+- **01:05.575**: :ref:`sphx_glr_how_to_compile_models_from_paddle.py` (``from_paddle.py``)
+- **01:00.955**: :ref:`sphx_glr_how_to_compile_models_from_tensorflow.py` (``from_tensorflow.py``)
+- **00:57.042**: :ref:`sphx_glr_how_to_compile_models_from_darknet.py` (``from_darknet.py``)
+- **00:26.250**: :ref:`sphx_glr_how_to_compile_models_from_tflite.py` (``from_tflite.py``)
+- **00:24.046**: :ref:`sphx_glr_how_to_compile_models_from_pytorch.py` (``from_pytorch.py``)
+- **00:21.962**: :ref:`sphx_glr_how_to_compile_models_from_mxnet.py` (``from_mxnet.py``)
+- **00:21.277**: :ref:`sphx_glr_how_to_compile_models_from_coreml.py` (``from_coreml.py``)
+- **00:13.855**: :ref:`sphx_glr_how_to_compile_models_from_keras.py` (``from_keras.py``)
+- **00:02.632**: :ref:`sphx_glr_how_to_compile_models_from_onnx.py` (``from_onnx.py``)
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 0d8f82a4a..a91fcd31f 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
@@ -393,7 +393,7 @@ Execute on TVM
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.0534 16.0881 16.3155 15.7336 0.1698
+ 15.7893 15.7791 15.9486 15.6496 0.1033
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 d18eaab93..c0f066f46 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
@@ -108,7 +108,7 @@ 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
-
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+
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/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').
@@ -253,7 +253,7 @@ Get boxes with score larger than 0.9
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 3 minutes 2.538 seconds)
+ **Total running time of the script:** ( 3 minutes 0.672 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 bdf8ca31e..bf111cf6d 100644
--- a/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_prequantized.rst.txt
@@ -187,7 +187,7 @@ 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
-
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55%|#####5 | 7.46M/13.6M [00:00<00:00, 36.7MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 56.4MB/s]
+
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45%|####5 | 6.14M/13.6M [00:00<00:00, 29.3MB/s]
73%|#######3 | 9.95M/13.6M [00:00<00:00, 33.9MB/s]
100%|##########| 13.6M/13.6M [00:00<00:00, 38.1MB/s]
@@ -344,7 +344,7 @@ 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)
- 90.1482 90.0487 90.9326 89.9494 0.2301
+ 90.3071 90.1194 98.5680 89.9626 1.0693
@@ -384,7 +384,7 @@ TODO
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 4.459 seconds)
+ **Total running time of the script:** ( 1 minutes 2.677 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 be8951dd0..dfaf2b77d 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
@@ -351,7 +351,7 @@ 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)
- 119.0673 118.7645 140.0764 117.7407 2.2965
+ 119.5094 119.4100 124.7076 118.6000 0.6309
@@ -385,7 +385,7 @@ 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 52.051 seconds)
+ **Total running time of the script:** ( 1 minutes 57.817 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 b848b1068..f9c4d258c 100644
--- a/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
+++ b/docs/_sources/how_to/deploy_models/deploy_quantized.rst.txt
@@ -221,7 +221,7 @@ We create a Relay VM to build and execute the model.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 13.515 seconds)
+ **Total running time of the script:** ( 1 minutes 17.380 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 6860986bb..a568dae4e 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
@@ -137,7 +137,7 @@ 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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@@ -202,7 +202,7 @@ Display result
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 2 minutes 20.620 seconds)
+ **Total running time of the script:** ( 2 minutes 21.079 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 47c6af853..049478c2a 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
@@ -5,13 +5,13 @@
Computation times
=================
-**10:21.476** total execution time for **how_to_deploy_models** files:
+**10:28.194** total execution time for **how_to_deploy_models** files:
-- **03:02.538**: :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``)
-- **02:20.620**: :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``)
-- **01:52.051**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)
-- **01:13.515**: :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)
-- **01:04.459**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)
-- **00:26.989**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)
-- **00:21.108**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)
-- **00:00.196**: :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)
+- **03:00.672**: :ref:`sphx_glr_how_to_deploy_models_deploy_object_detection_pytorch.py` (``deploy_object_detection_pytorch.py``)
+- **02:21.079**: :ref:`sphx_glr_how_to_deploy_models_deploy_ssd_gluoncv.py` (``deploy_ssd_gluoncv.py``)
+- **01:57.817**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized_tflite.py` (``deploy_prequantized_tflite.py``)
+- **01:17.380**: :ref:`sphx_glr_how_to_deploy_models_deploy_quantized.py` (``deploy_quantized.py``)
+- **01:02.677**: :ref:`sphx_glr_how_to_deploy_models_deploy_prequantized.py` (``deploy_prequantized.py``)
+- **00:26.727**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_android.py` (``deploy_model_on_android.py``)
+- **00:21.656**: :ref:`sphx_glr_how_to_deploy_models_deploy_model_on_rasp.py` (``deploy_model_on_rasp.py``)
+- **00:00.186**: :ref:`sphx_glr_how_to_deploy_models_deploy_sparse.py` (``deploy_sparse.py``)
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 0db3f9aa1..35d6e719a 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
@@ -423,7 +423,7 @@ 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.zip3b99be30-aa86-4492-8b02-d4c729a8b20c from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/mobilenet0.25-9f83e440.zip...
+ Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip1de20b6f-9555-4ec4-a42f-30ffd53050a2 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 91d7981cf..619c3a127 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
@@ -5,9 +5,9 @@
Computation times
=================
-**00:37.955** total execution time for **how_to_extend_tvm** files:
+**00:37.730** total execution time for **how_to_extend_tvm** files:
-- **00:34.324**: :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``)
-- **00:02.236**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)
-- **00:01.198**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)
-- **00:00.197**: :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``)
+- **00:34.250**: :ref:`sphx_glr_how_to_extend_tvm_bring_your_own_datatypes.py` (``bring_your_own_datatypes.py``)
+- **00:02.224**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_instrument.py` (``use_pass_instrument.py``)
+- **00:01.054**: :ref:`sphx_glr_how_to_extend_tvm_use_pass_infra.py` (``use_pass_infra.py``)
+- **00:00.202**: :ref:`sphx_glr_how_to_extend_tvm_low_level_custom_pass.py` (``low_level_custom_pass.py``)
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 20acd93b0..46729ab7c 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
@@ -199,10 +199,10 @@ profile the execution time of each passes.
.. code-block:: none
Printing results of timing profile...
- InferType: 6891us [6891us] (48.12%; 48.12%)
- FoldScaleAxis: 7429us [3us] (51.88%; 51.88%)
- FoldConstant: 7427us [1539us] (51.86%; 99.96%)
- InferType: 5888us [5888us] (41.12%; 79.28%)
+ InferType: 5935us [5935us] (45.39%; 45.39%)
+ FoldScaleAxis: 7141us [2us] (54.61%; 54.61%)
+ FoldConstant: 7139us [1461us] (54.60%; 99.97%)
+ InferType: 5678us [5678us] (43.42%; 79.53%)
@@ -239,10 +239,10 @@ Refer to following sections and :py:func:`tvm.instrument.pass_instrument` for th
.. code-block:: none
Printing results of timing profile...
- InferType: 6022us [6022us] (44.85%; 44.85%)
- FoldScaleAxis: 7404us [2us] (55.15%; 55.15%)
- FoldConstant: 7402us [1553us] (55.13%; 99.97%)
- InferType: 5849us [5849us] (43.56%; 79.02%)
+ InferType: 5730us [5730us] (44.49%; 44.49%)
+ FoldScaleAxis: 7148us [2us] (55.51%; 55.51%)
+ FoldConstant: 7147us [1491us] (55.49%; 99.97%)
+ InferType: 5655us [5655us] (43.91%; 79.13%)
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 01336b0a6..ab98e0357 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
@@ -295,7 +295,7 @@ latency of convolution.
.. code-block:: none
- Convolution: 54.171381 ms
+ Convolution: 34.376518 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 bc58b3af8..9d4c4f0af 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
@@ -626,7 +626,7 @@ be able to run on our build server
.. code-block:: none
- conv2d with tensor core: 6.678759 ms
+ conv2d with tensor core: 8.285017 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 96aab5507..9f99ae360 100644
--- a/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
+++ b/docs/_sources/how_to/optimize_operators/opt_gemm.rst.txt
@@ -118,8 +118,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
.. code-block:: none
- Numpy running time: 0.018782
- Baseline: 3.347739
+ Numpy running time: 0.018710
+ Baseline: 3.319441
@@ -209,7 +209,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
.. code-block:: none
- Opt1: 0.298135
+ Opt1: 0.296857
@@ -307,7 +307,7 @@ In this tutorial, we chose to vectorize the inner loop row data since it is cach
.. code-block:: none
- Opt2: 0.335212
+ Opt2: 0.333451
@@ -398,7 +398,7 @@ the access pattern for A matrix is more cache friendly.
.. code-block:: none
- Opt3: 0.115931
+ Opt3: 0.117757
@@ -516,7 +516,7 @@ flattening.
.. code-block:: none
- Opt4: 0.110467
+ Opt4: 0.112600
@@ -633,7 +633,7 @@ write to C when all the block results are ready.
.. code-block:: none
- Opt5: 0.112188
+ Opt5: 0.113386
@@ -753,7 +753,7 @@ Futhermore, we can also utilize multi-core processors to do the thread-level par
.. code-block:: none
- Opt6: 0.144823
+ Opt6: 0.147424
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 4e76a16ca..321449bc7 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
@@ -5,8 +5,8 @@
Computation times
=================
-**00:34.735** total execution time for **how_to_optimize_operators** files:
+**00:34.823** total execution time for **how_to_optimize_operators** files:
-- **00:32.133**: :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)
-- **00:01.391**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``)
-- **00:01.210**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)
+- **00:32.245**: :ref:`sphx_glr_how_to_optimize_operators_opt_gemm.py` (``opt_gemm.py``)
+- **00:01.394**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_tensorcore.py` (``opt_conv_tensorcore.py``)
+- **00:01.184**: :ref:`sphx_glr_how_to_optimize_operators_opt_conv_cuda.py` (``opt_conv_cuda.py``)
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 b36663176..30ffc530c 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
@@ -5,11 +5,11 @@
Computation times
=================
-**04:54.182** total execution time for **how_to_tune_with_autoscheduler** files:
-
-- **02:21.389**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``)
-- **01:19.007**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)
-- **00:40.244**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)
-- **00:16.808**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)
-- **00:08.466**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)
-- **00:08.267**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)
+**04:50.933** total execution time for **how_to_tune_with_autoscheduler** files:
+
+- **02:18.923**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_conv2d_layer_cuda.py` (``tune_conv2d_layer_cuda.py``)
+- **01:19.200**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_x86.py` (``tune_network_x86.py``)
+- **00:40.043**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_cuda.py` (``tune_network_cuda.py``)
+- **00:15.921**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_sparse_x86.py` (``tune_sparse_x86.py``)
+- **00:08.605**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_mali.py` (``tune_network_mali.py``)
+- **00:08.241**: :ref:`sphx_glr_how_to_tune_with_autoscheduler_tune_network_arm.py` (``tune_network_arm.py``)
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 16bbea1d3..7bf0b5456 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
@@ -221,57 +221,157 @@ cooperative fetching, unrolling and operator fusion.
bias: Buffer(bias_2: Pointer(float32), float32, [512], []),
compute: Buffer(compute_2: Pointer(float32), float32, [25088], [])}
buffer_map = {data_1: data, kernel_1: kernel, bias_1: bias, compute_1: compute} {
- attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 32;
- allocate(conv2d_nchw: Pointer(local float32), float32, [4]), storage_scope = local;
- allocate(pad_temp.shared: Pointer(shared float32), float32, [1568]), storage_scope = shared;
- allocate(kernel.shared: Pointer(shared float32), float32, [512]), storage_scope = shared;
- attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196 {
- conv2d_nchw_1: Buffer(conv2d_nchw, float32, [4], [], scope="local", align=16)[0] = 0f32
+ attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 8;
+ allocate(conv2d_nchw: Pointer(local float32), float32, [14]), storage_scope = local;
+ allocate(pad_temp.shared: Pointer(shared float32), float32, [2016]), storage_scope = shared;
+ allocate(kernel.shared: Pointer(shared float32), float32, [6144]), storage_scope = shared;
+ attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224 {
+ conv2d_nchw_1: Buffer(conv2d_nchw, float32, [14], [], scope="local", align=32)[0] = 0f32
conv2d_nchw_1[1] = 0f32
conv2d_nchw_1[2] = 0f32
conv2d_nchw_1[3] = 0f32
+ conv2d_nchw_1[4] = 0f32
+ conv2d_nchw_1[5] = 0f32
+ conv2d_nchw_1[6] = 0f32
+ conv2d_nchw_1[7] = 0f32
+ conv2d_nchw_1[8] = 0f32
+ conv2d_nchw_1[9] = 0f32
+ conv2d_nchw_1[10] = 0f32
+ conv2d_nchw_1[11] = 0f32
+ conv2d_nchw_1[12] = 0f32
+ conv2d_nchw_1[13] = 0f32
for (rc.outer.outer: int32, 0, 16) {
- for (ry.outer.outer: int32, 0, 3) {
- for (rx.outer.outer: int32, 0, 3) {
- let cse_var_2: int32 = (rc.outer.outer*288)
- let cse_var_1: int32 = (ry.outer.outer*3)
- {
- attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1: Buffer(pad_temp.shared, float32, [1568], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) - 8)], 0f32, dtype= [...]
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 196)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 188)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 392)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 384)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 588)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 580)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 784)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 776)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 980)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 972)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 1176)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 1168)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 1372)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 1364)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- kernel.shared_1: Buffer(kernel.shared, float32, [512], [], scope="shared")[threadIdx.x_2] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 32)*4608)) + cse_var_2) + (floormod(threadIdx.x_2, 32)*9)) + cse_var_1) + rx.outer.outer)]
- attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- kernel.shared_1[(threadIdx.x_2 + 196)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 4) + 49), 8)*4608)) + cse_var_2) + (floormod((threadIdx.x_2 + 4), 32)*9)) + cse_var_1) + rx.outer.outer)]
- attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- if @tir.likely((threadIdx.x_2 < 120), dtype=bool) {
- kernel.shared_1[(threadIdx.x_2 + 392)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 4) + 98), 8)*4608)) + cse_var_2) + (floormod((threadIdx.x_2 + 8), 32)*9)) + cse_var_1) + rx.outer.outer)]
- }
- for (rc.inner: int32, 0, 32) {
- conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[((floordiv(threadIdx.x, 49)*128) + rc.inner)]))
- conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 32)]))
- conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 64)]))
- conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 96)]))
- }
+ for (rx.outer.outer: int32, 0, 3) {
+ let cse_var_2: int32 = (rc.outer.outer*1568)
+ let cse_var_1: int32 = (rc.outer.outer*288)
+ {
+ attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1: Buffer(pad_temp.shared, float32, [2016], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else(((((7 <= floormod(threadIdx.x_1, 63)) && (floormod(threadIdx.x_1, 63) < 56)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[((((cse_var_2 + (floordiv(threadIdx.x_1, 63)*49)) + rx.outer.outer) + floormod(threadIdx.x_1, 63)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 224)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 5), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 5), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 32), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 5), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dt [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 448)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 1), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 1), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 64), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 1), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dt [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 672)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 6), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 6), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 96), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 6), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, dt [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 896)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 2), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 2), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 128), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 2), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, d [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1120)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 7), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 7), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 160), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 7), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1344)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 3), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 3), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 192), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 3), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1568)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 8), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 8), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 224), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 8), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1792)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 4), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 4), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 256), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 4), 9)*7)) + rx.outer.outer) + floormod(threadIdx.x_1, 7)) - 8)], 0f32, [...]
+ attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1: Buffer(kernel.shared, float32, [6144], [], scope="shared")[threadIdx.x_2] = kernel[(((((blockIdx.x*294912) + (floordiv(threadIdx.x_2, 96)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 224)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 7), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 448)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 14), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 672)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 32256)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 896)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 28), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1120)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 35), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1344)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 64512)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1568)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 49), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1792)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 56), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2016)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 96768)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2240)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 70), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2464)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 77), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2688)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 129024)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2912)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 91), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3136)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 98), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3360)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 161280)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3584)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 112), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3808)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 119), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4032)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 193536)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4256)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 133), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4480)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 140), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4704)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 225792)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4928)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 154), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5152)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 161), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5376)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 258048)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5600)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 175), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5824)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 182), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ if @tir.likely((threadIdx.x_2 < 96), dtype=bool) {
+ kernel.shared_1[(threadIdx.x_2 + 6048)] = kernel[(((((blockIdx.x*294912) + cse_var_1) + (threadIdx.x_2*3)) + rx.outer.outer) + 290304)]
+ }
+ for (rc.outer.inner: int32, 0, 32) {
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[((rc.outer.inner*63) + floormod(threadIdx.x, 7))]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[((rc.outer.inner*63) + floormod(threadIdx.x, 7))]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 56)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 56)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
}
}
}
}
- for (i1.inner: int32, 0, 4) {
- compute[((((blockIdx.x*784) + (floordiv(threadIdx.x, 49)*196)) + (i1.inner*49)) + floormod(threadIdx.x, 49))] = max((conv2d_nchw_1[i1.inner] + bias[(((blockIdx.x*16) + (floordiv(threadIdx.x, 49)*4)) + i1.inner)]), 0f32)
+ for (i1.inner: int32, 0, 2) {
+ for (i2.inner: int32, 0, 7) {
+ compute[(((((blockIdx.x*3136) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + (i2.inner*7)) + floormod(threadIdx.x, 7))] = max((conv2d_nchw_1[((i1.inner*7) + i2.inner)] + bias[(((blockIdx.x*64) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ }
}
}
}
@@ -324,7 +424,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 0.311 ms
+ Execution time of this operator: 0.397 ms
@@ -368,33 +468,33 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
conv2d_nchw_nn_o_o_i, conv2d_nchw_nn_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_i, factor=1)
conv2d_nchw_nn_o_o_o_i, conv2d_nchw_nn_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_i, factor=1)
conv2d_nchw_nn_o_o_o_o, conv2d_nchw_nn_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_o_i, factor=1)
- conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=4)
- conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=1)
- conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=4)
+ conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=1)
+ conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=2)
+ conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=32)
conv2d_nchw_ff_o_o_o_o, conv2d_nchw_ff_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_o_i, factor=1)
conv2d_nchw_yy_o_i, conv2d_nchw_yy_i = s[conv2d_nchw].split(conv2d_nchw_yy, factor=1)
- conv2d_nchw_yy_o_o_i, conv2d_nchw_yy_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_i, factor=1)
- conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=7)
+ conv2d_nchw_yy_o_o_i, conv2d_nchw_yy_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_i, factor=7)
+ conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=1)
conv2d_nchw_yy_o_o_o_o, conv2d_nchw_yy_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_o_i, factor=1)
conv2d_nchw_xx_o_i, conv2d_nchw_xx_i = s[conv2d_nchw].split(conv2d_nchw_xx, factor=1)
conv2d_nchw_xx_o_o_i, conv2d_nchw_xx_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_i, factor=1)
conv2d_nchw_xx_o_o_o_i, conv2d_nchw_xx_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_i, factor=7)
conv2d_nchw_xx_o_o_o_o, conv2d_nchw_xx_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_o_i, factor=1)
- conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=32)
- conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=1)
+ conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=1)
+ conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=32)
conv2d_nchw_ry_o_i, conv2d_nchw_ry_i = s[conv2d_nchw].split(conv2d_nchw_ry, factor=1)
- conv2d_nchw_ry_o_o, conv2d_nchw_ry_o_i = s[conv2d_nchw].split(conv2d_nchw_ry_o_i, factor=1)
+ conv2d_nchw_ry_o_o, conv2d_nchw_ry_o_i = s[conv2d_nchw].split(conv2d_nchw_ry_o_i, factor=3)
conv2d_nchw_rx_o_i, conv2d_nchw_rx_i = s[conv2d_nchw].split(conv2d_nchw_rx, factor=1)
conv2d_nchw_rx_o_o, conv2d_nchw_rx_o_i = s[conv2d_nchw].split(conv2d_nchw_rx_o_i, factor=1)
s[conv2d_nchw].reorder(conv2d_nchw_nn_o_o_o_o, conv2d_nchw_ff_o_o_o_o, conv2d_nchw_yy_o_o_o_o, conv2d_nchw_xx_o_o_o_o, conv2d_nchw_nn_o_o_o_i, conv2d_nchw_ff_o_o_o_i, conv2d_nchw_yy_o_o_o_i, conv2d_nchw_xx_o_o_o_i, conv2d_nchw_nn_o_o_i, conv2d_nchw_ff_o_o_i, conv2d_nchw_yy_o_o_i, conv2d_nchw_xx_o_o_i, conv2d_nchw_rc_o_o, conv2d_nchw_ry_o_o, conv2d_nchw_rx_o_o, conv2d_nchw_rc_o_i, conv2d_nchw_ry_o_i, conv2d_nchw_rx_o_i, conv2d_nchw_nn_o_i, conv2d_nchw_ff_o_i, conv2d_nchw_yy_o_i, conv2 [...]
compute_i0_o_i, compute_i0_i = s[compute].split(compute_i0, factor=1)
compute_i0_o_o_i, compute_i0_o_i = s[compute].split(compute_i0_o_i, factor=1)
compute_i0_o_o_o, compute_i0_o_o_i = s[compute].split(compute_i0_o_o_i, factor=1)
- compute_i1_o_i, compute_i1_i = s[compute].split(compute_i1, factor=4)
- compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=4)
+ compute_i1_o_i, compute_i1_i = s[compute].split(compute_i1, factor=2)
+ compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=32)
compute_i1_o_o_o, compute_i1_o_o_i = s[compute].split(compute_i1_o_o_i, factor=1)
- compute_i2_o_i, compute_i2_i = s[compute].split(compute_i2, factor=1)
- compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=7)
+ compute_i2_o_i, compute_i2_i = s[compute].split(compute_i2, factor=7)
+ compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=1)
compute_i2_o_o_o, compute_i2_o_o_i = s[compute].split(compute_i2_o_o_i, factor=1)
compute_i3_o_i, compute_i3_i = s[compute].split(compute_i3, factor=1)
compute_i3_o_o_i, compute_i3_o_i = s[compute].split(compute_i3_o_i, factor=7)
@@ -417,14 +517,14 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[kernel_shared].fuse(kernel_shared_ax0, kernel_shared_ax1, kernel_shared_ax2, kernel_shared_ax3)
kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[kernel_shared].vectorize(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
- kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=196)
+ kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=224)
s[kernel_shared].bind(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[pad_temp_shared].fuse(pad_temp_shared_ax0, pad_temp_shared_ax1, pad_temp_shared_ax2, pad_temp_shared_ax3)
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[pad_temp_shared].vectorize(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
- pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=196)
+ pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=224)
s[pad_temp_shared].bind(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
- s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "auto_unroll_max_step", 16)
+ s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "auto_unroll_max_step", 512)
s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "unroll_explicit", True)
CUDA source code:
@@ -442,43 +542,117 @@ They can be used for debugging and learning the behavior of the auto-scheduler.
#define int64_t long long
#define uint64_t unsigned long long
#endif
- extern "C" __global__ void __launch_bounds__(196) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
- float conv2d_nchw[4];
- __shared__ float pad_temp_shared[1568];
- __shared__ float kernel_shared[512];
+ extern "C" __global__ void __launch_bounds__(224) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
+ float conv2d_nchw[14];
+ __shared__ float pad_temp_shared[2016];
+ __shared__ float kernel_shared[6144];
conv2d_nchw[0] = 0.000000e+00f;
conv2d_nchw[1] = 0.000000e+00f;
conv2d_nchw[2] = 0.000000e+00f;
conv2d_nchw[3] = 0.000000e+00f;
+ conv2d_nchw[4] = 0.000000e+00f;
+ conv2d_nchw[5] = 0.000000e+00f;
+ conv2d_nchw[6] = 0.000000e+00f;
+ conv2d_nchw[7] = 0.000000e+00f;
+ conv2d_nchw[8] = 0.000000e+00f;
+ conv2d_nchw[9] = 0.000000e+00f;
+ conv2d_nchw[10] = 0.000000e+00f;
+ conv2d_nchw[11] = 0.000000e+00f;
+ conv2d_nchw[12] = 0.000000e+00f;
+ conv2d_nchw[13] = 0.000000e+00f;
for (int rc_outer_outer = 0; rc_outer_outer < 16; ++rc_outer_outer) {
- for (int ry_outer_outer = 0; ry_outer_outer < 3; ++ry_outer_outer) {
- for (int rx_outer_outer = 0; rx_outer_outer < 3; ++rx_outer_outer) {
- __syncthreads();
- pad_temp_shared[((int)threadIdx.x)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 196)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 188)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 392)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 384)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 588)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 580)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 784)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 776)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 980)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 972)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1176)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 1168)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1372)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 1364)] : 0.000000e+00f);
- kernel_shared[((int)threadIdx.x)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) >> 5) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- kernel_shared[(((int)threadIdx.x) + 196)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 196) >> 5) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 4) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- if (((int)threadIdx.x) < 120) {
- kernel_shared[(((int)threadIdx.x) + 392)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 392) >> 5) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 8) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- }
- __syncthreads();
- for (int rc_inner = 0; rc_inner < 32; ++rc_inner) {
- conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[(((((int)threadIdx.x) / 49) * 128) + rc_inner)]));
- conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 32)]));
- conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 64)]));
- conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 96)]));
- }
+ for (int rx_outer_outer = 0; rx_outer_outer < 3; ++rx_outer_outer) {
+ __syncthreads();
+ pad_temp_shared[((int)threadIdx.x)] = (((((7 <= (((int)threadIdx.x) % 63)) && ((((int)threadIdx.x) % 63) < 56)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 63) * 49)) + rx_outer_outer) + (((int)threadIdx.x) % 63)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 224)] = (((((1 <= (((((int)threadIdx.x) / 7) + 5) % 9)) && ((((((int)threadIdx.x) / 7) + 5) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 224) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 5) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 448)] = (((((1 <= (((((int)threadIdx.x) / 7) + 1) % 9)) && ((((((int)threadIdx.x) / 7) + 1) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 448) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 1) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 672)] = (((((1 <= (((((int)threadIdx.x) / 7) + 6) % 9)) && ((((((int)threadIdx.x) / 7) + 6) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 672) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 6) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 896)] = (((((1 <= (((((int)threadIdx.x) / 7) + 2) % 9)) && ((((((int)threadIdx.x) / 7) + 2) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 896) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 2) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1120)] = (((((1 <= (((((int)threadIdx.x) / 7) + 7) % 9)) && ((((((int)threadIdx.x) / 7) + 7) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1120) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 7) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1344)] = (((((1 <= (((((int)threadIdx.x) / 7) + 3) % 9)) && ((((((int)threadIdx.x) / 7) + 3) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1344) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 3) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1568)] = (((((1 <= (((((int)threadIdx.x) / 7) + 8) % 9)) && ((((((int)threadIdx.x) / 7) + 8) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1568) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 8) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1792)] = (((((1 <= (((((int)threadIdx.x) / 7) + 4) % 9)) && ((((((int)threadIdx.x) / 7) + 4) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1792) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 4) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ kernel_shared[((int)threadIdx.x)] = kernel[(((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 224)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 224) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 448)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 448) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 672)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 32256)];
+ kernel_shared[(((int)threadIdx.x) + 896)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 896) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1120)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1120) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1344)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 64512)];
+ kernel_shared[(((int)threadIdx.x) + 1568)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1568) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1792)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1792) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2016)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 96768)];
+ kernel_shared[(((int)threadIdx.x) + 2240)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2240) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2464)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2464) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2688)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 129024)];
+ kernel_shared[(((int)threadIdx.x) + 2912)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2912) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3136)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3136) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3360)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 161280)];
+ kernel_shared[(((int)threadIdx.x) + 3584)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3584) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3808)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3808) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4032)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 193536)];
+ kernel_shared[(((int)threadIdx.x) + 4256)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4256) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4480)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4480) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4704)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 225792)];
+ kernel_shared[(((int)threadIdx.x) + 4928)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4928) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5152)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5152) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5376)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 258048)];
+ kernel_shared[(((int)threadIdx.x) + 5600)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5600) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5824)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5824) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ if (((int)threadIdx.x) < 96) {
+ kernel_shared[(((int)threadIdx.x) + 6048)] = kernel[(((((((int)blockIdx.x) * 294912) + (rc_outer_outer * 288)) + (((int)threadIdx.x) * 3)) + rx_outer_outer) + 290304)];
+ }
+ __syncthreads();
+ for (int rc_outer_inner = 0; rc_outer_inner < 32; ++rc_outer_inner) {
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((rc_outer_inner * 63) + (((int)threadIdx.x) % 7))] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((rc_outer_inner * 63) + (((int)threadIdx.x) % 7))] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 56)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 56)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
}
}
}
- for (int i1_inner = 0; i1_inner < 4; ++i1_inner) {
- compute[((((((int)blockIdx.x) * 784) + ((((int)threadIdx.x) / 49) * 196)) + (i1_inner * 49)) + (((int)threadIdx.x) % 49))] = max((conv2d_nchw[i1_inner] + bias[(((((int)blockIdx.x) * 16) + ((((int)threadIdx.x) / 49) * 4)) + i1_inner)]), 0.000000e+00f);
+ for (int i1_inner = 0; i1_inner < 2; ++i1_inner) {
+ for (int i2_inner = 0; i2_inner < 7; ++i2_inner) {
+ compute[(((((((int)blockIdx.x) * 3136) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (i2_inner * 7)) + (((int)threadIdx.x) % 7))] = max((conv2d_nchw[((i1_inner * 7) + i2_inner)] + bias[(((((int)blockIdx.x) * 64) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ }
}
}
@@ -537,7 +711,7 @@ 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 21.389 seconds)
+ **Total running time of the script:** ( 2 minutes 18.923 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 5bea965e6..51d9aefa0 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
@@ -614,7 +614,7 @@ 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)
- 9.6421 9.6345 9.6745 9.6174 0.0239
+ 9.4782 9.4833 9.4941 9.4573 0.0155
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 c9d794d0e..8026e4eb7 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
@@ -633,7 +633,7 @@ so we can read the log file and load the best schedules.
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 756.5040 755.1786 761.3652 752.9680 3.5539
+ 767.1472 768.3834 771.2908 761.7675 3.9849
@@ -658,7 +658,7 @@ Other Tips
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 1 minutes 19.007 seconds)
+ **Total running time of the script:** ( 1 minutes 19.200 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 afb1db082..a502fb0bd 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
@@ -362,25 +362,75 @@ 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} {
- for (i0.outer.i1.outer.fused: int32, 0, 512) "parallel" {
- allocate(compute_3: Pointer(global float32), float32, [128]), storage_scope = global {
- for (i.inner.init: int32, 0, 8) {
- for (j.init: int32, 0, 16) {
- compute_4: Buffer(compute_3, float32, [128], [])[((i.inner.init*16) + j.init)] = 0f32
+ for (i0.outer.i1.outer.fused: int32, 0, 128) "parallel" {
+ allocate(compute_3: Pointer(global float32), float32, [512]), storage_scope = global {
+ for (nb_j.inner: int32, 0, 2) {
+ for (i.inner.init: int32, 0, 16) {
+ let cse_var_1: int32 = ((i.inner.init*32) + (nb_j.inner*16))
+ {
+ compute_4: Buffer(compute_3, float32, [512], [])[cse_var_1] = 0f32
+ compute_4[(cse_var_1 + 1)] = 0f32
+ compute_4[(cse_var_1 + 2)] = 0f32
+ compute_4[(cse_var_1 + 3)] = 0f32
+ compute_4[(cse_var_1 + 4)] = 0f32
+ compute_4[(cse_var_1 + 5)] = 0f32
+ compute_4[(cse_var_1 + 6)] = 0f32
+ compute_4[(cse_var_1 + 7)] = 0f32
+ compute_4[(cse_var_1 + 8)] = 0f32
+ compute_4[(cse_var_1 + 9)] = 0f32
+ compute_4[(cse_var_1 + 10)] = 0f32
+ compute_4[(cse_var_1 + 11)] = 0f32
+ compute_4[(cse_var_1 + 12)] = 0f32
+ compute_4[(cse_var_1 + 13)] = 0f32
+ compute_4[(cse_var_1 + 14)] = 0f32
+ compute_4[(cse_var_1 + 15)] = 0f32
+ }
}
- }
- for (elem_idx: int32, 0, let cse_var_1: int32 = floormod(i0.outer.i1.outer.fused, 32) 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, 32)
- let cse_var_2: int32 = ((i.inner*16) + j)
- compute_4[cse_var_2] = (compute_4[cse_var_2] + (placeholder_1[(((placeholder_3[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 32)*2048) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_3] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, let cse_var_2: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
+ for (i.inner: int32, 0, 16) {
+ let cse_var_21: int32 = (elem_idx*16)
+ let cse_var_20: int32 = ((i.inner*32) + (nb_j.inner*16))
+ let cse_var_19: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_18: int32 = (cse_var_20 + 1)
+ let cse_var_17: int32 = (cse_var_20 + 11)
+ let cse_var_16: int32 = (cse_var_20 + 12)
+ let cse_var_15: int32 = (cse_var_20 + 13)
+ let cse_var_14: int32 = (cse_var_20 + 14)
+ let cse_var_13: int32 = (cse_var_20 + 15)
+ let cse_var_12: int32 = (cse_var_20 + 2)
+ let cse_var_11: int32 = (cse_var_20 + 3)
+ let cse_var_10: int32 = (cse_var_20 + 4)
+ let cse_var_9: int32 = (cse_var_20 + 5)
+ let cse_var_8: int32 = (cse_var_20 + 6)
+ let cse_var_7: int32 = (cse_var_20 + 7)
+ let cse_var_6: int32 = (cse_var_20 + 8)
+ let cse_var_5: int32 = (cse_var_20 + 9)
+ let cse_var_4: int32 = ((floordiv(i0.outer.i1.outer.fused, 16)*4096) + (i.inner*256))
+ let cse_var_3: int32 = (cse_var_20 + 10)
+ {
+ compute_4[cse_var_20] = (compute_4[cse_var_20] + (placeholder_1[((placeholder_3[cse_var_19]*16) + cse_var_21)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_18] = (compute_4[cse_var_18] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 1)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_12] = (compute_4[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 2)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_11] = (compute_4[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 3)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_10] = (compute_4[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 4)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_9] = (compute_4[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 5)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_8] = (compute_4[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 6)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_7] = (compute_4[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 7)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_6] = (compute_4[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 8)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_5] = (compute_4[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 9)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_3] = (compute_4[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 10)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_17] = (compute_4[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 11)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_16] = (compute_4[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 12)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_15] = (compute_4[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 13)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_14] = (compute_4[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 14)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_13] = (compute_4[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 15)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ }
}
}
}
- for (i0.inner: int32, 0, 8) {
- let cse_var_4: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*4096) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 32)*16))
- compute[ramp(cse_var_4, 1, 16)] = max((compute_4[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_4, 1, 16)]), broadcast(0f32, 16))
+ for (i0.inner: int32, 0, 16) {
+ let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*8192) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32))
+ compute[ramp(cse_var_22, 1, 32)] = max((compute_4[ramp((i0.inner*32), 1, 32)] + placeholder_4[ramp(cse_var_22, 1, 32)]), broadcast(0f32, 32))
}
}
}
@@ -434,7 +484,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 1.527 ms
+ Execution time of this operator: 1.669 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 2cbfe7a2e..fd5c8d8bc 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
@@ -5,10 +5,10 @@
Computation times
=================
-**00:44.564** total execution time for **how_to_tune_with_autotvm** files:
+**00:43.937** total execution time for **how_to_tune_with_autotvm** files:
-- **00:43.701**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)
-- **00:00.232**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)
-- **00:00.216**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``)
-- **00:00.213**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``)
-- **00:00.202**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``)
+- **00:43.104**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_conv2d_cuda.py` (``tune_conv2d_cuda.py``)
+- **00:00.221**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_x86.py` (``tune_relay_x86.py``)
+- **00:00.206**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_arm.py` (``tune_relay_arm.py``)
+- **00:00.203**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_mobile_gpu.py` (``tune_relay_mobile_gpu.py``)
+- **00:00.202**: :ref:`sphx_glr_how_to_tune_with_autotvm_tune_relay_cuda.py` (``tune_relay_cuda.py``)
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 0efd059ff..f732633c5 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
@@ -859,8 +859,8 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 95.55/95.55 result: MeasureResult(costs=(0.0024227529583333335,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.592839241027832, timestamp=1649183885.0002024) [('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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 6 GFLOPS: 112.07/112.07 result: MeasureResult(costs=(0.0020657315714285715,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8517277240753174, timestamp=1649181195.2135682) [('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: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -983,7 +983,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 8 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1106,7 +1106,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 9 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1229,7 +1229,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 10 GFLOPS: 0.00/112.07 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
@@ -1247,7 +1247,7 @@ 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 11 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1370,7 +1370,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 12 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1493,7 +1493,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 13 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1616,7 +1616,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 14 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1739,7 +1739,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 15 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1862,7 +1862,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 16 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1985,7 +1985,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 17 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2108,7 +2108,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 18 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2231,7 +2231,7 @@ for this template
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+ No: 19 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 721, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 685, in run_through_rpc
@@ -2319,7 +2319,7 @@ for this template
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007fc7a6a85fa2
+ 12: 0x00007f20a6ca8fa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2384,7 +2384,7 @@ 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: 144.29/144.29 result: MeasureResult(costs=(0.00160446036,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4021077156066895, timestamp=1649183911.2835677) [('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: 144.37/144.37 result: MeasureResult(costs=(0.00160352834,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4203155040740967, timestamp=1649181221.5153155) [('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
@@ -2437,7 +2437,7 @@ 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
- Time cost of this operator: 0.002010
+ Time cost of this operator: 0.002032
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 d3982f64d..5b5d68ffd 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
@@ -292,10 +292,10 @@ 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 312.6 98.716 (1, 2, 10, 10, 3) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.138 0.991 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.93 0.294 (1, 1, 10, 10, 3) 1 1
- Total_time - 316.667 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 309.7 98.735 (1, 2, 10, 10, 3) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.045 0.971 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.921 0.294 (1, 1, 10, 10, 3) 1 1
+ Total_time - 313.667 - - - -
@@ -357,10 +357,10 @@ 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 220.1 98.478 (1, 1, 10, 10, 6) 2 1
- tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.5 1.119 (1, 6, 10, 10) 1 1
- tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.901 0.403 (1, 3, 10, 10, 1) 1 1
- Total_time - 223.501 - - - -
+ tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 211.4 98.651 (1, 1, 10, 10, 6) 2 1
+ tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.988 0.928 (1, 6, 10, 10) 1 1
+ tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.902 0.421 (1, 3, 10, 10, 1) 1 1
+ Total_time - 214.29 - - - -
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 e4ebc1154..363a18710 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
@@ -5,10 +5,10 @@
Computation times
=================
-**00:43.704** total execution time for **how_to_work_with_microtvm** files:
+**00:44.265** total execution time for **how_to_work_with_microtvm** files:
-- **00:39.697**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)
-- **00:03.414**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)
-- **00:00.200**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_ethosu.py` (``micro_ethosu.py``)
-- **00:00.199**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_reference_vm.py` (``micro_reference_vm.py``)
-- **00:00.192**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tvmc.py` (``micro_tvmc.py``)
+- **00:40.190**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_autotune.py` (``micro_autotune.py``)
+- **00:03.484**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tflite.py` (``micro_tflite.py``)
+- **00:00.200**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_reference_vm.py` (``micro_reference_vm.py``)
+- **00:00.197**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_ethosu.py` (``micro_ethosu.py``)
+- **00:00.194**: :ref:`sphx_glr_how_to_work_with_microtvm_micro_tvmc.py` (``micro_tvmc.py``)
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 d9e48192f..4095b5f99 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
@@ -5,8 +5,8 @@
Computation times
=================
-**00:09.163** total execution time for **how_to_work_with_relay** files:
+**00:06.450** total execution time for **how_to_work_with_relay** files:
-- **00:07.214**: :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)
-- **00:01.733**: :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)
-- **00:00.216**: :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)
+- **00:04.361**: :ref:`sphx_glr_how_to_work_with_relay_using_external_lib.py` (``using_external_lib.py``)
+- **00:01.884**: :ref:`sphx_glr_how_to_work_with_relay_build_gcn.py` (``build_gcn.py``)
+- **00:00.205**: :ref:`sphx_glr_how_to_work_with_relay_using_relay_viz.py` (``using_relay_viz.py``)
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 fcd7e9c11..4e9ce1a60 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
@@ -5,13 +5,13 @@
Computation times
=================
-**00:05.473** total execution time for **how_to_work_with_schedules** files:
+**00:05.418** total execution time for **how_to_work_with_schedules** files:
-- **00:01.983**: :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)
-- **00:01.137**: :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)
-- **00:00.699**: :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)
-- **00:00.682**: :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)
-- **00:00.301**: :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)
-- **00:00.233**: :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``)
-- **00:00.223**: :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)
-- **00:00.216**: :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)
+- **00:01.962**: :ref:`sphx_glr_how_to_work_with_schedules_intrin_math.py` (``intrin_math.py``)
+- **00:01.122**: :ref:`sphx_glr_how_to_work_with_schedules_tensorize.py` (``tensorize.py``)
+- **00:00.691**: :ref:`sphx_glr_how_to_work_with_schedules_reduction.py` (``reduction.py``)
+- **00:00.675**: :ref:`sphx_glr_how_to_work_with_schedules_scan.py` (``scan.py``)
+- **00:00.298**: :ref:`sphx_glr_how_to_work_with_schedules_extern_op.py` (``extern_op.py``)
+- **00:00.232**: :ref:`sphx_glr_how_to_work_with_schedules_schedule_primitives.py` (``schedule_primitives.py``)
+- **00:00.226**: :ref:`sphx_glr_how_to_work_with_schedules_tedd.py` (``tedd.py``)
+- **00:00.213**: :ref:`sphx_glr_how_to_work_with_schedules_tuple_inputs.py` (``tuple_inputs.py``)
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 ac2f25dfc..ad3207604 100644
--- a/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
+++ b/docs/_sources/how_to/work_with_schedules/tensorize.rst.txt
@@ -314,8 +314,8 @@ The importing needs to happen before the tensorized GEMV being executed.
B: Buffer(B_2: Pointer(float32), float32, [32768], []),
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmp04zs_4v7/input0.cc'
- source_filename = "/tmp/tmp04zs_4v7/input0.cc"
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpxviplmdz/input0.cc'
+ source_filename = "/tmp/tmpxviplmdz/input0.cc"
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-pc-linux-gnu"
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 92f898470..25d26d718 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
@@ -5,7 +5,7 @@
Computation times
=================
-**00:19.765** total execution time for **topic_vta_tutorials_autotvm** files:
+**00:19.746** total execution time for **topic_vta_tutorials_autotvm** files:
-- **00:19.565**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``)
-- **00:00.200**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``)
+- **00:19.547**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_relay_vta.py` (``tune_relay_vta.py``)
+- **00:00.199**: :ref:`sphx_glr_topic_vta_tutorials_autotvm_tune_alu_vta.py` (``tune_alu_vta.py``)
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 33886c83b..a14c863a7 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_classification.rst.txt
@@ -265,7 +265,7 @@ 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 21.05s!
+ resnet18_v1 inference graph built in 20.96s!
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 83fc23ba5..ff879d851 100644
--- a/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/frontend/deploy_detection.rst.txt
@@ -301,7 +301,7 @@ The compilation steps are:
/workspace/python/tvm/relay/build_module.py:439: DeprecationWarning: Please use input parameter mod (tvm.IRModule) instead of deprecated parameter mod (tvm.relay.function.Function)
DeprecationWarning,
- yolov3-tiny inference graph built in 14.44s!
+ yolov3-tiny inference graph built in 14.30s!
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 83fd2bd33..4e7964789 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
@@ -5,7 +5,7 @@
Computation times
=================
-**01:27.414** total execution time for **topic_vta_tutorials_frontend** files:
+**01:27.071** total execution time for **topic_vta_tutorials_frontend** files:
-- **00:46.317**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)
-- **00:41.097**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``)
+- **00:46.189**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_detection.py` (``deploy_detection.py``)
+- **00:40.881**: :ref:`sphx_glr_topic_vta_tutorials_frontend_deploy_classification.py` (``deploy_classification.py``)
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 7ebc57004..9bbce57c6 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
@@ -5,7 +5,7 @@
Computation times
=================
-**00:03.451** total execution time for **topic_vta_tutorials_optimize** files:
+**00:03.469** total execution time for **topic_vta_tutorials_optimize** files:
-- **00:02.931**: :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)
-- **00:00.520**: :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``)
+- **00:02.956**: :ref:`sphx_glr_topic_vta_tutorials_optimize_convolution_opt.py` (``convolution_opt.py``)
+- **00:00.513**: :ref:`sphx_glr_topic_vta_tutorials_optimize_matrix_multiply_opt.py` (``matrix_multiply_opt.py``)
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 6bcc23a78..c4ae40a63 100644
--- a/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
+++ b/docs/_sources/topic/vta/tutorials/sg_execution_times.rst.txt
@@ -5,7 +5,7 @@
Computation times
=================
-**00:00.949** total execution time for **topic_vta_tutorials** files:
+**00:00.926** total execution time for **topic_vta_tutorials** files:
-- **00:00.479**: :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``)
-- **00:00.470**: :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``)
+- **00:00.468**: :ref:`sphx_glr_topic_vta_tutorials_matrix_multiply.py` (``matrix_multiply.py``)
+- **00:00.458**: :ref:`sphx_glr_topic_vta_tutorials_vta_get_started.py` (``vta_get_started.py``)
diff --git a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
index 86568bd6a..2c06c92d5 100644
--- a/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
+++ b/docs/_sources/tutorial/auto_scheduler_matmul_x86.rst.txt
@@ -185,7 +185,7 @@ trials, we can load the best schedule from the log file and apply it.
.. code-block:: none
-
+ *E
@@ -305,7 +305,7 @@ We build the binary and check its correctness and performance.
.. code-block:: none
- Execution time of this operator: 93.814 ms
+ Execution time of this operator: 93.704 ms
@@ -414,6 +414,11 @@ Expression (TE) language that demonstrates how TVM can optimize computational
operations.
+.. rst-class:: sphx-glr-timing
+
+ **Total running time of the script:** ( 1 minutes 12.135 seconds)
+
+
.. _sphx_glr_download_tutorial_auto_scheduler_matmul_x86.py:
diff --git a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
index 9b7529341..f28fbc23f 100644
--- a/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
+++ b/docs/_sources/tutorial/autotvm_relay_x86.rst.txt
@@ -268,7 +268,7 @@ standard deviation.
.. code-block:: none
- {'mean': 492.467170759997, 'median': 492.44605545000013, 'std': 0.5235175131416864}
+ {'mean': 499.1049396499966, 'median': 498.7819513999966, 'std': 0.7775281888352579}
@@ -482,30 +482,31 @@ the tuning data to.
.. code-block:: none
-
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 1/25] Current/Best: 13.96/ 14.75 GFLOPS | Progress: (4/10) | 4.93 s
[Task 1/25] Current/Best: 6.51/ 23.71 GFLOPS | Progress: (8/10) | 7.73 s
[Task 1/25] Current/Best: 10.29/ 23.71 GFLOPS | Progress: (10/10) | 10.02 s Done.
-
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 2/25] Current/Best: 16.78/ 16.93 GFLOPS | Progress: (4/10) | 2.09 s
[Task 2/25] Current/Best: 16.39/ 16.93 GFLOPS | Progress: (8/10) | 3.58 s
[Task 2/25] Current/Best: 13.72/ 16.93 GFLOPS | Progress: (10/10) | 4.53 s Done.
-
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 3/25] Current/Best: 18.20/ 18.20 GFLOPS | Progress: (4/10) | 2.55 s
[Task 3/25] Current/Best: 23.84/ 23.84 GFLOPS | Progress: (8/10) | 3.99 s
[Task 3/25] Current/Best: 5.96/ 23.84 GFLOPS | Progress: (10/10) | 5.25 s Done.
-
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 4/25] Current/Best: 7.22/ 12.73 GFLOPS | Progress: (4/10) | 2.60 s
[Task 4/25] Current/Best: 14.31/ 18.17 GFLOPS | Progress: (8/10) | 6.48 s
[Task 4/25] Current/Best: 7.26/ 18.17 GFLOPS | Progress: (10/10) | 7.32 s Done.
-
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 5/25] Current/Best: 23.94/ 23.94 GFLOPS | Progress: (4/10) | 2.73 s
[Task 5/25] Current/Best: 18.41/ 23.94 GFLOPS | Progress: (8/10) | 4.74 s
[Task 5/25] Current/Best: 13.05/ 23.94 GFLOPS | Progress: (10/10) | 6.90 s Done.
-
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 6/25] Current/Best: 18.44/ 18.44 GFLOPS | Progress: (4/10) | 3.57 s
[Task 6/25] Current/Best: 8.34/ 18.44 GFLOPS | Progress: (8/10) | 6.15 s
[Task 6/25] Current/Best: 9.79/ 18.44 GFLOPS | Progress: (10/10) | 7.08 s Done.
-
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 7/25] Current/Best: 13.67/ 14.69 GFLOPS | Progress: (4/10) | 3.02 s
[Task 7/25] Current/Best: 16.02/ 19.32 GFLOPS | Progress: (8/10) | 4.99 s
[Task 7/25] Current/Best: 9.71/ 19.32 GFLOPS | Progress: (10/10) | 6.19 s Done.
-
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 8/25] Current/Best: 11.89/ 15.36 GFLOPS | Progress: (4/10) | 7.93 s
[Task 8/25] Current/Best: 6.70/ 15.36 GFLOPS | Progress: (8/10) | 10.17 s
[Task 8/25] Current/Best: 12.63/ 15.36 GFLOPS | Progress: (10/10) | 11.09 s Done.
-
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 9/25] Current/Best: 12.28/ 17.35 GFLOPS | Progress: (4/10) | 3.03 s
[Task 9/25] Current/Best: 17.41/ 17.41 GFLOPS | Progress: (8/10) | 13.09 s
[Task 9/25] Current/Best: 10.51/ 17.41 GFLOPS | Progress: (10/10) | 13.89 s Done.
-
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 10/25] Current/Best: 16.37/ 16.37 GFLOPS | Progress: (4/10) | 2.39 s
[Task 10/25] Current/Best: 10.30/ 18.13 GFLOPS | Progress: (8/10) | 5.24 s
[Task 10/25] Current/Best: 14.31/ 18.13 GFLOPS | Progress: (10/10) | 5.98 s Done.
-
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 11/25] Current/Best: 17.32/ 18.39 GFLOPS | Progress: (4/10) | 2.99 s
[Task 11/25] Current/Best: 21.35/ 22.69 GFLOPS | Progress: (8/10) | 4.54 s
[Task 11/25] Current/Best: 22.23/ 22.69 GFLOPS | Progress: (10/10) | 5.66 s Done.
-
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 12/25] Current/Best: 13.36/ 20.79 GFLOPS | Progress: (4/10) | 2.74 s
[Task 12/25] Current/Best: 4.59/ 20.79 GFLOPS | Progress: (8/10) | 5.09 s
[Task 12/25] Current/Best: 10.04/ 20.79 GFLOPS | Progress: (10/10) | 6.21 s Done.
-
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 13/25] Current/Best: 20.02/ 20.02 GFLOPS | Progress: (4/10) | 3.85 s
[Task 13/25] Current/Best: 14.46/ 20.33 GFLOPS | Progress: (8/10) | 5.75 s
[Task 13/25] Current/Best: 18.43/ 20.33 GFLOPS | Progress: (10/10) | 7.22 s Done.
-
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 14/25] Current/Best: 9.41/ 9.41 GFLOPS | Progress: (4/10) | 6.83 s
[Task 14/25] Current/Best: 15.83/ 18.70 GFLOPS | Progress: (8/10) | 8.53 s
[Task 14/25] Current/Best: 9.26/ 18.70 GFLOPS | Progress: (10/10) | 13.62 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 15/25] Current/Best: 18.07/ 18.07 GFLOPS | Progress: (4/10) | 5.31 s Done.
-
[Task 15/25] Current/Best: 24.05/ 24.05 GFLOPS | Progress: (8/10) | 8.22 s
[Task 15/25] Current/Best: 13.42/ 24.05 GFLOPS | Progress: (10/10) | 8.94 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 16/25] Current/Best: 6.68/ 15.27 GFLOPS | Progress: (4/10) | 3.25 s
[Task 16/25] Current/Best: 19.95/ 19.95 GFLOPS | Progress: (8/10) | 4.57 s
[Task 16/25] Current/Best: 7.68/ 19.95 GFLOPS | Progress: (10/10) | 5.90 s Done.
-
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 17/25] Current/Best: 18.99/ 18.99 GFLOPS | Progress: (4/10) | 2.97 s
[Task 17/25] Current/Best: 8.20/ 18.99 GFLOPS | Progress: (8/10) | 6.14 s
[Task 17/25] Current/Best: 13.39/ 18.99 GFLOPS | Progress: (10/10) | 7.58 s Done.
-
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 18/25] Current/Best: 20.18/ 20.18 GFLOPS | Progress: (4/10) | 6.02 s
[Task 18/25] Current/Best: 11.85/ 20.18 GFLOPS | Progress: (8/10) | 8.45 s
[Task 18/25] Current/Best: 19.93/ 20.18 GFLOPS | Progress: (10/10) | 9.81 s Done.
-
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 19/25] Current/Best: 15.58/ 15.58 GFLOPS | Progress: (4/10) | 6.40 s
[Task 19/25] Current/Best: 11.34/ 19.61 GFLOPS | Progress: (8/10) | 8.75 s
[Task 19/25] Current/Best: 8.17/ 19.61 GFLOPS | Progress: (10/10) | 10.10 s Done.
-
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 20/25] Current/Best: 14.82/ 14.82 GFLOPS | Progress: (4/10) | 3.37 s
[Task 20/25] Current/Best: 18.93/ 18.93 GFLOPS | Progress: (8/10) | 4.67 s
[Task 20/25] Current/Best: 10.69/ 18.93 GFLOPS | Progress: (10/10) | 5.76 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 21/25] Current/Best: 20.18/ 21.64 GFLOPS | Progress: (4/10) | 2.69 s
[Task 21/25] Current/Best: 16.76/ 23.09 GFLOPS | Progress: (8/10) | 4.40 s
[Task 21/25] Current/Best: 12.92/ 23.09 GFLOPS | Progress: (10/10) | 5.21 s Done.
-
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 22/25] Current/Best: 19.09/ 19.47 GFLOPS | Progress: (4/10) | 2.53 s
[Task 22/25] Current/Best: 13.19/ 19.47 GFLOPS | Progress: (8/10) | 3.90 s
[Task 22/25] Current/Best: 7.42/ 19.47 GFLOPS | Progress: (10/10) | 4.86 s Done.
-
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 23/25] Current/Best: 18.53/ 23.75 GFLOPS | Progress: (4/10) | 4.52 s
[Task 23/25] Current/Best: 17.74/ 23.75 GFLOPS | Progress: (8/10) | 7.45 s
[Task 23/25] Current/Best: 8.07/ 23.75 GFLOPS | Progress: (10/10) | 9.40 s Done.
-
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 24/25] Current/Best: 6.18/ 10.48 GFLOPS | Progress: (4/10) | 6789.53 s
[Task 24/25] Current/Best: 1.16/ 10.48 GFLOPS | Progress: (8/10) | 6795.52 s
[Task 24/25] Current/Best: 7.48/ 10.48 GFLOPS | Progress: (10/10) | 6799.10 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s Done.
+
[Task 1/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 1/25] Current/Best: 9.11/ 14.96 GFLOPS | Progress: (4/10) | 6.77 s
[Task 1/25] Current/Best: 16.09/ 24.19 GFLOPS | Progress: (8/10) | 9.66 s
[Task 1/25] Current/Best: 8.57/ 24.19 GFLOPS | Progress: (10/10) | 10.65 s Done.
+
[Task 2/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 2/25] Current/Best: 9.33/ 14.15 GFLOPS | Progress: (4/10) | 2.80 s
[Task 2/25] Current/Best: 17.20/ 18.89 GFLOPS | Progress: (8/10) | 4.04 s
[Task 2/25] Current/Best: 12.62/ 18.89 GFLOPS | Progress: (10/10) | 4.89 s Done.
+
[Task 3/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 3/25] Current/Best: 12.43/ 22.73 GFLOPS | Progress: (4/10) | 2.61 s
[Task 3/25] Current/Best: 1.63/ 24.31 GFLOPS | Progress: (8/10) | 5.70 s
[Task 3/25] Current/Best: 17.07/ 24.31 GFLOPS | Progress: (10/10) | 6.46 s Done.
+
[Task 4/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 4/25] Current/Best: 7.04/ 14.20 GFLOPS | Progress: (4/10) | 6.44 s
[Task 4/25] Current/Best: 13.57/ 14.20 GFLOPS | Progress: (8/10) | 8.57 s
[Task 4/25] Current/Best: 16.18/ 16.18 GFLOPS | Progress: (10/10) | 9.50 s Done.
+
[Task 5/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 5/25] Current/Best: 22.61/ 22.61 GFLOPS | Progress: (4/10) | 3.35 s
[Task 5/25] Current/Best: 12.23/ 22.61 GFLOPS | Progress: (8/10) | 6.54 s
[Task 5/25] Current/Best: 12.55/ 22.61 GFLOPS | Progress: (10/10) | 7.96 s Done.
+
[Task 6/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 6/25] Current/Best: 16.72/ 16.72 GFLOPS | Progress: (4/10) | 4.36 s
[Task 6/25] Current/Best: 10.21/ 22.79 GFLOPS | Progress: (8/10) | 6.71 s
[Task 6/25] Current/Best: 4.87/ 22.79 GFLOPS | Progress: (10/10) | 8.32 s Done.
+
[Task 7/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 7/25] Current/Best: 6.10/ 13.93 GFLOPS | Progress: (4/10) | 3.78 s
[Task 7/25] Current/Best: 21.59/ 21.59 GFLOPS | Progress: (8/10) | 5.25 s
[Task 7/25] Current/Best: 6.32/ 21.59 GFLOPS | Progress: (10/10) | 6.87 s Done.
+
[Task 8/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 8/25] Current/Best: 9.22/ 9.22 GFLOPS | Progress: (4/10) | 8.15 s
[Task 8/25] Current/Best: 12.25/ 12.25 GFLOPS | Progress: (8/10) | 10.73 s
[Task 8/25] Current/Best: 18.74/ 18.74 GFLOPS | Progress: (10/10) | 12.85 s Done.
+
[Task 9/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 9/25] Current/Best: 18.26/ 20.21 GFLOPS | Progress: (4/10) | 2.70 s
[Task 9/25] Current/Best: 3.27/ 23.03 GFLOPS | Progress: (8/10) | 4.22 s
[Task 9/25] Current/Best: 13.84/ 23.03 GFLOPS | Progress: (10/10) | 5.29 s Done.
+
[Task 10/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 10/25] Current/Best: 6.81/ 18.47 GFLOPS | Progress: (4/10) | 2.80 s
[Task 10/25] Current/Best: 12.00/ 18.47 GFLOPS | Progress: (8/10) | 5.89 s
[Task 10/25] Current/Best: 5.86/ 18.47 GFLOPS | Progress: (10/10) | 7.32 s Done.
+
[Task 11/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 11/25] Current/Best: 14.90/ 18.82 GFLOPS | Progress: (4/10) | 3.68 s
[Task 11/25] Current/Best: 18.57/ 18.82 GFLOPS | Progress: (8/10) | 6.15 s
[Task 11/25] Current/Best: 15.37/ 18.82 GFLOPS | Progress: (10/10) | 7.60 s Done.
+
[Task 12/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 12/25] Current/Best: 12.15/ 18.48 GFLOPS | Progress: (4/10) | 4.06 s
[Task 12/25] Current/Best: 18.19/ 18.48 GFLOPS | Progress: (8/10) | 6.02 s
[Task 12/25] Current/Best: 20.67/ 20.67 GFLOPS | Progress: (10/10) | 6.85 s Done.
+
[Task 13/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 13/25] Current/Best: 22.63/ 22.63 GFLOPS | Progress: (4/10) | 3.81 s
[Task 13/25] Current/Best: 13.22/ 22.63 GFLOPS | Progress: (8/10) | 6.97 s
[Task 13/25] Current/Best: 6.22/ 22.63 GFLOPS | Progress: (10/10) | 8.07 s Done.
+
[Task 14/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 14/25] Current/Best: 13.46/ 15.54 GFLOPS | Progress: (4/10) | 6.77 s
[Task 14/25] Current/Best: 11.59/ 17.82 GFLOPS | Progress: (8/10) | 8.91 s
[Task 14/25] Current/Best: 13.27/ 17.82 GFLOPS | Progress: (10/10) | 9.98 s
[Task 15/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 15/25] Current/Best: 8.89/ 13.99 GFLOPS | Progress: (4/10) | 3.14 s
[Task 15/25] Current/Best: 10.58/ 21.61 GFLOPS | Progress: (8/10) | 6.86 s
[Task 15/25] Current/Best: 6.12/ 21.61 GFLOPS | Progress: (10/10) | 8.04 s
[Task 16/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s Done.
Done.
-
[Task 25/25] Current/Best: 2.99/ 8.85 GFLOPS | Progress: (4/10) | 17.31 s
[Task 25/25] Current/Best: 7.31/ 8.85 GFLOPS | Progress: (8/10) | 20.90 s
[Task 25/25] Current/Best: 5.74/ 8.85 GFLOPS | Progress: (10/10) | 21.40 s
+
[Task 16/25] Current/Best: 14.18/ 18.29 GFLOPS | Progress: (4/10) | 2.74 s
[Task 16/25] Current/Best: 9.58/ 23.22 GFLOPS | Progress: (8/10) | 3.92 s
[Task 16/25] Current/Best: 22.21/ 23.22 GFLOPS | Progress: (10/10) | 4.47 s Done.
+
[Task 17/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 17/25] Current/Best: 15.11/ 16.76 GFLOPS | Progress: (4/10) | 2.90 s
[Task 17/25] Current/Best: 12.58/ 23.25 GFLOPS | Progress: (8/10) | 4.86 s
[Task 17/25] Current/Best: 5.17/ 23.25 GFLOPS | Progress: (10/10) | 6.68 s Done.
+
[Task 18/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 18/25] Current/Best: 19.96/ 19.96 GFLOPS | Progress: (4/10) | 3.13 s
[Task 18/25] Current/Best: 10.81/ 19.96 GFLOPS | Progress: (8/10) | 6.51 s
[Task 18/25] Current/Best: 11.65/ 19.96 GFLOPS | Progress: (10/10) | 7.84 s Done.
+
[Task 19/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 19/25] Current/Best: 13.89/ 15.81 GFLOPS | Progress: (4/10) | 3.49 s
[Task 19/25] Current/Best: 5.33/ 15.81 GFLOPS | Progress: (8/10) | 6.07 s
[Task 19/25] Current/Best: 17.49/ 19.37 GFLOPS | Progress: (10/10) | 6.99 s Done.
+
[Task 20/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 20/25] Current/Best: 1.58/ 10.26 GFLOPS | Progress: (4/10) | 4.66 s
[Task 20/25] Current/Best: 8.27/ 17.88 GFLOPS | Progress: (8/10) | 6.89 s
[Task 20/25] Current/Best: 9.91/ 17.88 GFLOPS | Progress: (10/10) | 8.38 s
[Task 21/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 21/25] Current/Best: 16.62/ 22.58 GFLOPS | Progress: (4/10) | 3.98 s
[Task 21/25] Current/Best: 10.66/ 22.58 GFLOPS | Progress: (8/10) | 6.01 s
[Task 21/25] Current/Best: 5.44/ 22.58 GFLOPS | Progress: (10/10) | 6.70 s
[Task 22/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 22/25] Current/Best: 13.77/ 17.84 GFLOPS | Progress: (4/10) | 3.17 s
[Task 22/25] Current/Best: 17.09/ 19.53 GFLOPS | Progress: (8/10) | 4.36 s
[Task 22/25] Current/Best: 3.10/ 19.53 GFLOPS | Progress: (10/10) | 5.36
s Done.
+
[Task 23/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 23/25] Current/Best: 19.66/ 19.66 GFLOPS | Progress: (4/10) | 3.68 s
[Task 23/25] Current/Best: 10.97/ 19.66 GFLOPS | Progress: (8/10) | 9.27 s
[Task 23/25] Current/Best: 18.58/ 20.85 GFLOPS | Progress: (10/10) | 10.15 s Done.
+
[Task 24/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s
[Task 24/25] Current/Best: 7.30/ 7.30 GFLOPS | Progress: (4/10) | 224.89 s
[Task 24/25] Current/Best: 4.48/ 7.30 GFLOPS | Progress: (8/10) | 230.65 s
[Task 24/25] Current/Best: 6.25/ 7.30 GFLOPS | Progress: (10/10) | 231.15 s
[Task 25/25] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/10) | 0.00 s Done.
+ Done.
+ Done.
+
[Task 25/25] Current/Best: 2.96/ 8.47 GFLOPS | Progress: (4/10) | 2.53 s
[Task 25/25] Current/Best: 8.54/ 9.81 GFLOPS | Progress: (8/10) | 15.67 s
[Task 25/25] Current/Best: 8.56/ 9.81 GFLOPS | Progress: (10/10) | 16.20 s
The output from this tuning process will look something like this:
@@ -647,8 +648,8 @@ improvement in comparing the optimized model to the unoptimized model.
.. code-block:: none
- optimized: {'mean': 429.0573660999962, 'median': 429.01000560000284, 'std': 0.7345522108018623}
- unoptimized: {'mean': 492.467170759997, 'median': 492.44605545000013, 'std': 0.5235175131416864}
+ optimized: {'mean': 419.4012590700004, 'median': 419.7932991999551, 'std': 1.8317447484633385}
+ unoptimized: {'mean': 499.1049396499966, 'median': 498.7819513999966, 'std': 0.7775281888352579}
@@ -668,7 +669,7 @@ profiling/benchmarking.
.. rst-class:: sphx-glr-timing
- **Total running time of the script:** ( 119 minutes 49.037 seconds)
+ **Total running time of the script:** ( 10 minutes 14.798 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 10e60f4a2..b74512fae 100644
--- a/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
+++ b/docs/_sources/tutorial/cross_compilation_and_rpc.rst.txt
@@ -235,7 +235,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.201e-07 secs/op
+ 1.223e-07 secs/op
diff --git a/docs/_sources/tutorial/intro_topi.rst.txt b/docs/_sources/tutorial/intro_topi.rst.txt
index be1fc1638..146a7c0e7 100644
--- a/docs/_sources/tutorial/intro_topi.rst.txt
+++ b/docs/_sources/tutorial/intro_topi.rst.txt
@@ -230,7 +230,7 @@ As you can see, scheduled stages of computation have been accumulated and we can
.. code-block:: none
- [stage(a, placeholder(a, 0x20e55b60)), stage(b, placeholder(b, 0x210f4760)), 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, 0x261e8110)), stage(b, placeholder(b, 0xbfba0e0)), 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(min [...]
diff --git a/docs/_sources/tutorial/sg_execution_times.rst.txt b/docs/_sources/tutorial/sg_execution_times.rst.txt
index c5c56c175..8162803e7 100644
--- a/docs/_sources/tutorial/sg_execution_times.rst.txt
+++ b/docs/_sources/tutorial/sg_execution_times.rst.txt
@@ -5,17 +5,17 @@
Computation times
=================
-**122:24.913** total execution time for **tutorial** files:
+**13:19.455** total execution time for **tutorial** files:
-- **119:49.037**: :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)
-- **00:58.702**: :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)
-- **00:49.088**: :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``)
-- **00:25.679**: :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)
-- **00:20.060**: :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)
-- **00:01.281**: :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)
-- **00:00.713**: :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)
-- **00:00.195**: :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``)
-- **00:00.042**: :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)
-- **00:00.041**: :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``)
-- **00:00.041**: :ref:`sphx_glr_tutorial_install.py` (``install.py``)
-- **00:00.034**: :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)
+- **10:14.798**: :ref:`sphx_glr_tutorial_autotvm_relay_x86.py` (``autotvm_relay_x86.py``)
+- **01:12.135**: :ref:`sphx_glr_tutorial_auto_scheduler_matmul_x86.py` (``auto_scheduler_matmul_x86.py``)
+- **01:00.536**: :ref:`sphx_glr_tutorial_tensor_expr_get_started.py` (``tensor_expr_get_started.py``)
+- **00:25.670**: :ref:`sphx_glr_tutorial_relay_quick_start.py` (``relay_quick_start.py``)
+- **00:24.669**: :ref:`sphx_glr_tutorial_autotvm_matmul_x86.py` (``autotvm_matmul_x86.py``)
+- **00:00.702**: :ref:`sphx_glr_tutorial_intro_topi.py` (``intro_topi.py``)
+- **00:00.556**: :ref:`sphx_glr_tutorial_tensor_ir_blitz_course.py` (``tensor_ir_blitz_course.py``)
+- **00:00.206**: :ref:`sphx_glr_tutorial_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``)
+- **00:00.049**: :ref:`sphx_glr_tutorial_introduction.py` (``introduction.py``)
+- **00:00.048**: :ref:`sphx_glr_tutorial_install.py` (``install.py``)
+- **00:00.044**: :ref:`sphx_glr_tutorial_tvmc_python.py` (``tvmc_python.py``)
+- **00:00.042**: :ref:`sphx_glr_tutorial_tvmc_command_line_driver.py` (``tvmc_command_line_driver.py``)
diff --git a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
index 70562c60a..227cc9e26 100644
--- a/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
+++ b/docs/_sources/tutorial/tensor_expr_get_started.rst.txt
@@ -244,7 +244,7 @@ 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
@@ -387,7 +387,7 @@ factor to be the number of threads on your CPU.
.. code-block:: none
- vector: 0.000024
+ vector: 0.000025
@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, [(stride: int32*n: int32)], [], type="auto"),
@@ -436,10 +436,10 @@ We can now compare the different schedules
.. code-block:: none
Operator Timing Performance
- numpy 8.115009995890432e-06 1.0
- naive 6.715100000000001e-06 0.8274912789264133
- parallel 6.042899999999999e-06 0.7446571234120745
- vector 2.44389e-05 3.011567454923191
+ numpy 7.916590002423618e-06 1.0
+ naive 5.9459999999999995e-06 0.7510809576067052
+ parallel 6.0416e-06 0.7631568640223125
+ vector 2.4634900000000004e-05 3.1118069765464895
@@ -828,7 +828,7 @@ matrix multiplication.
.. code-block:: none
- Numpy running time: 0.018801
+ Numpy running time: 0.018957
@@ -884,7 +884,7 @@ optimizations.
.. code-block:: none
- none: 3.262534
+ none: 3.347262
@@ -982,7 +982,7 @@ schedule.
.. code-block:: none
- blocking: 0.288632
+ blocking: 0.322226
@@ -1073,7 +1073,7 @@ already cache friendly from our previous optimizations.
.. code-block:: none
- vectorization: 0.319709
+ vectorization: 0.345056
@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], []),
@@ -1144,7 +1144,7 @@ more cache friendly.
.. code-block:: none
- loop permutation: 0.119549
+ loop permutation: 0.118940
@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], []),
@@ -1240,7 +1240,7 @@ optimized schedule.
.. code-block:: none
- array packing: 0.111093
+ array packing: 0.108758
@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], []),
@@ -1330,7 +1330,7 @@ to `C` when all the block results are ready.
.. code-block:: none
- block caching: 0.110773
+ block caching: 0.110610
@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], []),
@@ -1413,7 +1413,7 @@ of thread-level parallelization.
.. code-block:: none
- parallelization: 0.143956
+ parallelization: 0.144876
@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], []),
@@ -1491,13 +1491,13 @@ working, we can compare the results.
.. code-block:: none
Operator Timing Performance
- none 3.2625340355 1.0
- blocking 0.28863202769999996 0.08846866409955034
- vectorization 0.3197094943 0.09799422498622391
- loop permutation 0.11954862159999999 0.036642873392025335
- array packing 0.11109267649999999 0.03405103986385677
- block caching 0.1107727707 0.03395298546916876
- parallelization 0.1439559117 0.044123957063313214
+ none 3.3472621636999995 1.0
+ blocking 0.3222262188 0.09626560545344835
+ vectorization 0.34505561560000003 0.10308592477219716
+ loop permutation 0.1189401184 0.03553355326925629
+ array packing 0.10875797829999997 0.03249162240097172
+ block caching 0.110609531 0.03304477677294758
+ parallelization 0.1448755054 0.043281792197554486
@@ -1532,6 +1532,11 @@ operations with tunable parameters that allows you to automatically optimize
the computation for specific platforms.
+.. rst-class:: sphx-glr-timing
+
+ **Total running time of the script:** ( 1 minutes 0.536 seconds)
+
+
.. _sphx_glr_download_tutorial_tensor_expr_get_started.py:
diff --git a/docs/commit_hash b/docs/commit_hash
index 0a5e3cb9d..7ca1c6ed1 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-64dd05b0c0a73b8b395602821641a02af9d92e2b
+5ec061f9766d40c9ef27662b48485b80075142a3
diff --git a/docs/how_to/compile_models/from_mxnet.html b/docs/how_to/compile_models/from_mxnet.html
index e6c2c1d29..a876233f4 100644
--- a/docs/how_to/compile_models/from_mxnet.html
+++ b/docs/how_to/compile_models/from_mxnet.html
@@ -400,7 +400,7 @@
</div>
<img alt="../../_images/sphx_glr_from_mxnet_001.png" class="sphx-glr-single-img" src="../../_images/sphx_glr_from_mxnet_001.png" />
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zip44141c3a-0e11-4b6e-a8ba-8e947f92cdd1 from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/resnet18_v1-a0666292.zip...
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/resnet18_v1-a0666292.zipe32d3e85-a3e2-4077-b0f3-55553b5b0ee2 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_paddle.html b/docs/how_to/compile_models/from_paddle.html
index e8426697d..8b9eeeb78 100644
--- a/docs/how_to/compile_models/from_paddle.html
+++ b/docs/how_to/compile_models/from_paddle.html
@@ -463,7 +463,7 @@ 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 4.093 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 5.575 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-paddle-py">
<div class="sphx-glr-download 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 22e4bd5bc..5d4e06c66 100644
--- a/docs/how_to/compile_models/from_pytorch.html
+++ b/docs/how_to/compile_models/from_pytorch.html
@@ -386,9 +386,53 @@ 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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diff --git a/docs/how_to/compile_models/from_tensorflow.html b/docs/how_to/compile_models/from_tensorflow.html
index e66a8c789..a2b05e64a 100644
--- a/docs/how_to/compile_models/from_tensorflow.html
+++ b/docs/how_to/compile_models/from_tensorflow.html
@@ -606,7 +606,7 @@ 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 1.045 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 0.955 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-compile-models-from-tensorflow-py">
<div class="sphx-glr-download 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 a80503c0c..2713d1afc 100644
--- a/docs/how_to/compile_models/sg_execution_times.html
+++ b/docs/how_to/compile_models/sg_execution_times.html
@@ -300,17 +300,17 @@
<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>04:44.641</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
+<p><strong>04:53.594</strong> total execution time for <strong>how_to_compile_models</strong> files:</p>
<ul class="simple">
-<li><p><strong>01:04.093</strong>: <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></li>
-<li><p><strong>01:01.045</strong>: <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></li>
-<li><p><strong>00:55.752</strong>: <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></li>
-<li><p><strong>00:25.368</strong>: <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></li>
-<li><p><strong>00:22.179</strong>: <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></li>
-<li><p><strong>00:20.580</strong>: <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></li>
-<li><p><strong>00:19.293</strong>: <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></li>
-<li><p><strong>00:13.632</strong>: <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></li>
-<li><p><strong>00:02.699</strong>: <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></li>
+<li><p><strong>01:05.575</strong>: <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></li>
+<li><p><strong>01:00.955</strong>: <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></li>
+<li><p><strong>00:57.042</strong>: <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></li>
+<li><p><strong>00:26.250</strong>: <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></li>
+<li><p><strong>00:24.046</strong>: <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></li>
+<li><p><strong>00:21.962</strong>: <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></li>
+<li><p><strong>00:21.277</strong>: <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></li>
+<li><p><strong>00:13.855</strong>: <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></li>
+<li><p><strong>00:02.632</strong>: <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></li>
</ul>
</div>
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 132d545b2..e377ae9df 100644
--- a/docs/how_to/deploy_models/deploy_model_on_android.html
+++ b/docs/how_to/deploy_models/deploy_model_on_android.html
@@ -622,7 +622,7 @@ to the remote android device.</p>
Evaluate inference time cost...
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 16.0534 16.0881 16.3155 15.7336 0.1698
+ 15.7893 15.7791 15.9486 15.6496 0.1033
</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 66ce7fd13..6e25acbac 100644
--- a/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
+++ b/docs/how_to/deploy_models/deploy_object_detection_pytorch.html
@@ -409,14 +409,15 @@ 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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/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').
@@ -509,7 +510,7 @@ torchvision rcnn models.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Get 9 valid boxes
</pre></div>
</div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 2.538 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 0.672 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-object-detection-pytorch-py">
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<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 7343d6915..80ade2eb2 100644
--- a/docs/how_to/deploy_models/deploy_prequantized.html
+++ b/docs/how_to/deploy_models/deploy_prequantized.html
@@ -450,9 +450,10 @@ 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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</div>
@@ -541,7 +542,7 @@ output values are identical out of 1000 outputs from mobilenet v2.</p>
<p class="sphx-glr-script-out">Out:</p>
<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)
- 90.1482 90.0487 90.9326 89.9494 0.2301
+ 90.3071 90.1194 98.5680 89.9626 1.0693
</pre></div>
</div>
<div class="admonition note">
@@ -580,7 +581,7 @@ 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 4.459 seconds)</p>
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<p><a class="reference download internal" download="" href="../../_downloads/fb8217c13f4351224c6cf3aacf1a87fc/deploy_prequantized.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">deploy_prequantized.py</span></code></a></p>
diff --git a/docs/how_to/deploy_models/deploy_prequantized_tflite.html b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
index 71ee6b1d7..9a211b075 100644
--- a/docs/how_to/deploy_models/deploy_prequantized_tflite.html
+++ b/docs/how_to/deploy_models/deploy_prequantized_tflite.html
@@ -540,7 +540,7 @@ TFLite Top-5 labels: [387 102 386 341 349]
<p class="sphx-glr-script-out">Out:</p>
<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)
- 119.0673 118.7645 140.0764 117.7407 2.2965
+ 119.5094 119.4100 124.7076 118.6000 0.6309
</pre></div>
</div>
<div class="admonition note">
@@ -568,7 +568,7 @@ network for ARM CPU</span></a>.</p></li>
</ul>
</div></blockquote>
</div>
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+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 57.817 seconds)</p>
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<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 1f3dd5af4..e23891c2c 100644
--- a/docs/how_to/deploy_models/deploy_quantized.html
+++ b/docs/how_to/deploy_models/deploy_quantized.html
@@ -480,7 +480,7 @@ for calibration. But the accuracy might be impacted.</p>
DeprecationWarning,
</pre></div>
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<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 7d5fd6294..9ad8811b4 100644
--- a/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
+++ b/docs/how_to/deploy_models/deploy_ssd_gluoncv.html
@@ -415,24 +415,24 @@ 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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<p>Create TVM runtime and do inference
@@ -472,7 +472,7 @@ Downloading /workspace/.mxnet/models/ssd_512_resnet50_v1_voc-9c8b225a.zip from h
</pre></div>
</div>
<img alt="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" class="sphx-glr-single-img" src="../../_images/sphx_glr_deploy_ssd_gluoncv_001.png" />
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 20.620 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 21.079 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-deploy-models-deploy-ssd-gluoncv-py">
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<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 c6b4e5521..ad47b5c6f 100644
--- a/docs/how_to/deploy_models/sg_execution_times.html
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@@ -300,16 +300,16 @@
<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>10:21.476</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
+<p><strong>10:28.194</strong> total execution time for <strong>how_to_deploy_models</strong> files:</p>
<ul class="simple">
-<li><p><strong>03:02.538</strong>: <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></li>
-<li><p><strong>02:20.620</strong>: <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></li>
-<li><p><strong>01:52.051</strong>: <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></li>
-<li><p><strong>01:13.515</strong>: <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></li>
-<li><p><strong>01:04.459</strong>: <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></li>
-<li><p><strong>00:26.989</strong>: <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></li>
-<li><p><strong>00:21.108</strong>: <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></li>
-<li><p><strong>00:00.196</strong>: <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></li>
+<li><p><strong>03:00.672</strong>: <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></li>
+<li><p><strong>02:21.079</strong>: <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></li>
+<li><p><strong>01:57.817</strong>: <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></li>
+<li><p><strong>01:17.380</strong>: <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></li>
+<li><p><strong>01:02.677</strong>: <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></li>
+<li><p><strong>00:26.727</strong>: <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></li>
+<li><p><strong>00:21.656</strong>: <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></li>
+<li><p><strong>00:00.186</strong>: <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></li>
</ul>
</div>
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 caf7e3c29..f39c33480 100644
--- a/docs/how_to/extend_tvm/bring_your_own_datatypes.html
+++ b/docs/how_to/extend_tvm/bring_your_own_datatypes.html
@@ -588,7 +588,7 @@ In this alpha state of the Bring Your Own Datatypes framework, we have not imple
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading /workspace/.mxnet/models/mobilenet0.25-9f83e440.zip3b99be30-aa86-4492-8b02-d4c729a8b20c 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.zip1de20b6f-9555-4ec4-a42f-30ffd53050a2 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 1b29ea2f8..7eb518997 100644
--- a/docs/how_to/extend_tvm/sg_execution_times.html
+++ b/docs/how_to/extend_tvm/sg_execution_times.html
@@ -300,12 +300,12 @@
<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>00:37.955</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
+<p><strong>00:37.730</strong> total execution time for <strong>how_to_extend_tvm</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:34.324</strong>: <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></li>
-<li><p><strong>00:02.236</strong>: <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></li>
-<li><p><strong>00:01.198</strong>: <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></li>
-<li><p><strong>00:00.197</strong>: <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></li>
+<li><p><strong>00:34.250</strong>: <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></li>
+<li><p><strong>00:02.224</strong>: <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></li>
+<li><p><strong>00:01.054</strong>: <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></li>
+<li><p><strong>00:00.202</strong>: <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></li>
</ul>
</div>
diff --git a/docs/how_to/extend_tvm/use_pass_instrument.html b/docs/how_to/extend_tvm/use_pass_instrument.html
index 8453220b4..f75039a8e 100644
--- a/docs/how_to/extend_tvm/use_pass_instrument.html
+++ b/docs/how_to/extend_tvm/use_pass_instrument.html
@@ -486,10 +486,10 @@ profile the execution time of each passes.</p>
</div>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 6891us [6891us] (48.12%; 48.12%)
-FoldScaleAxis: 7429us [3us] (51.88%; 51.88%)
- FoldConstant: 7427us [1539us] (51.86%; 99.96%)
- InferType: 5888us [5888us] (41.12%; 79.28%)
+InferType: 5935us [5935us] (45.39%; 45.39%)
+FoldScaleAxis: 7141us [2us] (54.61%; 54.61%)
+ FoldConstant: 7139us [1461us] (54.60%; 99.97%)
+ InferType: 5678us [5678us] (43.42%; 79.53%)
</pre></div>
</div>
</div>
@@ -512,10 +512,10 @@ Refer to following sections and <a class="reference internal" href="../../refere
</div>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Printing results of timing profile...
-InferType: 6022us [6022us] (44.85%; 44.85%)
-FoldScaleAxis: 7404us [2us] (55.15%; 55.15%)
- FoldConstant: 7402us [1553us] (55.13%; 99.97%)
- InferType: 5849us [5849us] (43.56%; 79.02%)
+InferType: 5730us [5730us] (44.49%; 44.49%)
+FoldScaleAxis: 7148us [2us] (55.51%; 55.51%)
+ FoldConstant: 7147us [1491us] (55.49%; 99.97%)
+ InferType: 5655us [5655us] (43.91%; 79.13%)
</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 79d5156d4..1b717cde4 100644
--- a/docs/how_to/optimize_operators/opt_conv_cuda.html
+++ b/docs/how_to/optimize_operators/opt_conv_cuda.html
@@ -534,7 +534,7 @@ latency of convolution.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 54.171381 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Convolution: 34.376518 ms
</pre></div>
</div>
<div class="sphx-glr-footer class 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 0caba54ac..444c5c4fc 100644
--- a/docs/how_to/optimize_operators/opt_conv_tensorcore.html
+++ b/docs/how_to/optimize_operators/opt_conv_tensorcore.html
@@ -876,7 +876,7 @@ be able to run on our build server</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 6.678759 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>conv2d with tensor core: 8.285017 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 89f256939..f0674afbc 100644
--- a/docs/how_to/optimize_operators/opt_gemm.html
+++ b/docs/how_to/optimize_operators/opt_gemm.html
@@ -431,8 +431,8 @@ Then we write a baseline implementation, the simplest way to write a matrix mult
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.018782
-Baseline: 3.347739
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Numpy running time: 0.018710
+Baseline: 3.319441
</pre></div>
</div>
<p>In TVM, we can always inspect lower level IR to debug or optimize our schedule.
@@ -493,7 +493,7 @@ fill 32 * 32 * sizeof(float) which is 4KB in the cache whose total size is 32KB
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.298135
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt1: 0.296857
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -561,7 +561,7 @@ vastly.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.335212
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt2: 0.333451
</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>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.115931
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt3: 0.117757
</pre></div>
</div>
<p>Here is the generated IR after loop permutation.</p>
@@ -707,7 +707,7 @@ flattening.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.110467
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt4: 0.112600
</pre></div>
</div>
<p>Here is the generated IR after array packing.</p>
@@ -794,7 +794,7 @@ write to C when all the block results are ready.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.112188
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt5: 0.113386
</pre></div>
</div>
<p>Here is the generated IR after blocking.</p>
@@ -885,7 +885,7 @@ write to C when all the block results are ready.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.144823
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Opt6: 0.147424
</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 52ac392b6..b9e82c883 100644
--- a/docs/how_to/optimize_operators/sg_execution_times.html
+++ b/docs/how_to/optimize_operators/sg_execution_times.html
@@ -300,11 +300,11 @@
<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>00:34.735</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
+<p><strong>00:34.823</strong> total execution time for <strong>how_to_optimize_operators</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:32.133</strong>: <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></li>
-<li><p><strong>00:01.391</strong>: <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></li>
-<li><p><strong>00:01.210</strong>: <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></li>
+<li><p><strong>00:32.245</strong>: <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></li>
+<li><p><strong>00:01.394</strong>: <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></li>
+<li><p><strong>00:01.184</strong>: <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></li>
</ul>
</div>
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 054d56606..97605247d 100644
--- a/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
+++ b/docs/how_to/tune_with_autoscheduler/sg_execution_times.html
@@ -300,14 +300,14 @@
<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>04:54.182</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
+<p><strong>04:50.933</strong> total execution time for <strong>how_to_tune_with_autoscheduler</strong> files:</p>
<ul class="simple">
-<li><p><strong>02:21.389</strong>: <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></li>
-<li><p><strong>01:19.007</strong>: <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></li>
-<li><p><strong>00:40.244</strong>: <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></li>
-<li><p><strong>00:16.808</strong>: <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></li>
-<li><p><strong>00:08.466</strong>: <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></li>
-<li><p><strong>00:08.267</strong>: <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></li>
+<li><p><strong>02:18.923</strong>: <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></li>
+<li><p><strong>01:19.200</strong>: <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></li>
+<li><p><strong>00:40.043</strong>: <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></li>
+<li><p><strong>00:15.921</strong>: <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></li>
+<li><p><strong>00:08.605</strong>: <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></li>
+<li><p><strong>00:08.241</strong>: <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></li>
</ul>
</div>
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 9f4e9be77..16420f955 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
@@ -469,57 +469,157 @@ cooperative fetching, unrolling and operator fusion.</p>
bias: Buffer(bias_2: Pointer(float32), float32, [512], []),
compute: Buffer(compute_2: Pointer(float32), float32, [25088], [])}
buffer_map = {data_1: data, kernel_1: kernel, bias_1: bias, compute_1: compute} {
- attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 32;
- allocate(conv2d_nchw: Pointer(local float32), float32, [4]), storage_scope = local;
- allocate(pad_temp.shared: Pointer(shared float32), float32, [1568]), storage_scope = shared;
- allocate(kernel.shared: Pointer(shared float32), float32, [512]), storage_scope = shared;
- attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196 {
- conv2d_nchw_1: Buffer(conv2d_nchw, float32, [4], [], scope="local", align=16)[0] = 0f32
+ attr [IterVar(blockIdx.x: int32, (nullptr), "ThreadIndex", "blockIdx.x")] "thread_extent" = 8;
+ allocate(conv2d_nchw: Pointer(local float32), float32, [14]), storage_scope = local;
+ allocate(pad_temp.shared: Pointer(shared float32), float32, [2016]), storage_scope = shared;
+ allocate(kernel.shared: Pointer(shared float32), float32, [6144]), storage_scope = shared;
+ attr [IterVar(threadIdx.x: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224 {
+ conv2d_nchw_1: Buffer(conv2d_nchw, float32, [14], [], scope="local", align=32)[0] = 0f32
conv2d_nchw_1[1] = 0f32
conv2d_nchw_1[2] = 0f32
conv2d_nchw_1[3] = 0f32
+ conv2d_nchw_1[4] = 0f32
+ conv2d_nchw_1[5] = 0f32
+ conv2d_nchw_1[6] = 0f32
+ conv2d_nchw_1[7] = 0f32
+ conv2d_nchw_1[8] = 0f32
+ conv2d_nchw_1[9] = 0f32
+ conv2d_nchw_1[10] = 0f32
+ conv2d_nchw_1[11] = 0f32
+ conv2d_nchw_1[12] = 0f32
+ conv2d_nchw_1[13] = 0f32
for (rc.outer.outer: int32, 0, 16) {
- for (ry.outer.outer: int32, 0, 3) {
- for (rx.outer.outer: int32, 0, 3) {
- let cse_var_2: int32 = (rc.outer.outer*288)
- let cse_var_1: int32 = (ry.outer.outer*3)
- {
- attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1: Buffer(pad_temp.shared, float32, [1568], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx. [...]
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 196)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 188)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 392)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 384)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 588)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 580)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 784)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 776)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 980)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 972)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 1176)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 1168)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- pad_temp.shared_1[(threadIdx.x_1 + 1372)] = @tir.if_then_else(((((1 <= (floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer)) && ((floordiv(floormod(threadIdx.x_1, 49), 7) + ry.outer.outer) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((rc.outer.outer*1568) + (ry.outer.outer*7)) + threadIdx.x_1) + rx.outer.outer) + 1364)], 0f32, dtype=float32)
- attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- kernel.shared_1: Buffer(kernel.shared, float32, [512], [], scope="shared")[threadIdx.x_2] = kernel[((((((blockIdx.x*73728) + (floordiv(threadIdx.x_2, 32)*4608)) + cse_var_2) + (floormod(threadIdx.x_2, 32)*9)) + cse_var_1) + rx.outer.outer)]
- attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- kernel.shared_1[(threadIdx.x_2 + 196)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 4) + 49), 8)*4608)) + cse_var_2) + (floormod((threadIdx.x_2 + 4), 32)*9)) + cse_var_1) + rx.outer.outer)]
- attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 196;
- if @tir.likely((threadIdx.x_2 < 120), dtype=bool) {
- kernel.shared_1[(threadIdx.x_2 + 392)] = kernel[((((((blockIdx.x*73728) + (floordiv((floordiv(threadIdx.x_2, 4) + 98), 8)*4608)) + cse_var_2) + (floormod((threadIdx.x_2 + 8), 32)*9)) + cse_var_1) + rx.outer.outer)]
- }
- for (rc.inner: int32, 0, 32) {
- conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[((floordiv(threadIdx.x, 49)*128) + rc.inner)]))
- conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 32)]))
- conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 64)]))
- conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[((rc.inner*49) + floormod(threadIdx.x, 49))]*kernel.shared_1[(((floordiv(threadIdx.x, 49)*128) + rc.inner) + 96)]))
- }
+ for (rx.outer.outer: int32, 0, 3) {
+ let cse_var_2: int32 = (rc.outer.outer*1568)
+ let cse_var_1: int32 = (rc.outer.outer*288)
+ {
+ attr [IterVar(threadIdx.x_1: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1: Buffer(pad_temp.shared, float32, [2016], [], scope="shared")[threadIdx.x_1] = @tir.if_then_else(((((7 <= floormod(threadIdx.x_1, 63)) && (floormod(threadIdx.x_1, 63) < 56)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[((((cse_var_2 + (floordiv(threadIdx.x_1, 63)*49)) + rx.outer.outer) + floormod(threadIdx.x_1, 63)) - 8)], 0f32, dtype=float32)
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 224)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 5), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 5), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 32), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 5), 9)*7)) + rx.outer.outer) + floormod(th [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 448)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 1), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 1), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 64), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 1), 9)*7)) + rx.outer.outer) + floormod(th [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 672)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 6), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 6), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 96), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 6), 9)*7)) + rx.outer.outer) + floormod(th [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 896)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 2), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 2), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 128), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 2), 9)*7)) + rx.outer.outer) + floormod(t [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1120)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 7), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 7), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 160), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 7), 9)*7)) + rx.outer.outer) + floormod( [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1344)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 3), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 3), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 192), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 3), 9)*7)) + rx.outer.outer) + floormod( [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1568)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 8), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 8), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 224), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 8), 9)*7)) + rx.outer.outer) + floormod( [...]
+ attr [IterVar(threadIdx.x_1, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ pad_temp.shared_1[(threadIdx.x_1 + 1792)] = @tir.if_then_else(((((1 <= floormod((floordiv(threadIdx.x_1, 7) + 4), 9)) && (floormod((floordiv(threadIdx.x_1, 7) + 4), 9) < 8)) && (1 <= (rx.outer.outer + floormod(threadIdx.x_1, 7)))) && ((rx.outer.outer + floormod(threadIdx.x_1, 7)) < 8)), data[(((((cse_var_2 + (floordiv((floordiv(threadIdx.x_1, 7) + 256), 9)*49)) + (floormod((floordiv(threadIdx.x_1, 7) + 4), 9)*7)) + rx.outer.outer) + floormod( [...]
+ attr [IterVar(threadIdx.x_2: int32, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1: Buffer(kernel.shared, float32, [6144], [], scope="shared")[threadIdx.x_2] = kernel[(((((blockIdx.x*294912) + (floordiv(threadIdx.x_2, 96)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 224)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 7), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 448)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 14), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 672)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 32256)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 896)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 28), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1120)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 35), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1344)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 64512)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1568)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 49), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 1792)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 56), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2016)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 96768)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2240)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 70), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2464)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 77), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2688)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 129024)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 2912)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 91), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3136)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 98), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3360)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 161280)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3584)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 112), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 3808)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 119), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4032)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 193536)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4256)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 133), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4480)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 140), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4704)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 225792)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 4928)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 154), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5152)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 161), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5376)] = kernel[((((((blockIdx.x*294912) + (floordiv(floordiv(threadIdx.x_2, 32), 3)*4608)) + cse_var_1) + (floormod(threadIdx.x_2, 96)*3)) + rx.outer.outer) + 258048)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5600)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 175), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 32), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ kernel.shared_1[(threadIdx.x_2 + 5824)] = kernel[(((((blockIdx.x*294912) + (floordiv((floordiv(threadIdx.x_2, 32) + 182), 3)*4608)) + cse_var_1) + (floormod((threadIdx.x_2 + 64), 96)*3)) + rx.outer.outer)]
+ attr [IterVar(threadIdx.x_2, (nullptr), "ThreadIndex", "threadIdx.x")] "thread_extent" = 224;
+ if @tir.likely((threadIdx.x_2 < 96), dtype=bool) {
+ kernel.shared_1[(threadIdx.x_2 + 6048)] = kernel[(((((blockIdx.x*294912) + cse_var_1) + (threadIdx.x_2*3)) + rx.outer.outer) + 290304)]
+ }
+ for (rc.outer.inner: int32, 0, 32) {
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[((rc.outer.inner*63) + floormod(threadIdx.x, 7))]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3))]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[((rc.outer.inner*63) + floormod(threadIdx.x, 7))]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 96)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 1)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 7)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 97)]))
+ conv2d_nchw_1[0] = (conv2d_nchw_1[0] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[1] = (conv2d_nchw_1[1] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[2] = (conv2d_nchw_1[2] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[3] = (conv2d_nchw_1[3] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[4] = (conv2d_nchw_1[4] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[5] = (conv2d_nchw_1[5] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[6] = (conv2d_nchw_1[6] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 56)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 2)]))
+ conv2d_nchw_1[7] = (conv2d_nchw_1[7] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 14)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[8] = (conv2d_nchw_1[8] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 21)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[9] = (conv2d_nchw_1[9] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 28)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[10] = (conv2d_nchw_1[10] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 35)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[11] = (conv2d_nchw_1[11] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 42)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[12] = (conv2d_nchw_1[12] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 49)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
+ conv2d_nchw_1[13] = (conv2d_nchw_1[13] + (pad_temp.shared_1[(((rc.outer.inner*63) + floormod(threadIdx.x, 7)) + 56)]*kernel.shared_1[(((floordiv(threadIdx.x, 7)*192) + (rc.outer.inner*3)) + 98)]))
}
}
}
}
- for (i1.inner: int32, 0, 4) {
- compute[((((blockIdx.x*784) + (floordiv(threadIdx.x, 49)*196)) + (i1.inner*49)) + floormod(threadIdx.x, 49))] = max((conv2d_nchw_1[i1.inner] + bias[(((blockIdx.x*16) + (floordiv(threadIdx.x, 49)*4)) + i1.inner)]), 0f32)
+ for (i1.inner: int32, 0, 2) {
+ for (i2.inner: int32, 0, 7) {
+ compute[(((((blockIdx.x*3136) + (floordiv(threadIdx.x, 7)*98)) + (i1.inner*49)) + (i2.inner*7)) + floormod(threadIdx.x, 7))] = max((conv2d_nchw_1[((i1.inner*7) + i2.inner)] + bias[(((blockIdx.x*64) + (floordiv(threadIdx.x, 7)*2)) + i1.inner)]), 0f32)
+ }
}
}
}
@@ -557,7 +657,7 @@ cooperative fetching, unrolling and operator fusion.</p>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.311 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 0.397 ms
</pre></div>
</div>
</div>
@@ -587,33 +687,33 @@ conv2d_nchw_nn_o_i, conv2d_nchw_nn_i = s[conv2d_nchw].split(conv2d_nchw_nn, fact
conv2d_nchw_nn_o_o_i, conv2d_nchw_nn_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_i, factor=1)
conv2d_nchw_nn_o_o_o_i, conv2d_nchw_nn_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_i, factor=1)
conv2d_nchw_nn_o_o_o_o, conv2d_nchw_nn_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_nn_o_o_o_i, factor=1)
-conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=4)
-conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=1)
-conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=4)
+conv2d_nchw_ff_o_i, conv2d_nchw_ff_i = s[conv2d_nchw].split(conv2d_nchw_ff, factor=1)
+conv2d_nchw_ff_o_o_i, conv2d_nchw_ff_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_i, factor=2)
+conv2d_nchw_ff_o_o_o_i, conv2d_nchw_ff_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_i, factor=32)
conv2d_nchw_ff_o_o_o_o, conv2d_nchw_ff_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_ff_o_o_o_i, factor=1)
conv2d_nchw_yy_o_i, conv2d_nchw_yy_i = s[conv2d_nchw].split(conv2d_nchw_yy, factor=1)
-conv2d_nchw_yy_o_o_i, conv2d_nchw_yy_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_i, factor=1)
-conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=7)
+conv2d_nchw_yy_o_o_i, conv2d_nchw_yy_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_i, factor=7)
+conv2d_nchw_yy_o_o_o_i, conv2d_nchw_yy_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_i, factor=1)
conv2d_nchw_yy_o_o_o_o, conv2d_nchw_yy_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_yy_o_o_o_i, factor=1)
conv2d_nchw_xx_o_i, conv2d_nchw_xx_i = s[conv2d_nchw].split(conv2d_nchw_xx, factor=1)
conv2d_nchw_xx_o_o_i, conv2d_nchw_xx_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_i, factor=1)
conv2d_nchw_xx_o_o_o_i, conv2d_nchw_xx_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_i, factor=7)
conv2d_nchw_xx_o_o_o_o, conv2d_nchw_xx_o_o_o_i = s[conv2d_nchw].split(conv2d_nchw_xx_o_o_o_i, factor=1)
-conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=32)
-conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=1)
+conv2d_nchw_rc_o_i, conv2d_nchw_rc_i = s[conv2d_nchw].split(conv2d_nchw_rc, factor=1)
+conv2d_nchw_rc_o_o, conv2d_nchw_rc_o_i = s[conv2d_nchw].split(conv2d_nchw_rc_o_i, factor=32)
conv2d_nchw_ry_o_i, conv2d_nchw_ry_i = s[conv2d_nchw].split(conv2d_nchw_ry, factor=1)
-conv2d_nchw_ry_o_o, conv2d_nchw_ry_o_i = s[conv2d_nchw].split(conv2d_nchw_ry_o_i, factor=1)
+conv2d_nchw_ry_o_o, conv2d_nchw_ry_o_i = s[conv2d_nchw].split(conv2d_nchw_ry_o_i, factor=3)
conv2d_nchw_rx_o_i, conv2d_nchw_rx_i = s[conv2d_nchw].split(conv2d_nchw_rx, factor=1)
conv2d_nchw_rx_o_o, conv2d_nchw_rx_o_i = s[conv2d_nchw].split(conv2d_nchw_rx_o_i, factor=1)
s[conv2d_nchw].reorder(conv2d_nchw_nn_o_o_o_o, conv2d_nchw_ff_o_o_o_o, conv2d_nchw_yy_o_o_o_o, conv2d_nchw_xx_o_o_o_o, conv2d_nchw_nn_o_o_o_i, conv2d_nchw_ff_o_o_o_i, conv2d_nchw_yy_o_o_o_i, conv2d_nchw_xx_o_o_o_i, conv2d_nchw_nn_o_o_i, conv2d_nchw_ff_o_o_i, conv2d_nchw_yy_o_o_i, conv2d_nchw_xx_o_o_i, conv2d_nchw_rc_o_o, conv2d_nchw_ry_o_o, conv2d_nchw_rx_o_o, conv2d_nchw_rc_o_i, conv2d_nchw_ry_o_i, conv2d_nchw_rx_o_i, conv2d_nchw_nn_o_i, conv2d_nchw_ff_o_i, conv2d_nchw_yy_o_i, conv2d_nc [...]
compute_i0_o_i, compute_i0_i = s[compute].split(compute_i0, factor=1)
compute_i0_o_o_i, compute_i0_o_i = s[compute].split(compute_i0_o_i, factor=1)
compute_i0_o_o_o, compute_i0_o_o_i = s[compute].split(compute_i0_o_o_i, factor=1)
-compute_i1_o_i, compute_i1_i = s[compute].split(compute_i1, factor=4)
-compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=4)
+compute_i1_o_i, compute_i1_i = s[compute].split(compute_i1, factor=2)
+compute_i1_o_o_i, compute_i1_o_i = s[compute].split(compute_i1_o_i, factor=32)
compute_i1_o_o_o, compute_i1_o_o_i = s[compute].split(compute_i1_o_o_i, factor=1)
-compute_i2_o_i, compute_i2_i = s[compute].split(compute_i2, factor=1)
-compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=7)
+compute_i2_o_i, compute_i2_i = s[compute].split(compute_i2, factor=7)
+compute_i2_o_o_i, compute_i2_o_i = s[compute].split(compute_i2_o_i, factor=1)
compute_i2_o_o_o, compute_i2_o_o_i = s[compute].split(compute_i2_o_o_i, factor=1)
compute_i3_o_i, compute_i3_i = s[compute].split(compute_i3, factor=1)
compute_i3_o_o_i, compute_i3_o_i = s[compute].split(compute_i3_o_i, factor=7)
@@ -636,14 +736,14 @@ s[compute].bind(compute_i0_o_i_i1_o_i_fused_i2_o_i_fused_i3_o_i_fused, te.thread
kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[kernel_shared].fuse(kernel_shared_ax0, kernel_shared_ax1, kernel_shared_ax2, kernel_shared_ax3)
kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[kernel_shared].vectorize(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
-kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=196)
+kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[kernel_shared].split(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=224)
s[kernel_shared].bind(kernel_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused = s[pad_temp_shared].fuse(pad_temp_shared_ax0, pad_temp_shared_ax1, pad_temp_shared_ax2, pad_temp_shared_ax3)
pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused, factor=1)
s[pad_temp_shared].vectorize(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_i)
-pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=196)
+pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_o, pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i = s[pad_temp_shared].split(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o, factor=224)
s[pad_temp_shared].bind(pad_temp_shared_ax0_ax1_fused_ax2_fused_ax3_fused_o_i, te.thread_axis("threadIdx.x"))
-s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "auto_unroll_max_step", 16)
+s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "auto_unroll_max_step", 512)
s[conv2d_nchw].pragma(conv2d_nchw_nn_o_o_o_o, "unroll_explicit", True)
CUDA source code:
@@ -661,43 +761,117 @@ CUDA source code:
#define int64_t long long
#define uint64_t unsigned long long
#endif
-extern "C" __global__ void __launch_bounds__(196) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
- float conv2d_nchw[4];
- __shared__ float pad_temp_shared[1568];
- __shared__ float kernel_shared[512];
+extern "C" __global__ void __launch_bounds__(224) default_function_kernel0(float* __restrict__ data, float* __restrict__ kernel, float* __restrict__ compute, float* __restrict__ bias) {
+ float conv2d_nchw[14];
+ __shared__ float pad_temp_shared[2016];
+ __shared__ float kernel_shared[6144];
conv2d_nchw[0] = 0.000000e+00f;
conv2d_nchw[1] = 0.000000e+00f;
conv2d_nchw[2] = 0.000000e+00f;
conv2d_nchw[3] = 0.000000e+00f;
+ conv2d_nchw[4] = 0.000000e+00f;
+ conv2d_nchw[5] = 0.000000e+00f;
+ conv2d_nchw[6] = 0.000000e+00f;
+ conv2d_nchw[7] = 0.000000e+00f;
+ conv2d_nchw[8] = 0.000000e+00f;
+ conv2d_nchw[9] = 0.000000e+00f;
+ conv2d_nchw[10] = 0.000000e+00f;
+ conv2d_nchw[11] = 0.000000e+00f;
+ conv2d_nchw[12] = 0.000000e+00f;
+ conv2d_nchw[13] = 0.000000e+00f;
for (int rc_outer_outer = 0; rc_outer_outer < 16; ++rc_outer_outer) {
- for (int ry_outer_outer = 0; ry_outer_outer < 3; ++ry_outer_outer) {
- for (int rx_outer_outer = 0; rx_outer_outer < 3; ++rx_outer_outer) {
- __syncthreads();
- pad_temp_shared[((int)threadIdx.x)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) - 8)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 196)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 188)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 392)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 384)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 588)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 580)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 784)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 776)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 980)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 972)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1176)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 1168)] : 0.000000e+00f);
- pad_temp_shared[(((int)threadIdx.x) + 1372)] = (((((1 <= (((((int)threadIdx.x) % 49) / 7) + ry_outer_outer)) && ((((((int)threadIdx.x) % 49) / 7) + ry_outer_outer) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + (ry_outer_outer * 7)) + ((int)threadIdx.x)) + rx_outer_outer) + 1364)] : 0.000000e+00f);
- kernel_shared[((int)threadIdx.x)] = kernel[((((((((int)blockIdx.x) * 73728) + ((((int)threadIdx.x) >> 5) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- kernel_shared[(((int)threadIdx.x) + 196)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 196) >> 5) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 4) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- if (((int)threadIdx.x) < 120) {
- kernel_shared[(((int)threadIdx.x) + 392)] = kernel[((((((((int)blockIdx.x) * 73728) + (((((int)threadIdx.x) + 392) >> 5) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 8) & 31) * 9)) + (ry_outer_outer * 3)) + rx_outer_outer)];
- }
- __syncthreads();
- for (int rc_inner = 0; rc_inner < 32; ++rc_inner) {
- conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[(((((int)threadIdx.x) / 49) * 128) + rc_inner)]));
- conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 32)]));
- conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 64)]));
- conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[((rc_inner * 49) + (((int)threadIdx.x) % 49))] * kernel_shared[((((((int)threadIdx.x) / 49) * 128) + rc_inner) + 96)]));
- }
+ for (int rx_outer_outer = 0; rx_outer_outer < 3; ++rx_outer_outer) {
+ __syncthreads();
+ pad_temp_shared[((int)threadIdx.x)] = (((((7 <= (((int)threadIdx.x) % 63)) && ((((int)threadIdx.x) % 63) < 56)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[(((((rc_outer_outer * 1568) + ((((int)threadIdx.x) / 63) * 49)) + rx_outer_outer) + (((int)threadIdx.x) % 63)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 224)] = (((((1 <= (((((int)threadIdx.x) / 7) + 5) % 9)) && ((((((int)threadIdx.x) / 7) + 5) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 224) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 5) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 448)] = (((((1 <= (((((int)threadIdx.x) / 7) + 1) % 9)) && ((((((int)threadIdx.x) / 7) + 1) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 448) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 1) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 672)] = (((((1 <= (((((int)threadIdx.x) / 7) + 6) % 9)) && ((((((int)threadIdx.x) / 7) + 6) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 672) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 6) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 896)] = (((((1 <= (((((int)threadIdx.x) / 7) + 2) % 9)) && ((((((int)threadIdx.x) / 7) + 2) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 896) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 2) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1120)] = (((((1 <= (((((int)threadIdx.x) / 7) + 7) % 9)) && ((((((int)threadIdx.x) / 7) + 7) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1120) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 7) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1344)] = (((((1 <= (((((int)threadIdx.x) / 7) + 3) % 9)) && ((((((int)threadIdx.x) / 7) + 3) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1344) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 3) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1568)] = (((((1 <= (((((int)threadIdx.x) / 7) + 8) % 9)) && ((((((int)threadIdx.x) / 7) + 8) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1568) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 8) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ pad_temp_shared[(((int)threadIdx.x) + 1792)] = (((((1 <= (((((int)threadIdx.x) / 7) + 4) % 9)) && ((((((int)threadIdx.x) / 7) + 4) % 9) < 8)) && (1 <= (rx_outer_outer + (((int)threadIdx.x) % 7)))) && ((rx_outer_outer + (((int)threadIdx.x) % 7)) < 8)) ? data[((((((rc_outer_outer * 1568) + (((((int)threadIdx.x) + 1792) / 63) * 49)) + ((((((int)threadIdx.x) / 7) + 4) % 9) * 7)) + rx_outer_outer) + (((int)threadIdx.x) % 7)) - 8)] : 0.000000e+00f);
+ kernel_shared[((int)threadIdx.x)] = kernel[(((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 224)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 224) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 448)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 448) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 672)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 32256)];
+ kernel_shared[(((int)threadIdx.x) + 896)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 896) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1120)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1120) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1344)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 64512)];
+ kernel_shared[(((int)threadIdx.x) + 1568)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1568) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 1792)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 1792) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2016)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 96768)];
+ kernel_shared[(((int)threadIdx.x) + 2240)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2240) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2464)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2464) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 2688)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 129024)];
+ kernel_shared[(((int)threadIdx.x) + 2912)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 2912) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3136)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3136) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3360)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 161280)];
+ kernel_shared[(((int)threadIdx.x) + 3584)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3584) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 3808)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 3808) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4032)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 193536)];
+ kernel_shared[(((int)threadIdx.x) + 4256)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4256) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4480)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4480) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 4704)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 225792)];
+ kernel_shared[(((int)threadIdx.x) + 4928)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 4928) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5152)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5152) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5376)] = kernel[((((((((int)blockIdx.x) * 294912) + ((((int)threadIdx.x) / 96) * 4608)) + (rc_outer_outer * 288)) + ((((int)threadIdx.x) % 96) * 3)) + rx_outer_outer) + 258048)];
+ kernel_shared[(((int)threadIdx.x) + 5600)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5600) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 32) % 96) * 3)) + rx_outer_outer)];
+ kernel_shared[(((int)threadIdx.x) + 5824)] = kernel[(((((((int)blockIdx.x) * 294912) + (((((int)threadIdx.x) + 5824) / 96) * 4608)) + (rc_outer_outer * 288)) + (((((int)threadIdx.x) + 64) % 96) * 3)) + rx_outer_outer)];
+ if (((int)threadIdx.x) < 96) {
+ kernel_shared[(((int)threadIdx.x) + 6048)] = kernel[(((((((int)blockIdx.x) * 294912) + (rc_outer_outer * 288)) + (((int)threadIdx.x) * 3)) + rx_outer_outer) + 290304)];
+ }
+ __syncthreads();
+ for (int rc_outer_inner = 0; rc_outer_inner < 32; ++rc_outer_inner) {
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[((rc_outer_inner * 63) + (((int)threadIdx.x) % 7))] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[(((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3))]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[((rc_outer_inner * 63) + (((int)threadIdx.x) % 7))] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 96)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 1)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 7)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 97)]));
+ conv2d_nchw[0] = (conv2d_nchw[0] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[1] = (conv2d_nchw[1] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[2] = (conv2d_nchw[2] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[3] = (conv2d_nchw[3] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[4] = (conv2d_nchw[4] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[5] = (conv2d_nchw[5] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[6] = (conv2d_nchw[6] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 56)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 2)]));
+ conv2d_nchw[7] = (conv2d_nchw[7] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 14)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[8] = (conv2d_nchw[8] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 21)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[9] = (conv2d_nchw[9] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 28)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[10] = (conv2d_nchw[10] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 35)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[11] = (conv2d_nchw[11] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 42)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[12] = (conv2d_nchw[12] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 49)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
+ conv2d_nchw[13] = (conv2d_nchw[13] + (pad_temp_shared[(((rc_outer_inner * 63) + (((int)threadIdx.x) % 7)) + 56)] * kernel_shared[((((((int)threadIdx.x) / 7) * 192) + (rc_outer_inner * 3)) + 98)]));
}
}
}
- for (int i1_inner = 0; i1_inner < 4; ++i1_inner) {
- compute[((((((int)blockIdx.x) * 784) + ((((int)threadIdx.x) / 49) * 196)) + (i1_inner * 49)) + (((int)threadIdx.x) % 49))] = max((conv2d_nchw[i1_inner] + bias[(((((int)blockIdx.x) * 16) + ((((int)threadIdx.x) / 49) * 4)) + i1_inner)]), 0.000000e+00f);
+ for (int i1_inner = 0; i1_inner < 2; ++i1_inner) {
+ for (int i2_inner = 0; i2_inner < 7; ++i2_inner) {
+ compute[(((((((int)blockIdx.x) * 3136) + ((((int)threadIdx.x) / 7) * 98)) + (i1_inner * 49)) + (i2_inner * 7)) + (((int)threadIdx.x) % 7))] = max((conv2d_nchw[((i1_inner * 7) + i2_inner)] + bias[(((((int)blockIdx.x) * 64) + ((((int)threadIdx.x) / 7) * 2)) + i1_inner)]), 0.000000e+00f);
+ }
}
}
</pre></div>
@@ -735,7 +909,7 @@ 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 21.389 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 18.923 seconds)</p>
<div class="sphx-glr-footer class 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 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 cd56e395a..4448c2b65 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_cuda.html
@@ -876,7 +876,7 @@ 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)
- 9.6421 9.6345 9.6745 9.6174 0.0239
+ 9.4782 9.4833 9.4941 9.4573 0.0155
</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 2526e1e6c..8915b9d95 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_network_x86.html
@@ -895,7 +895,7 @@ 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)
- 756.5040 755.1786 761.3652 752.9680 3.5539
+ 767.1472 768.3834 771.2908 761.7675 3.9849
</pre></div>
</div>
</div>
@@ -917,7 +917,7 @@ 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 19.007 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 19.200 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-how-to-tune-with-autoscheduler-tune-network-x86-py">
<div class="sphx-glr-download 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 31f5ee17d..3a792107a 100644
--- a/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
+++ b/docs/how_to/tune_with_autoscheduler/tune_sparse_x86.html
@@ -600,25 +600,75 @@ 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} {
- for (i0.outer.i1.outer.fused: int32, 0, 512) "parallel" {
- allocate(compute_3: Pointer(global float32), float32, [128]), storage_scope = global {
- for (i.inner.init: int32, 0, 8) {
- for (j.init: int32, 0, 16) {
- compute_4: Buffer(compute_3, float32, [128], [])[((i.inner.init*16) + j.init)] = 0f32
+ for (i0.outer.i1.outer.fused: int32, 0, 128) "parallel" {
+ allocate(compute_3: Pointer(global float32), float32, [512]), storage_scope = global {
+ for (nb_j.inner: int32, 0, 2) {
+ for (i.inner.init: int32, 0, 16) {
+ let cse_var_1: int32 = ((i.inner.init*32) + (nb_j.inner*16))
+ {
+ compute_4: Buffer(compute_3, float32, [512], [])[cse_var_1] = 0f32
+ compute_4[(cse_var_1 + 1)] = 0f32
+ compute_4[(cse_var_1 + 2)] = 0f32
+ compute_4[(cse_var_1 + 3)] = 0f32
+ compute_4[(cse_var_1 + 4)] = 0f32
+ compute_4[(cse_var_1 + 5)] = 0f32
+ compute_4[(cse_var_1 + 6)] = 0f32
+ compute_4[(cse_var_1 + 7)] = 0f32
+ compute_4[(cse_var_1 + 8)] = 0f32
+ compute_4[(cse_var_1 + 9)] = 0f32
+ compute_4[(cse_var_1 + 10)] = 0f32
+ compute_4[(cse_var_1 + 11)] = 0f32
+ compute_4[(cse_var_1 + 12)] = 0f32
+ compute_4[(cse_var_1 + 13)] = 0f32
+ compute_4[(cse_var_1 + 14)] = 0f32
+ compute_4[(cse_var_1 + 15)] = 0f32
+ }
}
- }
- for (elem_idx: int32, 0, let cse_var_1: int32 = floormod(i0.outer.i1.outer.fused, 32) 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, 32)
- let cse_var_2: int32 = ((i.inner*16) + j)
- compute_4[cse_var_2] = (compute_4[cse_var_2] + (placeholder_1[(((placeholder_3[cse_var_3]*16) + (elem_idx*16)) + j)]*max(placeholder[(((floordiv(i0.outer.i1.outer.fused, 32)*2048) + (i.inner*256)) + placeholder_2[(placeholder_3[cse_var_3] + elem_idx)])], 0f32)))
+ for (elem_idx: int32, 0, let cse_var_2: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner) in (placeholder_3[(cse_var_2 + 1)] - placeholder_3[cse_var_2])) {
+ for (i.inner: int32, 0, 16) {
+ let cse_var_21: int32 = (elem_idx*16)
+ let cse_var_20: int32 = ((i.inner*32) + (nb_j.inner*16))
+ let cse_var_19: int32 = ((floormod(i0.outer.i1.outer.fused, 16)*2) + nb_j.inner)
+ let cse_var_18: int32 = (cse_var_20 + 1)
+ let cse_var_17: int32 = (cse_var_20 + 11)
+ let cse_var_16: int32 = (cse_var_20 + 12)
+ let cse_var_15: int32 = (cse_var_20 + 13)
+ let cse_var_14: int32 = (cse_var_20 + 14)
+ let cse_var_13: int32 = (cse_var_20 + 15)
+ let cse_var_12: int32 = (cse_var_20 + 2)
+ let cse_var_11: int32 = (cse_var_20 + 3)
+ let cse_var_10: int32 = (cse_var_20 + 4)
+ let cse_var_9: int32 = (cse_var_20 + 5)
+ let cse_var_8: int32 = (cse_var_20 + 6)
+ let cse_var_7: int32 = (cse_var_20 + 7)
+ let cse_var_6: int32 = (cse_var_20 + 8)
+ let cse_var_5: int32 = (cse_var_20 + 9)
+ let cse_var_4: int32 = ((floordiv(i0.outer.i1.outer.fused, 16)*4096) + (i.inner*256))
+ let cse_var_3: int32 = (cse_var_20 + 10)
+ {
+ compute_4[cse_var_20] = (compute_4[cse_var_20] + (placeholder_1[((placeholder_3[cse_var_19]*16) + cse_var_21)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_18] = (compute_4[cse_var_18] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 1)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_12] = (compute_4[cse_var_12] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 2)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_11] = (compute_4[cse_var_11] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 3)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_10] = (compute_4[cse_var_10] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 4)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_9] = (compute_4[cse_var_9] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 5)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_8] = (compute_4[cse_var_8] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 6)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_7] = (compute_4[cse_var_7] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 7)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_6] = (compute_4[cse_var_6] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 8)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_5] = (compute_4[cse_var_5] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 9)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_3] = (compute_4[cse_var_3] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 10)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_17] = (compute_4[cse_var_17] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 11)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_16] = (compute_4[cse_var_16] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 12)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_15] = (compute_4[cse_var_15] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 13)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_14] = (compute_4[cse_var_14] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 14)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ compute_4[cse_var_13] = (compute_4[cse_var_13] + (placeholder_1[(((placeholder_3[cse_var_19]*16) + cse_var_21) + 15)]*max(placeholder[(cse_var_4 + placeholder_2[(placeholder_3[cse_var_19] + elem_idx)])], 0f32)))
+ }
}
}
}
- for (i0.inner: int32, 0, 8) {
- let cse_var_4: int32 = (((floordiv(i0.outer.i1.outer.fused, 32)*4096) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 32)*16))
- compute[ramp(cse_var_4, 1, 16)] = max((compute_4[ramp((i0.inner*16), 1, 16)] + placeholder_4[ramp(cse_var_4, 1, 16)]), broadcast(0f32, 16))
+ for (i0.inner: int32, 0, 16) {
+ let cse_var_22: int32 = (((floordiv(i0.outer.i1.outer.fused, 16)*8192) + (i0.inner*512)) + (floormod(i0.outer.i1.outer.fused, 16)*32))
+ compute[ramp(cse_var_22, 1, 32)] = max((compute_4[ramp((i0.inner*32), 1, 32)] + placeholder_4[ramp(cse_var_22, 1, 32)]), broadcast(0f32, 32))
}
}
}
@@ -657,7 +707,7 @@ layout transformation, parallelization, vectorization, unrolling, and operator f
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.527 ms
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time of this operator: 1.669 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 e55850ee8..945cfa24d 100644
--- a/docs/how_to/tune_with_autotvm/sg_execution_times.html
+++ b/docs/how_to/tune_with_autotvm/sg_execution_times.html
@@ -300,13 +300,13 @@
<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>00:44.564</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
+<p><strong>00:43.937</strong> total execution time for <strong>how_to_tune_with_autotvm</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:43.701</strong>: <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></li>
-<li><p><strong>00:00.232</strong>: <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></li>
-<li><p><strong>00:00.216</strong>: <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></li>
-<li><p><strong>00:00.213</strong>: <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></li>
-<li><p><strong>00:00.202</strong>: <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></li>
+<li><p><strong>00:43.104</strong>: <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></li>
+<li><p><strong>00:00.221</strong>: <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></li>
+<li><p><strong>00:00.206</strong>: <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></li>
+<li><p><strong>00:00.203</strong>: <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></li>
+<li><p><strong>00:00.202</strong>: <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></li>
</ul>
</div>
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 3ea83f787..eed735211 100644
--- a/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
+++ b/docs/how_to/tune_with_autotvm/tune_conv2d_cuda.html
@@ -1142,8 +1142,8 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 95.55/95.55 result: MeasureResult(costs=(0.0024227529583333335,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.592839241027832, timestamp=1649183885.0002024) [('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: 0.00/95.55 result: Traceback (most recent call last):
+No: 6 GFLOPS: 112.07/112.07 result: MeasureResult(costs=(0.0020657315714285715,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.8517277240753174, timestamp=1649181195.2135682) [('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: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1266,7 +1266,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 8 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1389,7 +1389,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 9 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1512,7 +1512,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 10 GFLOPS: 0.00/112.07 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
@@ -1530,7 +1530,7 @@ No: 10 GFLOPS: 0.00/95.55 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 11 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1653,7 +1653,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 12 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1776,7 +1776,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 13 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -1899,7 +1899,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 14 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2022,7 +2022,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 15 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2145,7 +2145,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 16 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2268,7 +2268,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 17 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2391,7 +2391,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 18 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 571, in __call__
func, arg_info = _build_func_common(measure_input, self.runtime, **kwargs)
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 523, in _build_func_common
@@ -2514,7 +2514,7 @@ Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 854, 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: 0.00/95.55 result: Traceback (most recent call last):
+No: 19 GFLOPS: 0.00/112.07 result: Traceback (most recent call last):
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 721, in __call__
yield remote, remote.load_module(os.path.split(build_result.filename)[1])
File "/workspace/python/tvm/autotvm/measure/measure_methods.py", line 685, in run_through_rpc
@@ -2602,7 +2602,7 @@ tvm._ffi.base.TVMError: Traceback (most recent call last):
15: _PyEval_EvalFrameDefault
14: 0x0000000000537c30
13: _PyObject_FastCallKeywords
- 12: 0x00007fc7a6a85fa2
+ 12: 0x00007f20a6ca8fa2
11: _ctypes_callproc
10: ffi_call
9: ffi_call_unix64
@@ -2667,7 +2667,7 @@ 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: 144.29/144.29 result: MeasureResult(costs=(0.00160446036,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4021077156066895, timestamp=1649183911.2835677) [('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: 144.37/144.37 result: MeasureResult(costs=(0.00160352834,), error_no=MeasureErrorNo.NO_ERROR, all_cost=1.4203155040740967, timestamp=1649181221.5153155) [('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,
@@ -2706,7 +2706,7 @@ and measure running time.</p>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>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
-Time cost of this operator: 0.002010
+Time cost of this operator: 0.002032
</pre></div>
</div>
<div class="sphx-glr-footer class 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 ff9a0a66d..dce56cc82 100644
--- a/docs/how_to/work_with_microtvm/micro_autotune.html
+++ b/docs/how_to/work_with_microtvm/micro_autotune.html
@@ -553,10 +553,10 @@ the tuned operator.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build without Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 312.6 98.716 (1, 2, 10, 10, 3) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.138 0.991 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.93 0.294 (1, 1, 10, 10, 3) 1 1
-Total_time - 316.667 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 309.7 98.735 (1, 2, 10, 10, 3) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 3.045 0.971 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.921 0.294 (1, 1, 10, 10, 3) 1 1
+Total_time - 313.667 - - - -
</pre></div>
</div>
</div>
@@ -608,10 +608,10 @@ Total_time -
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>########## Build with Autotuning ##########
Node Name Ops Time(us) Time(%) Shape Inputs Outputs
--------- --- -------- ------- ----- ------ -------
-tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 220.1 98.478 (1, 1, 10, 10, 6) 2 1
-tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 2.5 1.119 (1, 6, 10, 10) 1 1
-tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.901 0.403 (1, 3, 10, 10, 1) 1 1
-Total_time - 223.501 - - - -
+tvmgen_default_fused_nn_contrib_conv2d_NCHWc tvmgen_default_fused_nn_contrib_conv2d_NCHWc 211.4 98.651 (1, 1, 10, 10, 6) 2 1
+tvmgen_default_fused_layout_transform_1 tvmgen_default_fused_layout_transform_1 1.988 0.928 (1, 6, 10, 10) 1 1
+tvmgen_default_fused_layout_transform tvmgen_default_fused_layout_transform 0.902 0.421 (1, 3, 10, 10, 1) 1 1
+Total_time - 214.29 - - - -
</pre></div>
</div>
<div class="sphx-glr-footer class 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/sg_execution_times.html b/docs/how_to/work_with_microtvm/sg_execution_times.html
index a84307a4a..60a353cf7 100644
--- a/docs/how_to/work_with_microtvm/sg_execution_times.html
+++ b/docs/how_to/work_with_microtvm/sg_execution_times.html
@@ -300,13 +300,13 @@
<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>00:43.704</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
+<p><strong>00:44.265</strong> total execution time for <strong>how_to_work_with_microtvm</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:39.697</strong>: <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></li>
-<li><p><strong>00:03.414</strong>: <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></li>
-<li><p><strong>00:00.200</strong>: <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</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_ethosu.py</span></code>)</p></li>
-<li><p><strong>00:00.199</strong>: <a class="reference internal" href="micro_reference_vm.html#sphx-glr-how-to-work-with-microtvm-micro-reference-vm-py"><span class="std std-ref">microTVM Reference Virtual Machines</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_reference_vm.py</span></code>)</p></li>
-<li><p><strong>00:00.192</strong>: <a class="reference internal" href="micro_tvmc.html#sphx-glr-how-to-work-with-microtvm-micro-tvmc-py"><span class="std std-ref">Executing a Tiny Model with TVMC Micro</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_tvmc.py</span></code>)</p></li>
+<li><p><strong>00:40.190</strong>: <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></li>
+<li><p><strong>00:03.484</strong>: <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></li>
+<li><p><strong>00:00.200</strong>: <a class="reference internal" href="micro_reference_vm.html#sphx-glr-how-to-work-with-microtvm-micro-reference-vm-py"><span class="std std-ref">microTVM Reference Virtual Machines</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_reference_vm.py</span></code>)</p></li>
+<li><p><strong>00:00.197</strong>: <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</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_ethosu.py</span></code>)</p></li>
+<li><p><strong>00:00.194</strong>: <a class="reference internal" href="micro_tvmc.html#sphx-glr-how-to-work-with-microtvm-micro-tvmc-py"><span class="std std-ref">Executing a Tiny Model with TVMC Micro</span></a> (<code class="docutils literal notranslate"><span class="pre">micro_tvmc.py</span></code>)</p></li>
</ul>
</div>
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 8cfabe89c..83b83025b 100644
--- a/docs/how_to/work_with_relay/sg_execution_times.html
+++ b/docs/how_to/work_with_relay/sg_execution_times.html
@@ -300,11 +300,11 @@
<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>00:09.163</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
+<p><strong>00:06.450</strong> total execution time for <strong>how_to_work_with_relay</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:07.214</strong>: <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></li>
-<li><p><strong>00:01.733</strong>: <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></li>
-<li><p><strong>00:00.216</strong>: <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></li>
+<li><p><strong>00:04.361</strong>: <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></li>
+<li><p><strong>00:01.884</strong>: <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></li>
+<li><p><strong>00:00.205</strong>: <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></li>
</ul>
</div>
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 d1ea48084..1dddb0561 100644
--- a/docs/how_to/work_with_schedules/sg_execution_times.html
+++ b/docs/how_to/work_with_schedules/sg_execution_times.html
@@ -300,16 +300,16 @@
<div class="section" id="computation-times">
<span id="sphx-glr-how-to-work-with-schedules-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:05.473</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
+<p><strong>00:05.418</strong> total execution time for <strong>how_to_work_with_schedules</strong> files:</p>
<ul class="simple">
-<li><p><strong>00:01.983</strong>: <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></li>
-<li><p><strong>00:01.137</strong>: <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></li>
-<li><p><strong>00:00.699</strong>: <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></li>
-<li><p><strong>00:00.682</strong>: <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></li>
-<li><p><strong>00:00.301</strong>: <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></li>
-<li><p><strong>00:00.233</strong>: <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></li>
-<li><p><strong>00:00.223</strong>: <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></li>
-<li><p><strong>00:00.216</strong>: <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></li>
+<li><p><strong>00:01.962</strong>: <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></li>
+<li><p><strong>00:01.122</strong>: <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></li>
+<li><p><strong>00:00.691</strong>: <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></li>
+<li><p><strong>00:00.675</strong>: <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></li>
+<li><p><strong>00:00.298</strong>: <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></li>
+<li><p><strong>00:00.232</strong>: <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></li>
+<li><p><strong>00:00.226</strong>: <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></li>
+<li><p><strong>00:00.213</strong>: <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></li>
</ul>
</div>
diff --git a/docs/how_to/work_with_schedules/tensorize.html b/docs/how_to/work_with_schedules/tensorize.html
index 37f2f1d4e..d3627e13f 100644
--- a/docs/how_to/work_with_schedules/tensorize.html
+++ b/docs/how_to/work_with_schedules/tensorize.html
@@ -548,8 +548,8 @@ The importing needs to happen before the tensorized GEMV being executed.</p>
B: Buffer(B_2: Pointer(float32), float32, [32768], []),
C: Buffer(C_2: Pointer(float32), float32, [524288], [])}
buffer_map = {A_1: A, B_1: B, C_1: C} {
- attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmp04zs_4v7/input0.cc'
-source_filename = "/tmp/tmp04zs_4v7/input0.cc"
+ attr [IterVar(i: int32, (nullptr), "DataPar", "")] "pragma_import_llvm" = "; ModuleID = '/tmp/tmpxviplmdz/input0.cc'
+source_filename = "/tmp/tmpxviplmdz/input0.cc"
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-pc-linux-gnu"
diff --git a/docs/reference/api/doxygen/annotated.html b/docs/reference/api/doxygen/annotated.html
index 57087093f..1006aaace 100644
--- a/docs/reference/api/doxygen/annotated.html
+++ b/docs/reference/api/doxygen/annotated.html
@@ -300,10 +300,11 @@ $(function() {
<tr id="row_1_5_3_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1parser_1_1SourceNode.html" target="_self">SourceNode</a></td><td class="desc"></td></tr>
<tr id="row_1_6_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_1_6_" class="arrow" onclick="toggleFolder('1_6_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacetvm_1_1relay.html" target="_self">relay</a></td><td class="desc">Relay: a high level functional IR for TVM </td></tr>
<tr id="row_1_6_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_1_6_0_" class="arrow" onclick="toggleFolder('1_6_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacetvm_1_1relay_1_1qnn.html" target="_self">qnn</a></td><td class="desc"></td></tr>
-<tr id="row_1_6_0_0_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html" target="_self">DequantizeAttrs</a></td><td class="desc">Attribute for dequantize operator </td></tr>
-<tr id="row_1_6_0_1_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html" target="_self">QuantizeAttrs</a></td><td class="desc">Attribute for quantize operator </td></tr>
-<tr id="row_1_6_0_2_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html" target="_self">RequantizeAttrs</a></td><td class="desc">Attribute for requantize operator </td></tr>
-<tr id="row_1_6_0_3_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1SimulatedQuantizeAttrs.html" target="_self">SimulatedQuantizeAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_1_6_0_0_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html" target="_self">BroadcastAttrs</a></td><td class="desc">Attribute for broadcast operator </td></tr>
+<tr id="row_1_6_0_1_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html" target="_self">DequantizeAttrs</a></td><td class="desc">Attribute for dequantize operator </td></tr>
+<tr id="row_1_6_0_2_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html" target="_self">QuantizeAttrs</a></td><td class="desc">Attribute for quantize operator </td></tr>
+<tr id="row_1_6_0_3_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html" target="_self">RequantizeAttrs</a></td><td class="desc">Attribute for requantize operator </td></tr>
+<tr id="row_1_6_0_4_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1SimulatedQuantizeAttrs.html" target="_self">SimulatedQuantizeAttrs</a></td><td class="desc"></td></tr>
<tr id="row_1_6_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1AdaptivePool1DAttrs.html" target="_self">AdaptivePool1DAttrs</a></td><td class="desc">Attributes for 1d adaptive pool operator </td></tr>
<tr id="row_1_6_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1AdaptivePool2DAttrs.html" target="_self">AdaptivePool2DAttrs</a></td><td class="desc">Attributes for 2d adaptive pool operator </td></tr>
<tr id="row_1_6_3_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1AdaptivePool3DAttrs.html" target="_self">AdaptivePool3DAttrs</a></td><td class="desc">Attributes for 3d adaptive pool operator </td></tr>
diff --git a/docs/reference/api/doxygen/classes.html b/docs/reference/api/doxygen/classes.html
index d51d66e3c..d988c5e0f 100644
--- a/docs/reference/api/doxygen/classes.html
+++ b/docs/reference/api/doxygen/classes.html
@@ -65,127 +65,128 @@ $(function() {
<div class="qindex"><a class="qindex" href="#letter_a">a</a> | <a class="qindex" href="#letter_b">b</a> | <a class="qindex" href="#letter_c">c</a> | <a class="qindex" href="#letter_d">d</a> | <a class="qindex" href="#letter_e">e</a> | <a class="qindex" href="#letter_f">f</a> | <a class="qindex" href="#letter_g">g</a> | <a class="qindex" href="#letter_h">h</a> | <a class="qindex" href="#letter_i">i</a> |& [...]
<table class="classindex">
<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_1ConvGemmWeightTransformAttrs.html">ConvGemmWeightTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1MapNode_1_1iterator.html">MapNode::iterator</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1Pragma [...]
-<tr><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_1runtime_1_1Map_1_1iterator.html">Map::iterator</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1PragmaS [...]
-<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="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_1Iterator.html">I [...]
-<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_1support_1_1Span_ [...]
-<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_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_1auto__scheduler_1_1IteratorNode.html">I [...]
-<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_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="structtvm_1_1auto__scheduler_1_1AttachMapNode_ [...]
-<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_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_1IterMapExpr.html">Iter [...]
-<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="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_1IterMapExprNode.html">IterMapExprNode</a> (<a class="el [...]
-<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 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. [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ADT.html">ADT</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</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>
+</td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv3DWinogradAttrs.html">Conv3DWinogradAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1IterAdapter.html">IterAdapter</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1PostprocNode.html">PostprocNode</a> (<a [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ConvGemmWeightTransformAttrs.html">ConvGemmWeightTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1MapNode_1_1iterator.html">MapNode::iterator</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1PragmaS [...]
+<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="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_1run [...]
+<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="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_1Iterator [...]
+<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_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_1support_1_1Span_1_1iterator__base.html">Sp [...]
+<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_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_1auto__scheduler_1_1IteratorNode.html">I [...]
+<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_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="structtvm_1_1auto__scheduler_1_1AttachMapNode_ [...]
+<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="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_1IterMapExpr.html">IterMapExpr</a> (<a class="el" href="namesp [...]
+<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 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_1IterMapExprNode.html">IterMapExprNode</a> (<a c [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ADT.html">ADT</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</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_1ar [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ADTObj.html">ADTObj</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</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>
</td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterMarkNode.html">IterMarkNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1PrimFunc.html">PrimFunc</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_1State.html">State</a> (<a class="el" href="namespacetvm_1_1auto__schedu [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ADTObj.html">ADTObj</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterSplitExpr.html">IterSplitExpr</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1PrimFuncNode.html">PrimFuncNode</a> (<a class="el" href="namespacetvm_1_1t [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AffineGridAttrs.html">AffineGridAttrs</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_1Database.html">Database</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_1IterSplitExprNode.html">IterSplitExprNode</ [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AffineType.html">AffineType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">DatabaseNode</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_1IterSumExpr.html">IterSumExpr</a> (<a class="el" href="namespacetvm_1_1 [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AffineTypeNode.html">AffineTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DataProducer.html">DataProducer</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterSumExprNode.html">IterSumExprNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm: [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllClassNonMaximumSuppressionAttrs.html">AllClassNonMaximumSuppressionAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DataProducerNode.html">DataProducerNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IterVar.html">IterVar</ [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Allocate.html">Allocate</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1DataType.html">DataType</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarAttr.html">IterVarAttr</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateConst.html">AllocateConst</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DataTypePattern.html">DataTypePattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarAttrNode.html">IterVarAttrNode</a> (<a class="el" href="namesp [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateConstNode.html">AllocateConstNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DataTypePatternNode.html">DataTypePatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IterVarNode.html">IterVarNode</a> (<a class="el" hre [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1usmp_1_1AllocatedPoolInfo.html">AllocatedPoolInfo</a> (<a class="el" href="namespacetvm_1_1tir_1_1usmp.html">tvm::tir::usmp</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DebugAttrs.html">DebugAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarRelation.html">IterVarRelation</a> (<a cl [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1tir_1_1usmp_1_1AllocatedPoolInfoNode.html">AllocatedPoolInfoNode</a> (<a class="el" href="namespacetvm_1_1tir_1_1usmp.html">tvm::tir::usmp</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DeformableConv2DAttrs.html">DeformableConv2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarRelationNo [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateNode.html">AllocateNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DenseAttrs.html">DenseAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_l"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AffineGridAttrs.html">AffineGridAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterSplitExpr.html">IterSplitExpr</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1PrimFuncNode.html">PrimFuncNode</a> (<a class="el" href="name [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AffineType.html">AffineType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1Database.html">Database</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_1IterSplitExprNode.html">IterSplitExprNode</a> (<a class="el" href="namespacetvm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AffineTypeNode.html">AffineTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1DatabaseNode.html">DatabaseNode</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_1IterSumExpr.html">IterSumExpr</a> (<a class="el" href="namespac [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllClassNonMaximumSuppressionAttrs.html">AllClassNonMaximumSuppressionAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DataProducer.html">DataProducer</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IterSumExprNode.html">IterSum [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Allocate.html">Allocate</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DataProducerNode.html">DataProducerNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IterVar.html">IterVar</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir< [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateConst.html">AllocateConst</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1DataType.html">DataType</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarAttr.html">IterVarAttr</a> (<a class="el" href="namespacetvm_1_1te.htm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateConstNode.html">AllocateConstNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DataTypePattern.html">DataTypePattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarAttrNode.html">IterVarAttrNode</a> (<a class="el" href [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1usmp_1_1AllocatedPoolInfo.html">AllocatedPoolInfo</a> (<a class="el" href="namespacetvm_1_1tir_1_1usmp.html">tvm::tir::usmp</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DataTypePatternNode.html">DataTypePatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1IterVarNode.html">IterVarNode< [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1tir_1_1usmp_1_1AllocatedPoolInfoNode.html">AllocatedPoolInfoNode</a> (<a class="el" href="namespacetvm_1_1tir_1_1usmp.html">tvm::tir::usmp</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DebugAttrs.html">DebugAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarRelation.html">IterVarRelation</ [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AllocateNode.html">AllocateNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DeformableConv2DAttrs.html">DeformableConv2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1IterVarRelationNode.html">IterVarRelationNode</a> (<a clas [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1Allocator.html">Allocator</a> (<a class="el" href="namespacetvm_1_1runtime_1_1vm.html">tvm::runtime::vm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DenseAttrs.html">DenseAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_l"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td> [...]
</td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ProgramBuilder.html">ProgramBuilder</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_1StmtSRef.html">StmtSRef</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1Allocator.html">Allocator</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_1runtime_1_1DenseMapNode.html">DenseMapNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ProgramBuilderNode.html">ProgramBuil [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllocStorageAttrs.html">AllocStorageAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DensePackAttrs.html">DensePackAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1L2NormalizeAttrs.html">L2NormalizeAttrs</a> (<a cla [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllocTensorAttrs.html">AllocTensorAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Dependency.html">Dependency</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LayerNormAttrs.html">LayerNormAttrs</a> (<a class="el" href="namespa [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AltPattern.html">AltPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DependencyNode.html">DependencyNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Layout.html">Layout</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm:: [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AltPatternNode.html">AltPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html">DequantizeAttrs</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_1tir_1_1LayoutAxis.html">LayoutAxis</a> (<a clas [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1arith_1_1Analyzer.html">Analyzer</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html">DeviceAPI</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LayoutNode.html">LayoutNode</a> (<a class="el" href="namespacetvm_1_1tir.html" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1And.html">And</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DeviceCopyAttrs.html">DeviceCopyAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LayoutTransformAttrs.html">LayoutTransformAttrs</a> (<a class="el" href="namespacetv [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AndNode.html">AndNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1DeviceWrapper.html">DeviceWrapper</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_1tir_1_1LE.html">LE</a> (<a class="el" href="name [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AnnotationStep.html">AnnotationStep</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1profiling_1_1DeviceWrapperNode.html">DeviceWrapperNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td valign="top"><a class="el" href="st [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AnnotationStepNode.html">AnnotationStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPattern.html">DFPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1tir_1_1LENode.html">LENode</a> (<a class= [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Any.html">Any</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternCallback.html">DFPatternCallback</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Let.html">Let</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>) [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AnyNode.html">AnyNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternCallbackNode.html">DFPatternCallbackNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Let.html">Let</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ApplyHistoryBest.html">ApplyHistoryBest</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternFunctor.html">DFPatternFunctor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetNode.html">LetNode</a> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ApplyHistoryBestNode.html">ApplyHistoryBestNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternFunctor_3_01R_07const_01DFPattern_01_6n_00_01Args_8_8_8_08_4.html">DFPatternFunctor< R(const DFPattern &n, Args...)></a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>) [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArangeAttrs.html">ArangeAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternNode.html">DFPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetPattern.html">LetPattern</a> (<a class="el" href="namespacetvm_1 [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ArgInfo.html">ArgInfo</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternVisitor.html">DFPatternVisitor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetPatternNode.html">LetPatternNode</a> (<a [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ArgInfoNode.html">ArgInfoNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1Diagnostic.html">Diagnostic</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LetStmt.html">LetStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tv [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArgReduceAttrs.html">ArgReduceAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticBuilder.html">DiagnosticBuilder</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LetStmtNode.html">LetStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html" [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArgsortAttrs.html">ArgsortAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticContext.html">DiagnosticContext</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1support_1_1LinearCongruentialEngine.html">LinearCongruentialEngine</a> (<a class="el" href= [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllocStorageAttrs.html">AllocStorageAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1DenseMapNode.html">DenseMapNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1ProgramBuilderNode.html">ProgramBuilderNo [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AllocTensorAttrs.html">AllocTensorAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DensePackAttrs.html">DensePackAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1L2NormalizeAttrs.html">L2NormalizeAttrs</a> (<a class [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AltPattern.html">AltPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Dependency.html">Dependency</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LayerNormAttrs.html">LayerNormAttrs</a> (<a class="el" href="namespacetvm_1_1rela [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1AltPatternNode.html">AltPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DependencyNode.html">DependencyNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Layout.html">Layout</a> (<a class="el" href="namespacetvm_1_1tir.htm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1arith_1_1Analyzer.html">Analyzer</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html">DequantizeAttrs</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_1tir_1_1LayoutAxis.html">LayoutAxis</a> (<a class="el" href= [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1And.html">And</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html">DeviceAPI</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LayoutNode.html">LayoutNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)&# [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AndNode.html">AndNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DeviceCopyAttrs.html">DeviceCopyAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LayoutTransformAttrs.html">LayoutTransformAttrs</a> (<a class="el" href="nam [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AnnotationStep.html">AnnotationStep</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_1profiling_1_1DeviceWrapper.html">DeviceWrapper</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_ [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AnnotationStepNode.html">AnnotationStepNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1profiling_1_1DeviceWrapperNode.html">DeviceWrapperNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td valign="top"><a class="el" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Any.html">Any</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPattern.html">DFPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1tir_1_1LENode.html">LENode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AnyNode.html">AnyNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternCallback.html">DFPatternCallback</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Let.html">Let</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::re [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ApplyHistoryBest.html">ApplyHistoryBest</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternCallbackNode.html">DFPatternCallbackNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Let.html">Let</a> [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ApplyHistoryBestNode.html">ApplyHistoryBestNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternFunctor.html">DFPatternFunctor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetNode.html">LetN [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArangeAttrs.html">ArangeAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternFunctor_3_01R_07const_01DFPattern_01_6n_00_01Args_8_8_8_08_4.html">DFPatternFunctor< R(const DFPattern &n, Args...)></a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a cla [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ArgInfo.html">ArgInfo</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternNode.html">DFPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetPattern.html">LetPattern</a> (<a class="el" hre [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ArgInfoNode.html">ArgInfoNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DFPatternVisitor.html">DFPatternVisitor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1LetPatternNode.html">LetPatternNode< [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArgReduceAttrs.html">ArgReduceAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1Diagnostic.html">Diagnostic</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LetStmt.html">LetStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>) &# [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ArgsortAttrs.html">ArgsortAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticBuilder.html">DiagnosticBuilder</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LetStmtNode.html">LetStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticContext.html">DiagnosticContext</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1support_1_1LinearCongruentialEngine.html">LinearCongruentialEngine</a> (<a class="el" href="namespac [...]
</td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1Array.html">Array</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticContextNode.html">DiagnosticContextNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1LinkedParam.html">LinkedParam</a> (<a class="el" href="namespacetvm.html">tvm</a>)  [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor.html">ArrayAccessor</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticNode.html">DiagnosticNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1LinkedParamNode.html">LinkedParamNode</a> (<a class="el" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor_3_01const_01char_01_5_00_01_1_1tvm_1_1runtime_1_1String_01_4.html">ArrayAccessor< const char *, ::tvm::runtime::String ></a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticRenderer.html">DiagnosticRenderer</a> (<a class="el" href="namespacetvm.html">tvm</a>)  & [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1SimpleObjAllocator_1_1ArrayHandler.html">SimpleObjAllocator::ArrayHandler</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticRendererNode.html">DiagnosticRendererNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoadNode.html">LoadNode</a> [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor.html">ArrayAccessor</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticContextNode.html">DiagnosticContextNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1LinkedParam.html">LinkedParam</a> (<a clas [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor_3_01const_01char_01_5_00_01_1_1tvm_1_1runtime_1_1String_01_4.html">ArrayAccessor< const char *, ::tvm::runtime::String ></a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticNode.html">DiagnosticNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </t [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1SimpleObjAllocator_1_1ArrayHandler.html">SimpleObjAllocator::ArrayHandler</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticRenderer.html">DiagnosticRenderer</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Load.html">Load</a> (<a class="el" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayIterator.html">ArrayIterator</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DiagnosticRendererNode.html">DiagnosticRendererNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoadNode.html">LoadNode</a> (<a c [...]
</td><td valign="top"><a class="el" href="classtvm_1_1TargetKind.html">TargetKind</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayIterator.html">ArrayIterator</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm::runtime::metadata</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DictAttrs.html">DictAttrs</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1LocalBuilder.html">LocalBuilder</a> (<a class=" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ArrayNode.html">ArrayNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DictAttrsNode.html">DictAttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1LocalBuilderNode.html">LocalBuilderNode</a> (<a class="el" href="namespacetvm_1_1 [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AssertStmt.html">AssertStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DilateAttrs.html">DilateAttrs</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_1LocalRunner.html">LocalRunner</a> (<a class="el" href="namespacetvm_1 [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ArrayNode.html">ArrayNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DictAttrs.html">DictAttrs</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1LocalBuilder.html">LocalBuilder</a> (<a class="el" href="namespacetvm_1_1auto__scheduler. [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AssertStmt.html">AssertStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1DictAttrsNode.html">DictAttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1LocalBuilderNode.html">LocalBuilderNode</a> (<a class="el" href="namespacetvm_1_1auto__sche [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AssertStmtNode.html">AssertStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DilateAttrs.html">DilateAttrs</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_1LocalRunner.html">LocalRunner</a> (<a class="el" href="namesp [...]
</td><td valign="top"><a class="el" href="classtvm_1_1TargetKindRegEntry.html">TargetKindRegEntry</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AssertStmtNode.html">AssertStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Dilation2DAttrs.html">Dilation2DAttrs</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_1LocalRunnerNode.html">LocalRunnerNode</a> (<a class=" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AttachMap.html">AttachMap</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_1Div.html">Div</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoopRV.html">LoopRV</a> (<a class="el" href="namespacetvm_1_1tir.html"> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AttachMapNode.html">AttachMapNode</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_1DivNode.html">DivNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoopRVNode.html">LoopRVNode</a> (<a class="el" href="na [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrDocEntry.html">AttrDocEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DominatorPattern.html">DominatorPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LRNAttrs.html">LRNAttrs</a> (<a class="el" href="namespa [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrDocVisitor.html">AttrDocVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DominatorPatternNode.html">DominatorPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LT.html">LT</a> (<a class="el" href="namespacet [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1AttrError.html">AttrError</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DropoutAttrs.html">DropoutAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LTNode.html">LTNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrExistVisitor.html">AttrExistVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1DurationNode.html">DurationNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_m"></a><table border="0" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AttachMap.html">AttachMap</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_1Dilation2DAttrs.html">Dilation2DAttrs</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_1LocalRunnerNode.html">LocalR [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1auto__scheduler_1_1AttachMapNode.html">AttachMapNode</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_1Div.html">Div</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoopRV.html">LoopRV</a> (<a class="el" href="namespacetvm_1_1ti [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrDocEntry.html">AttrDocEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1DivNode.html">DivNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LoopRVNode.html">LoopRVNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm: [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrDocVisitor.html">AttrDocVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DominatorPattern.html">DominatorPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1LRNAttrs.html">LRNAttrs</a> (<a class="el" href="nam [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1AttrError.html">AttrError</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1DominatorPatternNode.html">DominatorPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LT.html">LT</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>) &# [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrExistVisitor.html">AttrExistVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DropoutAttrs.html">DropoutAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1LTNode.html">LTNode</a> (<a class="el" href="namespacetvm_ [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrFieldInfo.html">AttrFieldInfo</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1DurationNode.html">DurationNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_m"></a><table border="0" cellspacing="0" cellpadding="0">< [...]
</td><td valign="top"><a class="el" href="classtvm_1_1RangeNode.html">RangeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1TempExpr.html">TempExpr</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td></tr>
-<tr><td valign="top"><a class="el" href="classtvm_1_1AttrFieldInfo.html">AttrFieldInfo</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DynExpandDimsAttrs.html">DynExpandDimsAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1Rebase.html">Rebase</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AttrFieldInfoNode.html">AttrFieldInfoNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_e"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  e  </div></td></tr></table>
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrFieldInfoNode.html">AttrFieldInfoNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1DynExpandDimsAttrs.html">DynExpandDimsAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1Rebase.html">Rebase</a> (<a class="el" href="namespacetvm_1_1te.html">tvm [...]
+<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 rowspan="2" valign="bottom"><a name="letter_e"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  e  </div></td></tr></table>
</td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1Map.html">Map</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1RebaseNode.html">RebaseNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1Tensor.html">Tensor</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)  & [...]
-<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="classtvm_1_1runtime_1_1MapNode.html">MapNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1RecClosure.html">RecClosure</a> (<a class="el" href="namespacetvm_ [...]
-<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="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_1relay_1_1Match.html">Match</a> (<a class="el" href="namespacetvm_1_1r [...]
-<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_1EnvFunc.html">EnvFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MatchBufferRegion.html">MatchBufferRegion</a> (<a class="el" href="namespacetvm_1_1t [...]
-<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_1EnvFuncNode.html">EnvFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MatchBufferRegionNode.html">MatchBufferRegionNode</a> (<a class="el" href="namespacetvm_1_1ti [...]
-<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_1EQ.html">EQ</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</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">tv [...]
-<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="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="structtvm_1_1relay_1_1MatmulAttrs.html">MatmulAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm: [...]
-<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="structtvm_1_1ErrorBuilder.html">ErrorBuilder</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html">MatrixSetDiagAttrs</a> (<a class="el" href="namespacetvm_1_1 [...]
-<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_1ErrorReporter.html">ErrorReporter</a> (<a class="el" href="namespacetvm.html">tvm</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</a>)   </td><td valign="top"> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AttrRegistryMap.html">AttrRegistryMap</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="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_1AttrRegistryMapContainerMap.html">AttrRegistryMapContainerMap</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EvaluateNode.html">EvaluateNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool1DAttrs.html">MaxPool1DAttrs</a> (<a class="el" href="namespa [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1Attrs.html">Attrs</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1Executable.html">Executable</a> (<a class="el" href="namespacetvm_1_1runtime_1_1vm.html">tvm::runtime::vm</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" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AttrsNode.html">AttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Executor.html">Executor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool3DAttrs.html">MaxPool3DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)&# [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrsSEqualVisitor.html">AttrsSEqualVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html">ExecutorNode</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_1MeasureCallback.html">MeasureCallback</a> (< [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrsSHashVisitor.html">AttrsSHashVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExecutorRegEntry.html">ExecutorRegEntry</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_1MeasureCallback.html">MeasureCallback [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AttrStmt.html">AttrStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ExpandDimsAttrs.html">ExpandDimsAttrs</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_1MeasureCallbackNode.html">MeasureCallbackNode</a> (<a class="el" h [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AttrStmtNode.html">AttrStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1tir_1_1ExprDeepEqual.html">ExprDeepEqual</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_1MeasureCallbackNode.html">MeasureCallbackNode</a> (<a class="el" hr [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry.html">AttrTriggerNonDefaultEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprFunctor.html">ExprFunctor</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_1MeasureCandidate.html">Measur [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1AttrVisitor.html">AttrVisitor</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprFunctor.html">ExprFunctor</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_1MeasureCandidateNode.html">MeasureCandidateNode</a> (<a class="el" href="namespacetvm_1_1meta_ [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AutoSchedulerLayoutTransformAttrs.html">AutoSchedulerLayoutTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprFunctor_3_01R_07const_01Expr_01_6n_00_01Args_8_8_8_08_4.html">ExprFunctor< R(const Expr &n, Args...)></a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool1DAttrs.html">AvgPool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html">ExprFunctor< R(const PrimExpr &n, Args...)></a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool2DAttrs.html">AvgPool2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprMutator.html">ExprMutator</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_1MeasureResult.html">MeasureResult</a> (<a class="el" hr [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool3DAttrs.html">AvgPool3DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprMutator.html">ExprMutator</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_1MeasureResultNode.html">MeasureResultNode</a> (<a class="el" [...]
+<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_1runtime_1_1MapNode.html">MapNode</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1RecClosure.html">RecClosure</a> (<a class="el" href="namespacet [...]
+<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="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_1relay_1_1Match.html">Match</a> (<a class="el" href="names [...]
+<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_1EnvFunc.html">EnvFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MatchBufferRegion.html">MatchBufferRegion</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir [...]
+<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_1EnvFuncNode.html">EnvFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MatchBufferRegionNode.html">MatchBufferRegionNode</a> (<a class="el" href="namespace [...]
+<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="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="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_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_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="structtvm_1_1relay_1_1MatmulAttrs.html">MatmulAttrs</a> (<a class="el" href="namespacetvm_1_1relay.ht [...]
+<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="structtvm_1_1ErrorBuilder.html">ErrorBuilder</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html">MatrixSetDiagAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>) [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrRegistryMap.html">AttrRegistryMap</a> (<a class="el" href="namespacetvm.html">tvm</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="classtvm_1_1tir_1_1Max.html">Max</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign= [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrRegistryMapContainerMap.html">AttrRegistryMapContainerMap</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="classtvm_1_1tir_1_1MaxNode.html">MaxNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::t [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1Attrs.html">Attrs</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1EvaluateNode.html">EvaluateNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool1DAttrs.html">MaxPool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>) &# [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrsNode.html">AttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1Executable.html">Executable</a> (<a class="el" href="namespacetvm_1_1runtime_1_1vm.html">tvm::runtime::vm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool2DAttrs.html">MaxPool2DAttrs</a> (<a class="el" href="namespacetvm_1_1rel [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrsSEqualVisitor.html">AttrsSEqualVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1Executor.html">Executor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MaxPool3DAttrs.html">MaxPool3DAttrs</a> (<a class="el" href= [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1detail_1_1AttrsSHashVisitor.html">AttrsSHashVisitor</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExecutorNode.html">ExecutorNode</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_1MeasureCallback.html">MeasureCallback</a> (<a [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AttrStmt.html">AttrStmt</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExecutorRegEntry.html">ExecutorRegEntry</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_1MeasureCallback.html">MeasureCallback</a> (<a class="el" href="n [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1AttrStmtNode.html">AttrStmtNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ExpandDimsAttrs.html">ExpandDimsAttrs</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_1MeasureCallbackNode.html">MeasureCallbackNode</a> (<a clas [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1detail_1_1AttrTriggerNonDefaultEntry.html">AttrTriggerNonDefaultEntry</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1tir_1_1ExprDeepEqual.html">ExprDeepEqual</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_1MeasureCallbackNode.html">Mea [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1AttrVisitor.html">AttrVisitor</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprFunctor.html">ExprFunctor</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_1MeasureCandidate.html">MeasureCandidate</a> (<a class="el" href="namespacetvm_1_1meta__s [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AutoSchedulerLayoutTransformAttrs.html">AutoSchedulerLayoutTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprFunctor.html">ExprFunctor</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_1MeasureCandidateNode.htm [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool1DAttrs.html">AvgPool1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprFunctor_3_01R_07const_01Expr_01_6n_00_01Args_8_8_8_08_4.html">ExprFunctor< R(const Expr &n, Args...)></a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href=" [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool2DAttrs.html">AvgPool2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprFunctor_3_01R_07const_01PrimExpr_01_6n_00_01Args_8_8_8_08_4.html">ExprFunctor< R(const PrimExpr &n, Args...)></a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1AvgPool3DAttrs.html">AvgPool3DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprMutator.html">ExprMutator</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_1MeasureResult.html">MeasureResult</a> (<a class="el" hr [...]
<tr><td rowspan="2" valign="bottom"><a name="letter_b"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  b  </div></td></tr></table>
-</td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprPattern.html">ExprPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1MemoryInfo.html">MemoryInfo</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1RelayExprNode.html">RelayExprNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </t [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprPatternNode.html">ExprPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1MemoryInfoNode.html">MemoryInfoNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1RelayNode.html">RelayNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm: [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseAttrsNode.html">BaseAttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html">ExprRewriter</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1MemoryManager.html">MemoryManager</a> (<a class="el" href="namespacetvm_1_1runtime_ [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1te_1_1BaseComputeOpNode.html">BaseComputeOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprVisitor.html">ExprVisitor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structMemoryManagerInterface.html">MemoryManagerInterface</a>   </td><td va [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseExpr.html">BaseExpr</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprVisitor.html">ExprVisitor</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MeshgridAttrs.html">MeshgridAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)  [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseExprNode.html">BaseExprNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1ExternOp.html">ExternOp</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1MetadataArray.html">MetadataArray</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.h [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseFunc.html">BaseFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1ExternOpNode.html">ExternOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1MetadataArrayNode.html">MetadataArrayNode</a> (<a class="el" href="namespacetvm_1_1runtime_1_1me [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseFuncNode.html">BaseFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ExtractedTask.html">ExtractedTask</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_1metadata_1_1MetadataBase.html">MetadataBase</a> (<a class="el" [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseTensorType.html">BaseTensorType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ExtractedTaskNode.html">ExtractedTaskNode</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_1metadata_1_1MetadataBaseNode.html">MetadataBaseNode [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseTensorTypeNode.html">BaseTensorTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1PackedFuncObj_1_1Extractor.html">PackedFuncObj::Extractor</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1MetaScheduleContext.html">MetaScheduleC [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseValueEqual.html">BaseValueEqual</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_f"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  f  </div></td></tr></table>
+</td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprMutator.html">ExprMutator</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_1MeasureResultNode.html">MeasureResultNode</a> (<a class="el" href="namespacetvm_1_1auto__scheduler.html">tvm::auto_scheduler</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1RelayExpr.html">RelayExpr</a> (<a class="el" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprPattern.html">ExprPattern</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1MemoryInfo.html">MemoryInfo</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1RelayExprNode.html">RelayExprNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseAttrsNode.html">BaseAttrsNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprPatternNode.html">ExprPatternNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1MemoryInfoNode.html">MemoryInfoNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)  [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1te_1_1BaseComputeOpNode.html">BaseComputeOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprRewriter.html">ExprRewriter</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1vm_1_1MemoryManager.html">MemoryManager</a> (<a class="el" href=" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseExpr.html">BaseExpr</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ExprVisitor.html">ExprVisitor</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structMemoryManagerInterface.html">MemoryManagerInterface</a>   </td><td valign="top"><a class="el" href="cla [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseExprNode.html">BaseExprNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ExprVisitor.html">ExprVisitor</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MeshgridAttrs.html">MeshgridAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseFunc.html">BaseFunc</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1ExternOp.html">ExternOp</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1MetadataArray.html">MetadataArray</a> (<a class="el" href="namespacetvm_1_1runtime_1_1metadata.html">tvm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseFuncNode.html">BaseFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1ExternOpNode.html">ExternOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1metadata_1_1MetadataArrayNode.html">MetadataArrayNode</a> (<a class="el" href="namespacetvm_1_1runti [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseTensorType.html">BaseTensorType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ExtractedTask.html">ExtractedTask</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_1metadata_1_1MetadataBase.html">MetadataBase</a> (<a class=" [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseTensorTypeNode.html">BaseTensorTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1ExtractedTaskNode.html">ExtractedTaskNode</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_1metadata_1_1MetadataBaseNode.html">Metadata [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseValueEqual.html">BaseValueEqual</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1PackedFuncObj_1_1Extractor.html">PackedFuncObj::Extractor</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1MetaScheduleContext.html">MetaScheduleContext</ [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1BaseValueHash.html">BaseValueHash</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_f"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  f  </div></td></tr></table>
</td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1MetaScheduleContextNode.html">MetaScheduleContextNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html">RequantizeAttrs</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_1me [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1BaseValueHash.html">BaseValueHash</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1MetricCollector.html">MetricCollector</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ReshapeAttrs.html">ReshapeAttrs</a> (<a c [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchMatmulAttrs.html">BatchMatmulAttrs</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_1FeatureExtractor.html">FeatureExtractor</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_1profiling_1_1MetricColl [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchNormAttrs.html">BatchNormAttrs</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_1FeatureExtractorNode.html">FeatureExtractorNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Min.html">Min</a> (<a c [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchToSpaceNDAttrs.html">BatchToSpaceNDAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1FeatureSet.html">FeatureSet</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MinNode.html">MinNode</a> (<a class="el" href="namespacetvm [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BiasAddAttrs.html">BiasAddAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1FIFOBufferAttrs.html">FIFOBufferAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MirrorPadAttrs.html">MirrorPadAttrs</a> (<a class="el" href [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BijectiveLayout.html">BijectiveLayout</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1FixedPointMultiplyAttrs.html">FixedPointMultiplyAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html">MixedModeMutator</a> ( [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BijectiveLayoutNode.html">BijectiveLayoutNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1SeqStmt_1_1Flattener.html">SeqStmt::Flattener</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1MixedModeVisitor.html">MixedModeVisitor</a> (<a clas [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BinaryConv2DAttrs.html">BinaryConv2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1FloatImm.html">FloatImm</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Mod.html">Mod</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)  &# [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BinaryDenseAttrs.html">BinaryDenseAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1FloatImmNode.html">FloatImmNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ModNode.html">ModNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>) [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BinaryOpNode.html">BinaryOpNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1FloorDiv.html">FloorDiv</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSet.html">ModularSet</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::ar [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BitPackAttrs.html">BitPackAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1FloorDivNode.html">FloorDivNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSetAnalyzer.html">ModularSetAnalyzer</a> (<a class="el" href="name [...]
-<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_1FloorMod.html">FloorMod</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSetNode.html">ModularSetNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</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_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_1runtime_1_1Module.html">Module</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::run [...]
-<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_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_1runtime_1_1ModuleNode.html">ModuleNode</a> ( [...]
-<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_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="classtvm_1_1tir_1_1Mul.html">Mul</a> (<a c [...]
-<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_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="classtvm_1_1tir_1_1MulNode.html">MulNode</a> (<a cla [...]
-<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_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="structtvm_1_1relay_1_1MultiBoxPriorAttrs.html">MultiBoxPriorAt [...]
-<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_1For.html">For</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html">MultiBoxTransformLocAttrs</a> (<a class="el" href="namespacetvm_1_1 [...]
-<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_1tir_1_1ForNode.html">ForNode</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_1Mutator.html">Mutator</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">t [...]
-<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_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_1MutatorNode.html"> [...]
-<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_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 rowspan="2" valign="bottom"><a name="letter_n"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class="ah">  [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchMatmulAttrs.html">BatchMatmulAttrs</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_1MetricCollector.html">MetricCollector</a> (<a class="el" href="namespacetvm_1_1runtime_1_1profiling.html">tvm::runtime::profiling</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ReshapeAt [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchNormAttrs.html">BatchNormAttrs</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_1FeatureExtractor.html">FeatureExtractor</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_1profiling_1_1MetricCollecto [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BatchToSpaceNDAttrs.html">BatchToSpaceNDAttrs</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_1FeatureExtractorNode.html">FeatureExtractorNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Min.html">Min [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BiasAddAttrs.html">BiasAddAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1FeatureSet.html">FeatureSet</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1MinNode.html">MinNode</a> (<a class="el" href="namespacetvm_1_1tir.html"> [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BijectiveLayout.html">BijectiveLayout</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1FIFOBufferAttrs.html">FIFOBufferAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1MirrorPadAttrs.html">MirrorPadAttrs</a> (<a class="el" href= [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BijectiveLayoutNode.html">BijectiveLayoutNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1FixedPointMultiplyAttrs.html">FixedPointMultiplyAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1MixedModeMutator.html">MixedModeMutat [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BinaryConv2DAttrs.html">BinaryConv2DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1SeqStmt_1_1Flattener.html">SeqStmt::Flattener</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1MixedModeVisitor.html">MixedModeVisitor</a> (<a c [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BinaryDenseAttrs.html">BinaryDenseAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1FloatImm.html">FloatImm</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Mod.html">Mod</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BinaryOpNode.html">BinaryOpNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1FloatImmNode.html">FloatImmNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1ModNode.html">ModNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1BitPackAttrs.html">BitPackAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1FloorDiv.html">FloorDiv</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSet.html">ModularSet</a> (<a class="el" href="namespacetvm_1_1arith.html"> [...]
+<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_1FloorDivNode.html">FloorDivNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSetAnalyzer.html">ModularSetAnalyzer</a> (<a class="el" href="namespacetvm_1_1arith.htm [...]
+<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_1tir_1_1FloorMod.html">FloorMod</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1ModularSetNode.html">ModularSetNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm: [...]
+<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_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_1runtime_1_1Module.html">Module</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runt [...]
+<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_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_1runtime_1_1ModuleNode.html">ModuleNode [...]
+<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_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="classtvm_1_1tir_1_1Mul.html">Mul</ [...]
+<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_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="classtvm_1_1tir_1_1MulNode.html">MulNode</a> (<a class="el" href="name [...]
+<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_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="structtvm_1_1relay_1_1MultiBoxPriorAttrs.html">MultiBo [...]
+<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_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="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html">MultiBoxTransformLocAttrs</a> (<a class="el" href="namespacetvm_1_1re [...]
+<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_1tir_1_1ForNode.html">ForNode</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_1Mutator.html">Mutator</a> (<a class="el" href="namespacetvm_1_1meta__schedule [...]
+<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_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_1MutatorNode.html">MutatorNode</a> (<a class="el" href="na [...]
+<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_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 rowspan="2" valign="bottom"><a name="letter_n"></a><table border="0" cellspacing="0" cellpadding="0"> [...]
</td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1RunnerInputNode.html">RunnerInputNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="structTVMMetadata.html">TVMMetadata</a>   </td></tr>
-<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="classtvm_1_1meta__schedule_1_1RunnerNode.html">RunnerNode</a> (<a class=" [...]
+<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_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="classtvm_1_1meta__schedule_1_1RunnerN [...]
<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_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="classtvm_1_1runtime_1_1NDArray.html">NDArray</a> (<a class="el" href="nam [...]
<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_1Function.html">Function</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1NDArrayContainerTrait.html">NDArrayContainerTrait</a> (<a class="el" href [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1Buffer.html">Buffer</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="structtvm_1_1relay_1_1NdarraySizeAttrs.html">NdarraySizeAttrs</a> (<a class="el" href="namespacetvm_1_1rela [...]
@@ -202,10 +203,10 @@ $(function() {
</td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1NotNode.html">NotNode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ScatterAttrs.html">ScatterAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1TypeCall.html">TypeCall</a> (<a class="el" href="namespacetvm.html">tvm</a>)   [...]
<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_1runtime_1_1NullOptType.html">NullOptType</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ScatterNDAttrs.html">ScatterNDAttrs</a> (<a class="el" href="namespa [...]
<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="structtvm_1_1relay_1_1GatherAttrs.html">GatherAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td rowspan="2" valign="bottom"><a name="letter_o"></a><table border="0" cellspacing="0" cellpadding="0"><tr><td><div class=" [...]
-</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_1TypeConstraint.html">TypeConstraint</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
-<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="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_1tir_1_1Schedule.html">Schedule</a> (<a class="el" href="namespacetvm_1_1tir.html"> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferStoreNode.html">BufferStoreNode</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="classtvm_1_1runtime_1_1ObjAllocatorBase.html">ObjAllocatorBase</a> (<a class="el" href="namespacetvm_1_1runtime.htm [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1Builder.html">Builder</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</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="classtvm_1_1runtime_1_1Object.html">Object</a> (<a class="el" href="namespacetvm_1_1runtime.html">tv [...]
+</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_1TypeConstraint.html">TypeConstraint</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td></tr>
+<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="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_1te_1_1Schedule.html">Schedule</a> (<a class="el" href="namespacetvm_1_1te.html">tv [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1tir_1_1BufferStoreNode.html">BufferStoreNode</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="classtvm_1_1runtime_1_1ObjAllocatorBase.html">ObjAllocatorBase</a> (<a class="el" href="namespacetvm_1_1runtime.htm [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1Builder.html">Builder</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</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="classtvm_1_1runtime_1_1Object.html">Object</a> (<a class="el" href="namespacetvm_1_1runtime.html">tv [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1BuilderInput.html">BuilderInput</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1GenericFuncNode.html">GenericFuncNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1ObjectEqual.html">ObjectEqual</a> (<a class="el" href="nam [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1BuilderInputNode.html">BuilderInputNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1tir_1_1GENode.html">GENode</a> (<a class="el" href="namespacetvm_1_1tir.html">tvm::tir</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1ObjectHash.html">ObjectHash</a> (<a class="el" hr [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1BuilderNode.html">BuilderNode</a> (<a class="el" href="namespacetvm_1_1meta__schedule.html">tvm::meta_schedule</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1relay_1_1GetValidCountsAttrs.html">GetValidCountsAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1ObjectPtr.html">ObjectPtr</ [...]
@@ -250,11 +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_1ImplSEqualReduce_3_01T_00_01true_01_4.html">ImplSEqualReduce< T, true ></a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1PackedFuncValueConvert [...]
<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_1ImplSHashReduce.html">ImplSHashReduce</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1runtime_1_1PackedFuncValueConverter_3_1_1tvm_1_1runtime_1_1String_01_4.html">PackedFuncValu [...]
<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_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_1runtime_1_1micro__rpc_1_1P [...]
-<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="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="structtvm_1_1relay_1_1PadAttrs.html">PadAttrs</a> [...]
-<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="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="clas [...]
+<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="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="structtvm_1_1relay_1_1PadAttrs.html">PadAttrs</a> [...]
+<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="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="clas [...]
<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_1IncompleteType.html">IncompleteType</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassContext.html">PassContext</a> (<a class="el" href="names [...]
-<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_1IncompleteTypeNode.html">IncompleteTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassContextNode.html">PassContextNode</a> (< [...]
-<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="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_1transform_1_1PassInfo.html">PassInfo</a> (<a class=" [...]
+<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_1IncompleteTypeNode.html">IncompleteTypeNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1transform_1_1PassContextNode.html">PassContextNode</a> (< [...]
+<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="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_1transform_1_1PassInfo.html">PassInfo</a> (<a class=" [...]
<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_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_1transform_1_1PassInfoNode.html">Pass [...]
<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_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_1instrument_1_1PassInstrument.html">PassInstrument</a> (<a class="el" href="namespacetvm_1_1in [...]
<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="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_1instrument_1_1PassInstrumentNode.html">PassInstrumentNode</a> (<a clas [...]
@@ -273,8 +274,8 @@ $(function() {
<tr><td valign="top"><a class="el" href="classtvm_1_1Constructor.html">Constructor</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1Integer.html">Integer</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternVarNode.html">PatternVarNode</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1ConstructorNode.html">ConstructorNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1InterpreterClosure.html">InterpreterClosure</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternVisitor.html">PatternVisitor</a> (<a class="el" href="namespacetvm_1 [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1relay_1_1ConstructorValue.html">ConstructorValue</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1InterpreterClosureObj.html">InterpreterClosureObj</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternWildcard.html">PatternWildcard</a> [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ConstructorValueObj.html">ConstructorValueObj</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IntGroupBounds.html">IntGroupBounds</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternWildcardNode.html">PatternWildcardNode</a> [...]
-<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1NDArray_1_1Container.html">NDArray::Container</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IntGroupBoundsNode.html">IntGroupBoundsNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1PercentNode.html">Per [...]
+<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1ConstructorValueObj.html">ConstructorValueObj</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IntGroupBounds.html">IntGroupBounds</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1relay_1_1PatternWildcardNode.html">PatternWildcardNode</a> [...]
+<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1NDArray_1_1Container.html">NDArray::Container</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IntGroupBoundsNode.html">IntGroupBoundsNode</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1profiling_1_1PercentNode.html">Per [...]
<tr><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1NDArray_1_1ContainerBase.html">NDArray::ContainerBase</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IntImm.html">IntImm</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1PlaceholderOp.html">PlaceholderOp</a> (<a class="el" href="namespacetvm_1_1te.ht [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv1DAttrs.html">Conv1DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IntImmNode.html">IntImmNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1te_1_1PlaceholderOpNode.html">PlaceholderOpNode</a> (<a class="el" href="namespacetvm_1_1te.html">tvm::te</ [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv1DTransposeAttrs.html">Conv1DTransposeAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1arith_1_1IntSet.html">IntSet</a> (<a class="el" href="namespacetvm_1_1arith.html">tvm::arith</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1PointerType.html">PointerType</a> (<a class="el" href="namespacetvm.html [...]
@@ -285,7 +286,6 @@ $(function() {
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv2DWinogradNNPACKWeightTransformAttrs.html">Conv2DWinogradNNPACKWeightTransformAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1IRModuleNode.html">IRModuleNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1PoolInfo.html">PoolInfo</a> (<a class="el" hr [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv3DAttrs.html">Conv3DAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1detail_1_1is__specialized.html">is_specialized</a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1PoolInfoNode.html">PoolInfoNode</a> (<a class="el" href="namespacetv [...]
<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv3DTransposeAttrs.html">Conv3DTransposeAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="structtvm_1_1detail_1_1is__specialized_3_01Container_3_01Args_8_8_8_01_4_00_01Container_01_4.html">is_specialized< Container< Args... >, Container ></a> (<a class="el" href="namespacetvm_1_1detail.html">tvm::detail</a>)   </td [...]
-<tr><td valign="top"><a class="el" href="structtvm_1_1relay_1_1Conv3DWinogradAttrs.html">Conv3DWinogradAttrs</a> (<a class="el" href="namespacetvm_1_1relay.html">tvm::relay</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1runtime_1_1IterAdapter.html">IterAdapter</a> (<a class="el" href="namespacetvm_1_1runtime.html">tvm::runtime</a>)   </td><td valign="top"><a class="el" href="classtvm_1_1meta__schedule_1_1PostprocNode.html">PostprocNode</a> (<a [...]
<tr><td></td><td></td><td></td><td></td><td></td></tr>
</table>
<div class="qindex"><a class="qindex" href="#letter_a">a</a> | <a class="qindex" href="#letter_b">b</a> | <a class="qindex" href="#letter_c">c</a> | <a class="qindex" href="#letter_d">d</a> | <a class="qindex" href="#letter_e">e</a> | <a class="qindex" href="#letter_f">f</a> | <a class="qindex" href="#letter_g">g</a> | <a class="qindex" href="#letter_h">h</a> | <a class="qindex" href="#letter_i">i</a> |& [...]
diff --git a/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode.html b/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode.html
index 83439e1b3..465763329 100644
--- a/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode.html
+++ b/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode.html
@@ -79,7 +79,7 @@ $(function() {
<p>Inherits <a class="el" href="classtvm_1_1runtime_1_1Object.html">tvm::runtime::Object</a>.</p>
-<p>Inherited by <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool1DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool2DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool3DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AffineGridAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AllClassNonMaximumSuppres [...]
+<p>Inherited by <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool1DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool2DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AdaptivePool3DAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AffineGridAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html">tvm::AttrsNode< AllClassNonMaximumSuppres [...]
<div class="dynheader">
Collaboration diagram for tvm::BaseAttrsNode:</div>
<div class="dyncontent">
@@ -318,7 +318,7 @@ Additional Inherited Members</h2></td></tr>
</dl>
<dl class="section note"><dt>Note</dt><dd>This function throws when the required field is not present. </dd></dl>
-<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532 [...]
+<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532559a">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acfba199ef906818f35432d2e5532 [...]
</div>
</div>
@@ -384,7 +384,7 @@ template<typename... Args> </div>
<p>Get the field information. </p>
<dl class="section return"><dt>Returns</dt><dd>The fields in the <a class="el" href="classtvm_1_1Attrs.html" title="Managed reference to BaseAttrsNode. ">Attrs</a>. </dd></dl>
-<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6 [...]
+<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6a981">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acefe615381b5d881870af9db7ce6 [...]
</div>
</div>
@@ -474,7 +474,7 @@ template<typename... Args> </div>
</table>
</div><div class="memdoc">
-<p>Reimplemented in <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a3 [...]
+<p>Reimplemented in <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a34a9c72">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#a5da687ced06b4f2dfa04b142a3 [...]
</div>
</div>
@@ -511,7 +511,7 @@ template<typename... Args> </div>
</dd>
</dl>
-<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da88 [...]
+<p>Implemented in <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< DerivedType ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< DilateAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da885205">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a>, <a class="el" href="classtvm_1_1AttrsNode.html#acd05137ba529ac7cd07053e3da88 [...]
</div>
</div>
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index 1502b0fbc..4cf38b603 100644
--- a/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode__coll__graph.svg
+++ b/docs/reference/api/doxygen/classtvm_1_1BaseAttrsNode__coll__graph.svg
@@ -9,9 +9,9 @@
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<title>tvm::BaseAttrsNode</title>
<polygon fill="#ffffff" stroke="transparent" points="-4,4 -4,-608 269,-608 269,4 -4,4"/>
-<!-- Node270 -->
+<!-- Node272 -->
<g id="node1" class="node">
-<title>Node270</title>
+<title>Node272</title>
<polygon fill="#bfbfbf" stroke="#000000" points="0,-.5 0,-178.5 207,-178.5 207,-.5 0,-.5"/>
<text text-anchor="middle" x="103.5" y="-166.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::BaseAttrsNode</text>
<polyline fill="none" stroke="#000000" points="0,-159.5 207,-159.5 "/>
@@ -30,9 +30,9 @@
<text text-anchor="start" x="8" y="-18.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">+ InitByPackedArgs()</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>
</g>
-<!-- Node271 -->
+<!-- Node273 -->
<g id="node2" class="node">
-<title>Node271</title>
+<title>Node273</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="12,-216.5 12,-603.5 195,-603.5 195,-216.5 12,-216.5"/>
<text text-anchor="middle" x="103.5" y="-591.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
@@ -73,15 +73,15 @@
</a>
</g>
</g>
-<!-- Node271->Node270 -->
+<!-- Node273->Node272 -->
<g id="edge1" class="edge">
-<title>Node271->Node270</title>
+<title>Node273->Node272</title>
<path fill="none" stroke="#191970" d="M103.5,-205.9464C103.5,-196.5963 103.5,-187.4618 103.5,-178.684"/>
<polygon fill="none" stroke="#191970" points="100.0001,-206.1701 103.5,-216.1701 107.0001,-206.1701 100.0001,-206.1701"/>
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-<!-- Node271->Node271 -->
+<!-- Node273->Node273 -->
<g id="edge2" class="edge">
-<title>Node271->Node271</title>
+<title>Node273->Node273</title>
<path fill="none" stroke="#404040" d="M195.3625,-443.9248C206.0482,-437.6637 213,-426.3555 213,-410 213,-399.0112 209.8618,-390.3007 204.5615,-383.8687"/>
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<text text-anchor="middle" x="239" y="-407.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
diff --git a/docs/reference/api/doxygen/classtvm_1_1runtime_1_1Object__coll__graph.svg b/docs/reference/api/doxygen/classtvm_1_1runtime_1_1Object__coll__graph.svg
index 720280aaf..132323f4c 100644
--- a/docs/reference/api/doxygen/classtvm_1_1runtime_1_1Object__coll__graph.svg
+++ b/docs/reference/api/doxygen/classtvm_1_1runtime_1_1Object__coll__graph.svg
@@ -9,9 +9,9 @@
<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 392)">
<title>tvm::runtime::Object</title>
<polygon fill="#ffffff" stroke="transparent" points="-4,4 -4,-392 257,-392 257,4 -4,4"/>
-<!-- Node604 -->
+<!-- Node606 -->
<g id="node1" class="node">
-<title>Node604</title>
+<title>Node606</title>
<polygon fill="#bfbfbf" stroke="#000000" points="0,-.5 0,-387.5 183,-387.5 183,-.5 0,-.5"/>
<text text-anchor="middle" x="91.5" y="-375.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::Object</text>
<polyline fill="none" stroke="#000000" points="0,-368.5 183,-368.5 "/>
@@ -49,9 +49,9 @@
<text text-anchor="start" x="8" y="-18.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># DecRef()</text>
<text text-anchor="start" x="8" y="-7.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"># GetOrAllocRuntimeTypeIndex()</text>
</g>
-<!-- Node604->Node604 -->
+<!-- Node606->Node606 -->
<g id="edge1" class="edge">
-<title>Node604->Node604</title>
+<title>Node606->Node606</title>
<path fill="none" stroke="#404040" d="M183.3625,-256.0888C194.0482,-244.6299 201,-223.9336 201,-194 201,-171.3159 197.0077,-153.9367 190.4236,-141.8623"/>
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<text text-anchor="middle" x="227" y="-191.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000"> #deleter_</text>
diff --git a/docs/reference/api/doxygen/functions_func_s.html b/docs/reference/api/doxygen/functions_func_s.html
index 7173eec4e..9ad9dc079 100644
--- a/docs/reference/api/doxygen/functions_func_s.html
+++ b/docs/reference/api/doxygen/functions_func_s.html
@@ -688,7 +688,7 @@ $(function() {
: <a class="el" href="classtvm_1_1tir_1_1ScheduleNode.html#a93d1d23f24d903db844f75f51fe09a36">tvm::tir::ScheduleNode</a>
</li>
<li>StorageAlignStep()
-: <a class="el" href="classtvm_1_1auto__scheduler_1_1StorageAlignStep.html#a99dbb8c55d9e7d78268b6d43fd348bc7">tvm::auto_scheduler::StorageAlignStep</a>
+: <a class="el" href="classtvm_1_1auto__scheduler_1_1StorageAlignStep.html#af50b7c2f020f8e0a80f5bcc8e559b394">tvm::auto_scheduler::StorageAlignStep</a>
</li>
<li>Store()
: <a class="el" href="classtvm_1_1tir_1_1Store.html#a2c4278b8bcdae57ada2022ecc7c290c3">tvm::tir::Store</a>
@@ -700,7 +700,7 @@ $(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#a68df7bab89fca339e3918438dd80300d">tvm::runtime::String</a>
+: <a class="el" href="classtvm_1_1runtime_1_1String.html#ac5d930b522e9fef9c07e51819d96d2f3">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 124ef0493..88be4c70c 100644
--- a/docs/reference/api/doxygen/functions_func_t.html
+++ b/docs/reference/api/doxygen/functions_func_t.html
@@ -300,6 +300,7 @@ $(function() {
, <a class="el" href="structtvm_1_1relay_1_1PadAttrs.html#aac1b66ac003e46b63c82930ebc9518e3">tvm::relay::PadAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1PReluAttrs.html#afb126b8cbdd8afad374eda19a71d7974">tvm::relay::PReluAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1ProposalAttrs.html#a9b385afc760a6a37cdbd51440452c2bb">tvm::relay::ProposalAttrs</a>
+, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#a711a295ff4a6374d94dbaf37012597c0">tvm::relay::qnn::BroadcastAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html#a9d8b66b3a7938fc2bed13e3eb574ad29">tvm::relay::qnn::DequantizeAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html#a34a809fceea00d2c7640eceb98e389c2">tvm::relay::qnn::QuantizeAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html#afe0c71d143221032933f707078ea09ba">tvm::relay::qnn::RequantizeAttrs</a>
@@ -991,7 +992,7 @@ $(function() {
: <a class="el" href="classtvm_1_1runtime_1_1TVMMovableArgValueWithContext__.html#adf0eff794c9dd05da7e61c03b03f6bc7">tvm::runtime::TVMMovableArgValueWithContext_</a>
</li>
<li>TVMPODValue_()
-: <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#afe1837bdbafe8341c2031c5cebcf6e74">tvm::runtime::TVMPODValue_</a>
+: <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#a2f46b59a6c1d5eb4575d7f583b5f1a0c">tvm::runtime::TVMPODValue_</a>
</li>
<li>TVMRetValue()
: <a class="el" href="classtvm_1_1runtime_1_1TVMRetValue.html#ab86bf21f214fca72e73a7f6e20ffab8d">tvm::runtime::TVMRetValue</a>
@@ -1020,10 +1021,10 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeData.html#a0a98fd1095812379d2bd1337db1511c1">tvm::TypeData</a>
</li>
<li>TypedEnvFunc()
-: <a class="el" href="classtvm_1_1TypedEnvFunc_3_01R_07Args_8_8_8_08_4.html#a0d72a6fa7263821c14bcd37837998ed9">tvm::TypedEnvFunc< R(Args...)></a>
+: <a class="el" href="classtvm_1_1TypedEnvFunc_3_01R_07Args_8_8_8_08_4.html#a41a6b9014d0feeb628ca7edfd0d26f0b">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#aa3663a440db7a6951abd767109b9bf90">tvm::runtime::TypedPackedFunc< R(Args...)></a>
+: <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#a4abadc6786dd14a3aed6e2b5b342d1d6">tvm::runtime::TypedPackedFunc< R(Args...)></a>
</li>
<li>TypeIndex2Key()
: <a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">tvm::runtime::Object</a>
diff --git a/docs/reference/api/doxygen/functions_i.html b/docs/reference/api/doxygen/functions_i.html
index 867bfdf0d..9915eb3f1 100644
--- a/docs/reference/api/doxygen/functions_i.html
+++ b/docs/reference/api/doxygen/functions_i.html
@@ -554,7 +554,7 @@ $(function() {
<li>iterator
: <a class="el" href="classtvm_1_1runtime_1_1Array.html#a98e5ad633b8195d954c98067213ae29f">tvm::runtime::Array< T, typename ></a>
, <a class="el" href="classtvm_1_1runtime_1_1Map_1_1iterator.html#ad8b40ddeffccb6f221601eda70202f9a">tvm::runtime::Map< K, V, typename, typename >::iterator</a>
-, <a class="el" href="classtvm_1_1runtime_1_1MapNode_1_1iterator.html#a75e3f2657cdb7cc613bf922429983165">tvm::runtime::MapNode::iterator</a>
+, <a class="el" href="classtvm_1_1runtime_1_1MapNode_1_1iterator.html#ad605c9f9aaed23e669c2a3c595d08ba4">tvm::runtime::MapNode::iterator</a>
, <a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor.html#a79703afd52032715cc2d9d4c6830147f">tvm::runtime::metadata::ArrayAccessor< C, Ref ></a>
, <a class="el" href="classtvm_1_1runtime_1_1metadata_1_1ArrayAccessor_3_01const_01char_01_5_00_01_1_1tvm_1_1runtime_1_1String_01_4.html#a3216d91ef7fb0771463e76c9a0afcd1c">tvm::runtime::metadata::ArrayAccessor< const char *, ::tvm::runtime::String ></a>
, <a class="el" href="classtvm_1_1support_1_1Span.html#af6fbb6a54a3ecf8673146acae0c8228b">tvm::support::Span< T, W ></a>
@@ -584,7 +584,7 @@ $(function() {
: <a class="el" href="classtvm_1_1tir_1_1IterVar.html#a1c0d6998203092c953b7da00f16c5c31">tvm::tir::IterVar</a>
</li>
<li>IterVarAttr()
-: <a class="el" href="classtvm_1_1te_1_1IterVarAttr.html#aa20680587a1c880b659063cd37ba4763">tvm::te::IterVarAttr</a>
+: <a class="el" href="classtvm_1_1te_1_1IterVarAttr.html#a5549479b7e3ce243d89b219b0dd7ef71">tvm::te::IterVarAttr</a>
</li>
<li>IterVarRelation()
: <a class="el" href="classtvm_1_1te_1_1IterVarRelation.html#a3e611ee0870d9a542b8deb79575dbf66">tvm::te::IterVarRelation</a>
diff --git a/docs/reference/api/doxygen/functions_l.html b/docs/reference/api/doxygen/functions_l.html
index 2938fe832..13f61f0ae 100644
--- a/docs/reference/api/doxygen/functions_l.html
+++ b/docs/reference/api/doxygen/functions_l.html
@@ -143,6 +143,9 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1ClauseNode.html#a85479b56eab2bb3255248a8b0fcd23f8">tvm::relay::ClauseNode</a>
, <a class="el" href="classtvm_1_1tir_1_1CommReducerNode.html#a3fc76ed5cf3a73c803ce1c74dedf7429">tvm::tir::CommReducerNode</a>
</li>
+<li>lhs_axis
+: <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#a73378c316806d3f78a3fa0fb27178ad3">tvm::relay::qnn::BroadcastAttrs</a>
+</li>
<li>lhs_begin
: <a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html#ab858f0ecef7ac56b1f9d69b57eb6f3c8">tvm::relay::ReshapeLikeAttrs</a>
</li>
@@ -243,7 +246,7 @@ $(function() {
: <a class="el" href="classtvm_1_1IRModuleNode.html#ae078ad8def39579701d144578c787bcf">tvm::IRModuleNode</a>
</li>
<li>LookupTypeDef()
-: <a class="el" href="classtvm_1_1IRModuleNode.html#ae095c1fd87642bd417224668c5b4d910">tvm::IRModuleNode</a>
+: <a class="el" href="classtvm_1_1IRModuleNode.html#a23f3769fe60b3b06c9d163650ea7caaf">tvm::IRModuleNode</a>
</li>
<li>loop_var
: <a class="el" href="classtvm_1_1tir_1_1ForNode.html#a7dbf66bdcf8ed397321517f0915a0946">tvm::tir::ForNode</a>
diff --git a/docs/reference/api/doxygen/functions_r.html b/docs/reference/api/doxygen/functions_r.html
index f8286a907..385a8d51a 100644
--- a/docs/reference/api/doxygen/functions_r.html
+++ b/docs/reference/api/doxygen/functions_r.html
@@ -489,6 +489,9 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1ClauseNode.html#a93217eeea15c1f7c1a659da3da86d3bd">tvm::relay::ClauseNode</a>
, <a class="el" href="classtvm_1_1tir_1_1CommReducerNode.html#a2902b0d55dd823febc6941fae9f32337">tvm::tir::CommReducerNode</a>
</li>
+<li>rhs_axis
+: <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#afd0dadf19b60022c3c8cc0b0f9b6c27a">tvm::relay::qnn::BroadcastAttrs</a>
+</li>
<li>rhs_begin
: <a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html#a8f25936511569c3ea754e9d065ccff81">tvm::relay::ReshapeLikeAttrs</a>
</li>
diff --git a/docs/reference/api/doxygen/functions_s.html b/docs/reference/api/doxygen/functions_s.html
index ea0727835..6305996cb 100644
--- a/docs/reference/api/doxygen/functions_s.html
+++ b/docs/reference/api/doxygen/functions_s.html
@@ -782,7 +782,7 @@ $(function() {
, <a class="el" href="classtvm_1_1SpanNode.html#ad573167f93facbfbee19983b08bbba3d">tvm::SpanNode</a>
</li>
<li>SourceMap()
-: <a class="el" href="classtvm_1_1parser_1_1SourceMap.html#afc48463cc0967ab79876178613a5aff2">tvm::parser::SourceMap</a>
+: <a class="el" href="classtvm_1_1parser_1_1SourceMap.html#a5fd3cc7160f57f7adcf1a0633603c72e">tvm::parser::SourceMap</a>
</li>
<li>space_generator
: <a class="el" href="classtvm_1_1meta__schedule_1_1TuneContextNode.html#a7bdfdd48530bfe380c5f6c143158a07f">tvm::meta_schedule::TuneContextNode</a>
@@ -804,7 +804,7 @@ $(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>span
: <a class="el" href="classtvm_1_1tir_1_1BufferNode.html#a13fc164e1b65cee741b4895df6316a4a">tvm::tir::BufferNode</a>
@@ -877,8 +877,8 @@ $(function() {
: <a class="el" href="structtvm_1_1relay_1_1DeviceCopyAttrs.html#aac5b2c76325a587bbefaa5af87b4138f">tvm::relay::DeviceCopyAttrs</a>
</li>
<li>Stage()
-: <a class="el" href="classtvm_1_1auto__scheduler_1_1Stage.html#a39ffbb1b4e189180bc4067e74965f42b">tvm::auto_scheduler::Stage</a>
-, <a class="el" href="classtvm_1_1te_1_1Stage.html#a1ecdc9a000be62c9cc26a96d4c33e36e">tvm::te::Stage</a>
+: <a class="el" href="classtvm_1_1auto__scheduler_1_1Stage.html#af0643fe8c1298451c9a322f915c48843">tvm::auto_scheduler::Stage</a>
+, <a class="el" href="classtvm_1_1te_1_1Stage.html#aa6ace38b6312e42aaf9389c8749ae0a4">tvm::te::Stage</a>
</li>
<li>stage_id
: <a class="el" href="classtvm_1_1auto__scheduler_1_1StepNode.html#afcc7aaf263348f66139307affbfcee09">tvm::auto_scheduler::StepNode</a>
@@ -1046,7 +1046,7 @@ $(function() {
, <a class="el" href="classtvm_1_1tir_1_1BufferNode.html#ac18ddd10b79a30ae57d3a8283686259d">tvm::tir::BufferNode</a>
</li>
<li>String()
-: <a class="el" href="classtvm_1_1runtime_1_1String.html#acf549b3c43142639879e0fc31ea5cd77">tvm::runtime::String</a>
+: <a class="el" href="classtvm_1_1runtime_1_1String.html#a02fca36e3ff55cc1e83635b02a11fca3">tvm::runtime::String</a>
, <a class="el" href="classtvm_1_1runtime_1_1StringObj_1_1FromStd.html#a7fb804f7dc96dd9f705c84095f37f1ca">tvm::runtime::StringObj::FromStd</a>
, <a class="el" href="classtvm_1_1runtime_1_1StringObj.html#a7fb804f7dc96dd9f705c84095f37f1ca">tvm::runtime::StringObj</a>
</li>
diff --git a/docs/reference/api/doxygen/functions_t.html b/docs/reference/api/doxygen/functions_t.html
index c26078dfb..e971389b8 100644
--- a/docs/reference/api/doxygen/functions_t.html
+++ b/docs/reference/api/doxygen/functions_t.html
@@ -482,6 +482,7 @@ $(function() {
, <a class="el" href="structtvm_1_1relay_1_1PadAttrs.html#aac1b66ac003e46b63c82930ebc9518e3">tvm::relay::PadAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1PReluAttrs.html#afb126b8cbdd8afad374eda19a71d7974">tvm::relay::PReluAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1ProposalAttrs.html#a9b385afc760a6a37cdbd51440452c2bb">tvm::relay::ProposalAttrs</a>
+, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#a711a295ff4a6374d94dbaf37012597c0">tvm::relay::qnn::BroadcastAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html#a9d8b66b3a7938fc2bed13e3eb574ad29">tvm::relay::qnn::DequantizeAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html#a34a809fceea00d2c7640eceb98e389c2">tvm::relay::qnn::QuantizeAttrs</a>
, <a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html#afe0c71d143221032933f707078ea09ba">tvm::relay::qnn::RequantizeAttrs</a>
@@ -1170,7 +1171,7 @@ $(function() {
</li>
<li>TVMArgValue
: <a class="el" href="classtvm_1_1runtime_1_1ObjectPtr.html#a7e8b2c6a4fde079ee813c425d2eb6b24">tvm::runtime::ObjectPtr< T ></a>
-, <a class="el" href="classtvm_1_1runtime_1_1TVMArgValue.html#a5fbd71750e5bbba6edc9094178af9276">tvm::runtime::TVMArgValue</a>
+, <a class="el" href="classtvm_1_1runtime_1_1TVMArgValue.html#a987b2fb283cea5484d4655e3f711c046">tvm::runtime::TVMArgValue</a>
</li>
<li>TVMMovableArgValue_
: <a class="el" href="classtvm_1_1runtime_1_1ObjectPtr.html#acd985550cba6cf8509122cbd996c1557">tvm::runtime::ObjectPtr< T ></a>
@@ -1183,7 +1184,7 @@ $(function() {
<li>TVMPODValue_
: <a class="el" href="classtvm_1_1runtime_1_1NDArray.html#a9a9fd94393cfd7d4b6e6029348e3e19a">tvm::runtime::NDArray</a>
, <a class="el" href="classtvm_1_1runtime_1_1ObjectPtr.html#a9a9fd94393cfd7d4b6e6029348e3e19a">tvm::runtime::ObjectPtr< T ></a>
-, <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#afe1837bdbafe8341c2031c5cebcf6e74">tvm::runtime::TVMPODValue_</a>
+, <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#a2f46b59a6c1d5eb4575d7f583b5f1a0c">tvm::runtime::TVMPODValue_</a>
</li>
<li>TVMRetValue
: <a class="el" href="classtvm_1_1BaseAttrsNode.html#a1f56f080d0c1fab79d9469029aef8ebb">tvm::BaseAttrsNode</a>
@@ -1192,7 +1193,7 @@ $(function() {
, <a class="el" href="classtvm_1_1runtime_1_1ObjectPtr.html#ae0ea8b4adc6dab8c74086bceaef6b3e1">tvm::runtime::ObjectPtr< T ></a>
, <a class="el" href="classtvm_1_1runtime_1_1ObjectRef.html#ae0ea8b4adc6dab8c74086bceaef6b3e1">tvm::runtime::ObjectRef</a>
, <a class="el" href="classtvm_1_1runtime_1_1TVMPODValue__.html#ae0ea8b4adc6dab8c74086bceaef6b3e1">tvm::runtime::TVMPODValue_</a>
-, <a class="el" href="classtvm_1_1runtime_1_1TVMRetValue.html#ac4a3850c0989e7c2d5cd8e0f096d0997">tvm::runtime::TVMRetValue</a>
+, <a class="el" href="classtvm_1_1runtime_1_1TVMRetValue.html#a77455a8fe7d27b90a01a64f1cd28e9ec">tvm::runtime::TVMRetValue</a>
, <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#ae0ea8b4adc6dab8c74086bceaef6b3e1">tvm::runtime::TypedPackedFunc< R(Args...)></a>
</li>
<li>type
@@ -1264,7 +1265,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypedEnvFunc_3_01R_07Args_8_8_8_08_4.html#a41a6b9014d0feeb628ca7edfd0d26f0b">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#a8941c80982a1b2a289440f3c79bb0ac8">tvm::runtime::TypedPackedFunc< R(Args...)></a>
+: <a class="el" href="classtvm_1_1runtime_1_1TypedPackedFunc_3_01R_07Args_8_8_8_08_4.html#af45a2ceff92e6f6c394ea766a45027a0">tvm::runtime::TypedPackedFunc< R(Args...)></a>
</li>
<li>TypeIndex2Key()
: <a class="el" href="classtvm_1_1runtime_1_1Object.html#a817ba6c23b7ee1821c48a75edf255a30">tvm::runtime::Object</a>
@@ -1287,7 +1288,7 @@ $(function() {
: <a class="el" href="classtvm_1_1TypeRelation.html#ac26b1897eab8197ed26606ab81b7403b">tvm::TypeRelation</a>
</li>
<li>TypeReporter()
-: <a class="el" href="classtvm_1_1TypeReporter.html#aa3dc38a3c84d324d0b3a9f358460a091">tvm::TypeReporter</a>
+: <a class="el" href="classtvm_1_1TypeReporter.html#a8e7e05a07f9f7ad9bea91f27afac9051">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_v.html b/docs/reference/api/doxygen/functions_v.html
index 0c03d69b1..a72753763 100644
--- a/docs/reference/api/doxygen/functions_v.html
+++ b/docs/reference/api/doxygen/functions_v.html
@@ -565,9 +565,9 @@ $(function() {
, <a class="el" href="classtvm_1_1TypeMutator.html#a84e824911927d98e20a338eab8b75a45">tvm::TypeMutator</a>
</li>
<li>VisitType_()
-: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#ac94cab8aea5c2a9afb439d7417f30a20">tvm::TypeFunctor< R(const Type &n, Args...)></a>
-, <a class="el" href="classtvm_1_1TypeMutator.html#a89bd7a76f5a736defc7f3b0dda664761">tvm::TypeMutator</a>
-, <a class="el" href="classtvm_1_1TypeVisitor.html#a292b19b578526ea74b1434dc50514a18">tvm::TypeVisitor</a>
+: <a class="el" href="classtvm_1_1TypeFunctor_3_01R_07const_01Type_01_6n_00_01Args_8_8_8_08_4.html#a949688cb9b4a8fa16ddc3e5fbbf13580">tvm::TypeFunctor< R(const Type &n, Args...)></a>
+, <a class="el" href="classtvm_1_1TypeMutator.html#ac694fbe28eb7026d30c5ca5fa2fb4a1a">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>
@@ -589,7 +589,7 @@ $(function() {
: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFrame.html#a8f8c990ee4fa7cb7472f5440f2ca3bde">tvm::runtime::vm::VMFrame</a>
</li>
<li>VMFunction()
-: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFunction.html#aea763069fe1dd6849ce0d1ec336931e0">tvm::runtime::vm::VMFunction</a>
+: <a class="el" href="structtvm_1_1runtime_1_1vm_1_1VMFunction.html#af9d2bdcf19642c21bc4909b9e9b6196d">tvm::runtime::vm::VMFunction</a>
</li>
<li>Void()
: <a class="el" href="classtvm_1_1runtime_1_1DataType.html#ab8dc0832aff8fd7421884c0fe20a3bfd">tvm::runtime::DataType</a>
diff --git a/docs/reference/api/doxygen/functions_vars_l.html b/docs/reference/api/doxygen/functions_vars_l.html
index 63d524545..7c309e9eb 100644
--- a/docs/reference/api/doxygen/functions_vars_l.html
+++ b/docs/reference/api/doxygen/functions_vars_l.html
@@ -122,6 +122,9 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1ClauseNode.html#a85479b56eab2bb3255248a8b0fcd23f8">tvm::relay::ClauseNode</a>
, <a class="el" href="classtvm_1_1tir_1_1CommReducerNode.html#a3fc76ed5cf3a73c803ce1c74dedf7429">tvm::tir::CommReducerNode</a>
</li>
+<li>lhs_axis
+: <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#a73378c316806d3f78a3fa0fb27178ad3">tvm::relay::qnn::BroadcastAttrs</a>
+</li>
<li>lhs_begin
: <a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html#ab858f0ecef7ac56b1f9d69b57eb6f3c8">tvm::relay::ReshapeLikeAttrs</a>
</li>
diff --git a/docs/reference/api/doxygen/functions_vars_r.html b/docs/reference/api/doxygen/functions_vars_r.html
index eda413a3b..7be5fa2e5 100644
--- a/docs/reference/api/doxygen/functions_vars_r.html
+++ b/docs/reference/api/doxygen/functions_vars_r.html
@@ -220,6 +220,9 @@ $(function() {
: <a class="el" href="classtvm_1_1relay_1_1ClauseNode.html#a93217eeea15c1f7c1a659da3da86d3bd">tvm::relay::ClauseNode</a>
, <a class="el" href="classtvm_1_1tir_1_1CommReducerNode.html#a2902b0d55dd823febc6941fae9f32337">tvm::tir::CommReducerNode</a>
</li>
+<li>rhs_axis
+: <a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html#afd0dadf19b60022c3c8cc0b0f9b6c27a">tvm::relay::qnn::BroadcastAttrs</a>
+</li>
<li>rhs_begin
: <a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html#a8f25936511569c3ea754e9d065ccff81">tvm::relay::ReshapeLikeAttrs</a>
</li>
diff --git a/docs/reference/api/doxygen/hierarchy.html b/docs/reference/api/doxygen/hierarchy.html
index 6d3a5911d..71e3b14b0 100644
--- a/docs/reference/api/doxygen/hierarchy.html
+++ b/docs/reference/api/doxygen/hierarchy.html
@@ -288,232 +288,234 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_98_30_19_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1BinaryDenseAttrs.html" target="_self">tvm::relay::BinaryDenseAttrs</a></td><td class="desc"></td></tr>
<tr id="row_98_30_20_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_20_" class="arrow" onclick="toggleFolder('98_30_20_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< BitPackAttrs ></a></td><td class="desc"></td></tr>
<tr id="row_98_30_20_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1BitPackAttrs.html" target="_self">tvm::relay::BitPackAttrs</a></td><td class="desc">Attributes used in bitpack operators </td></tr>
-<tr id="row_98_30_21_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_21_" class="arrow" onclick="toggleFolder('98_30_21_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CallLoweredAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_21_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CallLoweredAttrs.html" target="_self">tvm::relay::CallLoweredAttrs</a></td><td class="desc">Metadata for calls to TIR functions, useful for program analysis crossing Relay and TIR </td></tr>
-<tr id="row_98_30_22_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_22_" class="arrow" onclick="toggleFolder('98_30_22_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CastAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_22_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CastAttrs.html" target="_self">tvm::relay::CastAttrs</a></td><td class="desc">Data type cast </td></tr>
-<tr id="row_98_30_23_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_23_" class="arrow" onclick="toggleFolder('98_30_23_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CastHintAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_23_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CastHintAttrs.html" target="_self">tvm::relay::CastHintAttrs</a></td><td class="desc">Annotate an expression to be cast into specific data type </td></tr>
-<tr id="row_98_30_24_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_24_" class="arrow" onclick="toggleFolder('98_30_24_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ClipAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_24_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ClipAttrs.html" target="_self">tvm::relay::ClipAttrs</a></td><td class="desc">Attributes for Clip operator </td></tr>
-<tr id="row_98_30_25_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_25_" class="arrow" onclick="toggleFolder('98_30_25_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CompilerAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_25_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CompilerAttrs.html" target="_self">tvm::relay::CompilerAttrs</a></td><td class="desc">Options for the operators used to annotate a compiler </td></tr>
-<tr id="row_98_30_26_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_26_" class="arrow" onclick="toggleFolder('98_30_26_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConcatenateAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_26_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConcatenateAttrs.html" target="_self">tvm::relay::ConcatenateAttrs</a></td><td class="desc">Attributes used in concatenate operators </td></tr>
-<tr id="row_98_30_27_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_27_" class="arrow" onclick="toggleFolder('98_30_27_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv1DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_27_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv1DAttrs.html" target="_self">tvm::relay::Conv1DAttrs</a></td><td class="desc">Attributes used in 1D convolution operators </td></tr>
-<tr id="row_98_30_28_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_28_" class="arrow" onclick="toggleFolder('98_30_28_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv1DTransposeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_28_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv1DTransposeAttrs.html" target="_self">tvm::relay::Conv1DTransposeAttrs</a></td><td class="desc">Attributes used in 1D transposed convolution operator </td></tr>
-<tr id="row_98_30_29_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_29_" class="arrow" onclick="toggleFolder('98_30_29_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_29_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DAttrs.html" target="_self">tvm::relay::Conv2DAttrs</a></td><td class="desc">Attributes used in convolution operators </td></tr>
-<tr id="row_98_30_30_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_30_" class="arrow" onclick="toggleFolder('98_30_30_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DTransposeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_30_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DTransposeAttrs.html" target="_self">tvm::relay::Conv2DTransposeAttrs</a></td><td class="desc">Attributes used in transposed convolution operator </td></tr>
-<tr id="row_98_30_31_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_31_" class="arrow" onclick="toggleFolder('98_30_31_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DWinogradAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_31_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DWinogradAttrs.html" target="_self">tvm::relay::Conv2DWinogradAttrs</a></td><td class="desc">Attributes used in convolution operators with winograd algorithm </td></tr>
-<tr id="row_98_30_32_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_32_" class="arrow" onclick="toggleFolder('98_30_32_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_32_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DWinogradNNPACKWeightTransformAttrs.html" target="_self">tvm::relay::Conv2DWinogradNNPACKWeightTransformAttrs</a></td><td class="desc">Attributes used in winograd weight transformation operators </td></tr>
-<tr id="row_98_30_33_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_33_" class="arrow" onclick="toggleFolder('98_30_33_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_33_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DAttrs.html" target="_self">tvm::relay::Conv3DAttrs</a></td><td class="desc">Attributes used in convolution operators </td></tr>
-<tr id="row_98_30_34_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_34_" class="arrow" onclick="toggleFolder('98_30_34_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DTransposeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_34_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DTransposeAttrs.html" target="_self">tvm::relay::Conv3DTransposeAttrs</a></td><td class="desc">Attributes used in transposed convolution operator </td></tr>
-<tr id="row_98_30_35_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_35_" class="arrow" onclick="toggleFolder('98_30_35_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DWinogradAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_35_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DWinogradAttrs.html" target="_self">tvm::relay::Conv3DWinogradAttrs</a></td><td class="desc">Attributes used in 3d winograd convolution operators </td></tr>
-<tr id="row_98_30_36_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_36_" class="arrow" onclick="toggleFolder('98_30_36_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConvGemmWeightTransformAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_36_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConvGemmWeightTransformAttrs.html" target="_self">tvm::relay::ConvGemmWeightTransformAttrs</a></td><td class="desc">Attributes used in gemm weight transformation operators </td></tr>
-<tr id="row_98_30_37_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_37_" class="arrow" onclick="toggleFolder('98_30_37_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConvWinogradWeightTransformAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_37_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConvWinogradWeightTransformAttrs.html" target="_self">tvm::relay::ConvWinogradWeightTransformAttrs</a></td><td class="desc">Attributes used in winograd weight transformation operators </td></tr>
-<tr id="row_98_30_38_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_38_" class="arrow" onclick="toggleFolder('98_30_38_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CorrelationAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_38_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CorrelationAttrs.html" target="_self">tvm::relay::CorrelationAttrs</a></td><td class="desc">Attributes used in correlation operators </td></tr>
-<tr id="row_98_30_39_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_39_" class="arrow" onclick="toggleFolder('98_30_39_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CropAndResizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_39_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CropAndResizeAttrs.html" target="_self">tvm::relay::CropAndResizeAttrs</a></td><td class="desc">Attributes used in image crop_and_resize operator </td></tr>
-<tr id="row_98_30_40_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_40_" class="arrow" onclick="toggleFolder('98_30_40_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DebugAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_40_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DebugAttrs.html" target="_self">tvm::relay::DebugAttrs</a></td><td class="desc">Options for the debug operators </td></tr>
-<tr id="row_98_30_41_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_41_" class="arrow" onclick="toggleFolder('98_30_41_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DeformableConv2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_41_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DeformableConv2DAttrs.html" target="_self">tvm::relay::DeformableConv2DAttrs</a></td><td class="desc">Attributes for DeformableConv2D operator </td></tr>
-<tr id="row_98_30_42_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_42_" class="arrow" onclick="toggleFolder('98_30_42_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DenseAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_42_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DenseAttrs.html" target="_self">tvm::relay::DenseAttrs</a></td><td class="desc">Attributes for dense operator </td></tr>
-<tr id="row_98_30_43_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_43_" class="arrow" onclick="toggleFolder('98_30_43_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DensePackAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_43_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DensePackAttrs.html" target="_self">tvm::relay::DensePackAttrs</a></td><td class="desc">Attributes for dense_pack operator </td></tr>
-<tr id="row_98_30_44_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_44_" class="arrow" onclick="toggleFolder('98_30_44_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DequantizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_44_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html" target="_self">tvm::relay::qnn::DequantizeAttrs</a></td><td class="desc">Attribute for dequantize operator </td></tr>
-<tr id="row_98_30_45_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_45_" class="arrow" onclick="toggleFolder('98_30_45_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DeviceCopyAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_45_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DeviceCopyAttrs.html" target="_self">tvm::relay::DeviceCopyAttrs</a></td><td class="desc">Options for the device copy operators </td></tr>
-<tr id="row_98_30_46_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_46_" class="arrow" onclick="toggleFolder('98_30_46_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DilateAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_46_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DilateAttrs.html" target="_self">tvm::relay::DilateAttrs</a></td><td class="desc">Attributes used in dilate operator </td></tr>
-<tr id="row_98_30_47_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_47_" class="arrow" onclick="toggleFolder('98_30_47_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Dilation2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_47_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Dilation2DAttrs.html" target="_self">tvm::relay::Dilation2DAttrs</a></td><td class="desc">Attributes used in dilation operators </td></tr>
-<tr id="row_98_30_48_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_48_" class="arrow" onclick="toggleFolder('98_30_48_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DropoutAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_48_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DropoutAttrs.html" target="_self">tvm::relay::DropoutAttrs</a></td><td class="desc">Attributes used in dropout operator </td></tr>
-<tr id="row_98_30_49_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_49_" class="arrow" onclick="toggleFolder('98_30_49_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DynExpandDimsAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_49_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DynExpandDimsAttrs.html" target="_self">tvm::relay::DynExpandDimsAttrs</a></td><td class="desc">Attributes used in dynamic expand_dims operators </td></tr>
-<tr id="row_98_30_50_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_50_" class="arrow" onclick="toggleFolder('98_30_50_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< EinsumAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_50_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1EinsumAttrs.html" target="_self">tvm::relay::EinsumAttrs</a></td><td class="desc">Attributes used in einsum operator </td></tr>
-<tr id="row_98_30_51_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_51_" class="arrow" onclick="toggleFolder('98_30_51_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ExpandDimsAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_51_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ExpandDimsAttrs.html" target="_self">tvm::relay::ExpandDimsAttrs</a></td><td class="desc">Attributes used in expand_dims operators </td></tr>
-<tr id="row_98_30_52_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_52_" class="arrow" onclick="toggleFolder('98_30_52_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< FIFOBufferAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_52_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1FIFOBufferAttrs.html" target="_self">tvm::relay::FIFOBufferAttrs</a></td><td class="desc">Attributes for FIFO buffer operator </td></tr>
-<tr id="row_98_30_53_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_53_" class="arrow" onclick="toggleFolder('98_30_53_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< FixedPointMultiplyAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_53_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1FixedPointMultiplyAttrs.html" target="_self">tvm::relay::FixedPointMultiplyAttrs</a></td><td class="desc">Attributes for FixedPointMultiply operator </td></tr>
-<tr id="row_98_30_54_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_54_" class="arrow" onclick="toggleFolder('98_30_54_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GatherAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_54_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GatherAttrs.html" target="_self">tvm::relay::GatherAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_55_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_55_" class="arrow" onclick="toggleFolder('98_30_55_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GatherNDAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_55_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GatherNDAttrs.html" target="_self">tvm::relay::GatherNDAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_56_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_56_" class="arrow" onclick="toggleFolder('98_30_56_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GetValidCountsAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_56_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GetValidCountsAttrs.html" target="_self">tvm::relay::GetValidCountsAttrs</a></td><td class="desc">Attributes used in get_valid_counts operator </td></tr>
-<tr id="row_98_30_57_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_57_" class="arrow" onclick="toggleFolder('98_30_57_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GlobalPool2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_57_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GlobalPool2DAttrs.html" target="_self">tvm::relay::GlobalPool2DAttrs</a></td><td class="desc">Attributes for global pool operator </td></tr>
-<tr id="row_98_30_58_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_58_" class="arrow" onclick="toggleFolder('98_30_58_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GridSampleAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_58_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GridSampleAttrs.html" target="_self">tvm::relay::GridSampleAttrs</a></td><td class="desc">Attributes used in image grid_sample operator </td></tr>
-<tr id="row_98_30_59_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_59_" class="arrow" onclick="toggleFolder('98_30_59_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GroupNormAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_59_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GroupNormAttrs.html" target="_self">tvm::relay::GroupNormAttrs</a></td><td class="desc">Attributes used in group_norm operator </td></tr>
-<tr id="row_98_30_60_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_60_" class="arrow" onclick="toggleFolder('98_30_60_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< InitOpAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_60_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1InitOpAttrs.html" target="_self">tvm::relay::InitOpAttrs</a></td><td class="desc">Attributes that specify a tensor </td></tr>
-<tr id="row_98_30_61_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_61_" class="arrow" onclick="toggleFolder('98_30_61_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< InstanceNormAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_61_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1InstanceNormAttrs.html" target="_self">tvm::relay::InstanceNormAttrs</a></td><td class="desc">Attributes used in instance_norm operator </td></tr>
-<tr id="row_98_30_62_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_62_" class="arrow" onclick="toggleFolder('98_30_62_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< L2NormalizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_62_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1L2NormalizeAttrs.html" target="_self">tvm::relay::L2NormalizeAttrs</a></td><td class="desc">Attributes for L2Normalize operator </td></tr>
-<tr id="row_98_30_63_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_63_" class="arrow" onclick="toggleFolder('98_30_63_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LayerNormAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_63_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LayerNormAttrs.html" target="_self">tvm::relay::LayerNormAttrs</a></td><td class="desc">Attributes used in layer_norm operator </td></tr>
-<tr id="row_98_30_64_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_64_" class="arrow" onclick="toggleFolder('98_30_64_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LayoutTransformAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_64_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LayoutTransformAttrs.html" target="_self">tvm::relay::LayoutTransformAttrs</a></td><td class="desc">Attributes for LayoutTransform operator </td></tr>
-<tr id="row_98_30_65_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_65_" class="arrow" onclick="toggleFolder('98_30_65_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LeakyReluAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_65_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LeakyReluAttrs.html" target="_self">tvm::relay::LeakyReluAttrs</a></td><td class="desc">Attributes for leaky relu operator </td></tr>
-<tr id="row_98_30_66_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_66_" class="arrow" onclick="toggleFolder('98_30_66_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LRNAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_66_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LRNAttrs.html" target="_self">tvm::relay::LRNAttrs</a></td><td class="desc">Attributes for LRN operator </td></tr>
-<tr id="row_98_30_67_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_67_" class="arrow" onclick="toggleFolder('98_30_67_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MatmulAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_67_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MatmulAttrs.html" target="_self">tvm::relay::MatmulAttrs</a></td><td class="desc">Attributes for matmul operator </td></tr>
-<tr id="row_98_30_68_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_68_" class="arrow" onclick="toggleFolder('98_30_68_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MatrixSetDiagAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_68_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html" target="_self">tvm::relay::MatrixSetDiagAttrs</a></td><td class="desc">Attributes used in matrix_set_diag operator </td></tr>
-<tr id="row_98_30_69_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_69_" class="arrow" onclick="toggleFolder('98_30_69_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool1DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_69_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool1DAttrs.html" target="_self">tvm::relay::MaxPool1DAttrs</a></td><td class="desc">Attributes for 1D max pool operator </td></tr>
-<tr id="row_98_30_70_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_70_" class="arrow" onclick="toggleFolder('98_30_70_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_70_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool2DAttrs.html" target="_self">tvm::relay::MaxPool2DAttrs</a></td><td class="desc">Attributes for max pool operator </td></tr>
-<tr id="row_98_30_71_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_71_" class="arrow" onclick="toggleFolder('98_30_71_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool3DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_71_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool3DAttrs.html" target="_self">tvm::relay::MaxPool3DAttrs</a></td><td class="desc">Attributes for 3D max pool operator </td></tr>
-<tr id="row_98_30_72_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_72_" class="arrow" onclick="toggleFolder('98_30_72_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MeshgridAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_72_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MeshgridAttrs.html" target="_self">tvm::relay::MeshgridAttrs</a></td><td class="desc">Attributes used in meshgrid operators </td></tr>
-<tr id="row_98_30_73_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_73_" class="arrow" onclick="toggleFolder('98_30_73_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MirrorPadAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_73_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MirrorPadAttrs.html" target="_self">tvm::relay::MirrorPadAttrs</a></td><td class="desc">Attributes used for the MirrorPadding operator </td></tr>
-<tr id="row_98_30_74_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_74_" class="arrow" onclick="toggleFolder('98_30_74_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MultiBoxPriorAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_74_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MultiBoxPriorAttrs.html" target="_self">tvm::relay::MultiBoxPriorAttrs</a></td><td class="desc">Attributes used in multibox_prior operators </td></tr>
-<tr id="row_98_30_75_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_75_" class="arrow" onclick="toggleFolder('98_30_75_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MultiBoxTransformLocAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_75_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html" target="_self">tvm::relay::MultiBoxTransformLocAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_76_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_76_" class="arrow" onclick="toggleFolder('98_30_76_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NdarraySizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_76_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NdarraySizeAttrs.html" target="_self">tvm::relay::NdarraySizeAttrs</a></td><td class="desc">Attributes for ndarray_size operator </td></tr>
-<tr id="row_98_30_77_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_77_" class="arrow" onclick="toggleFolder('98_30_77_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NLLLossAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_77_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NLLLossAttrs.html" target="_self">tvm::relay::NLLLossAttrs</a></td><td class="desc">Attributes used in NLLLoss operator </td></tr>
-<tr id="row_98_30_78_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_78_" class="arrow" onclick="toggleFolder('98_30_78_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NonMaximumSuppressionAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_78_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NonMaximumSuppressionAttrs.html" target="_self">tvm::relay::NonMaximumSuppressionAttrs</a></td><td class="desc">Attributes used in non_maximum_suppression operator </td></tr>
-<tr id="row_98_30_79_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_79_" class="arrow" onclick="toggleFolder('98_30_79_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NormalAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_79_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NormalAttrs.html" target="_self">tvm::relay::NormalAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_80_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_80_" class="arrow" onclick="toggleFolder('98_30_80_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< OnDeviceAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_80_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1OnDeviceAttrs.html" target="_self">tvm::relay::OnDeviceAttrs</a></td><td class="desc">Attributes for the "on_device" annotation (ie operator) </td></tr>
-<tr id="row_98_30_81_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_81_" class="arrow" onclick="toggleFolder('98_30_81_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< OneHotAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_81_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1OneHotAttrs.html" target="_self">tvm::relay::OneHotAttrs</a></td><td class="desc">Attributes used in one-hot operator </td></tr>
-<tr id="row_98_30_82_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_82_" class="arrow" onclick="toggleFolder('98_30_82_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< PadAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_82_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1PadAttrs.html" target="_self">tvm::relay::PadAttrs</a></td><td class="desc">Attributes used for the padding operator </td></tr>
-<tr id="row_98_30_83_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_83_" class="arrow" onclick="toggleFolder('98_30_83_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< PReluAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_83_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1PReluAttrs.html" target="_self">tvm::relay::PReluAttrs</a></td><td class="desc">Attributes for prelu operator </td></tr>
-<tr id="row_98_30_84_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_84_" class="arrow" onclick="toggleFolder('98_30_84_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ProposalAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_84_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ProposalAttrs.html" target="_self">tvm::relay::ProposalAttrs</a></td><td class="desc">Attributes used in proposal operators </td></tr>
-<tr id="row_98_30_85_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_85_" class="arrow" onclick="toggleFolder('98_30_85_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< QuantizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_85_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html" target="_self">tvm::relay::qnn::QuantizeAttrs</a></td><td class="desc">Attribute for quantize operator </td></tr>
-<tr id="row_98_30_86_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_86_" class="arrow" onclick="toggleFolder('98_30_86_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReduceAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_86_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReduceAttrs.html" target="_self">tvm::relay::ReduceAttrs</a></td><td class="desc">Attributes for Reduce operators </td></tr>
-<tr id="row_98_30_87_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_87_" class="arrow" onclick="toggleFolder('98_30_87_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< RepeatAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_87_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1RepeatAttrs.html" target="_self">tvm::relay::RepeatAttrs</a></td><td class="desc">Attributes used in repeat operators </td></tr>
-<tr id="row_98_30_88_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_88_" class="arrow" onclick="toggleFolder('98_30_88_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< RequantizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_88_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html" target="_self">tvm::relay::qnn::RequantizeAttrs</a></td><td class="desc">Attribute for requantize operator </td></tr>
-<tr id="row_98_30_89_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_89_" class="arrow" onclick="toggleFolder('98_30_89_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_89_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeAttrs.html" target="_self">tvm::relay::ReshapeAttrs</a></td><td class="desc">Attributes used in reshape operators </td></tr>
-<tr id="row_98_30_90_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_90_" class="arrow" onclick="toggleFolder('98_30_90_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeLikeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_90_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html" target="_self">tvm::relay::ReshapeLikeAttrs</a></td><td class="desc">Attributes used in MXNet-style reshape_like operators </td></tr>
-<tr id="row_98_30_91_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_91_" class="arrow" onclick="toggleFolder('98_30_91_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeTensorAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_91_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeTensorAttrs.html" target="_self">tvm::relay::ReshapeTensorAttrs</a></td><td class="desc">Attributes for VM reshape_tensor operator </td></tr>
-<tr id="row_98_30_92_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_92_" class="arrow" onclick="toggleFolder('98_30_92_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize1DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_92_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize1DAttrs.html" target="_self">tvm::relay::Resize1DAttrs</a></td><td class="desc">Attributes used in image resize1d operator </td></tr>
-<tr id="row_98_30_93_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_93_" class="arrow" onclick="toggleFolder('98_30_93_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_93_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize2DAttrs.html" target="_self">tvm::relay::Resize2DAttrs</a></td><td class="desc">Attributes used in image resize2d operator </td></tr>
-<tr id="row_98_30_94_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_94_" class="arrow" onclick="toggleFolder('98_30_94_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize3DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_94_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize3DAttrs.html" target="_self">tvm::relay::Resize3DAttrs</a></td><td class="desc">Attributes used in image resize3d operator </td></tr>
-<tr id="row_98_30_95_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_95_" class="arrow" onclick="toggleFolder('98_30_95_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReverseAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_95_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReverseAttrs.html" target="_self">tvm::relay::ReverseAttrs</a></td><td class="desc">Attributes used in reverse operators </td></tr>
-<tr id="row_98_30_96_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_96_" class="arrow" onclick="toggleFolder('98_30_96_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReverseSequenceAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_96_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReverseSequenceAttrs.html" target="_self">tvm::relay::ReverseSequenceAttrs</a></td><td class="desc">Attributes used in reverse_sequence operators </td></tr>
-<tr id="row_98_30_97_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_97_" class="arrow" onclick="toggleFolder('98_30_97_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ROIAlignAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_97_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ROIAlignAttrs.html" target="_self">tvm::relay::ROIAlignAttrs</a></td><td class="desc">Attributes used in roi_align operators </td></tr>
-<tr id="row_98_30_98_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_98_" class="arrow" onclick="toggleFolder('98_30_98_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ROIPoolAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_98_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ROIPoolAttrs.html" target="_self">tvm::relay::ROIPoolAttrs</a></td><td class="desc">Attributes used in roi_pool operators </td></tr>
-<tr id="row_98_30_99_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_99_" class="arrow" onclick="toggleFolder('98_30_99_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScanopAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_99_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScanopAttrs.html" target="_self">tvm::relay::ScanopAttrs</a></td><td class="desc">Attributes used in cumsum and cumprod operator </td></tr>
-<tr id="row_98_30_100_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_100_" class="arrow" onclick="toggleFolder('98_30_100_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterAddAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_100_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterAddAttrs.html" target="_self">tvm::relay::ScatterAddAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_101_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_101_" class="arrow" onclick="toggleFolder('98_30_101_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_101_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterAttrs.html" target="_self">tvm::relay::ScatterAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_102_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_102_" class="arrow" onclick="toggleFolder('98_30_102_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterNDAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_102_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterNDAttrs.html" target="_self">tvm::relay::ScatterNDAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_103_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_103_" class="arrow" onclick="toggleFolder('98_30_103_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SearchSortedAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_103_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SearchSortedAttrs.html" target="_self">tvm::relay::SearchSortedAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_104_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_104_" class="arrow" onclick="toggleFolder('98_30_104_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SequenceMaskAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_104_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SequenceMaskAttrs.html" target="_self">tvm::relay::SequenceMaskAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_105_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_105_" class="arrow" onclick="toggleFolder('98_30_105_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ShapeFuncAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_105_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ShapeFuncAttrs.html" target="_self">tvm::relay::ShapeFuncAttrs</a></td><td class="desc">Options for the shape function operator </td></tr>
-<tr id="row_98_30_106_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_106_" class="arrow" onclick="toggleFolder('98_30_106_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ShapeOfAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_106_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ShapeOfAttrs.html" target="_self">tvm::relay::ShapeOfAttrs</a></td><td class="desc">Attributes for ShapeOf operator </td></tr>
-<tr id="row_98_30_107_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_107_" class="arrow" onclick="toggleFolder('98_30_107_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SimulatedQuantizeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_107_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1SimulatedQuantizeAttrs.html" target="_self">tvm::relay::qnn::SimulatedQuantizeAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_108_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_108_" class="arrow" onclick="toggleFolder('98_30_108_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SliceLikeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_108_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SliceLikeAttrs.html" target="_self">tvm::relay::SliceLikeAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_109_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_109_" class="arrow" onclick="toggleFolder('98_30_109_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SlidingWindowAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_109_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SlidingWindowAttrs.html" target="_self">tvm::relay::SlidingWindowAttrs</a></td><td class="desc">Attributes used for the sliding_window operator </td></tr>
-<tr id="row_98_30_110_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_110_" class="arrow" onclick="toggleFolder('98_30_110_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SoftmaxAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_110_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SoftmaxAttrs.html" target="_self">tvm::relay::SoftmaxAttrs</a></td><td class="desc">Attributes used in softmax operators </td></tr>
-<tr id="row_98_30_111_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_111_" class="arrow" onclick="toggleFolder('98_30_111_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SpaceToBatchNDAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_111_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SpaceToBatchNDAttrs.html" target="_self">tvm::relay::SpaceToBatchNDAttrs</a></td><td class="desc">Attributes used in SpaceToBatchND operator </td></tr>
-<tr id="row_98_30_112_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_112_" class="arrow" onclick="toggleFolder('98_30_112_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseConv2DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_112_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseConv2DAttrs.html" target="_self">tvm::relay::SparseConv2DAttrs</a></td><td class="desc">Attributes for sparse_dense operator </td></tr>
-<tr id="row_98_30_113_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_113_" class="arrow" onclick="toggleFolder('98_30_113_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseDenseAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_113_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseDenseAttrs.html" target="_self">tvm::relay::SparseDenseAttrs</a></td><td class="desc">Attributes for sparse_dense operator </td></tr>
-<tr id="row_98_30_114_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_114_" class="arrow" onclick="toggleFolder('98_30_114_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseToDenseAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_114_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseToDenseAttrs.html" target="_self">tvm::relay::SparseToDenseAttrs</a></td><td class="desc">Attributes used in sparse_to_dense operator </td></tr>
-<tr id="row_98_30_115_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_115_" class="arrow" onclick="toggleFolder('98_30_115_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseTransposeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_115_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseTransposeAttrs.html" target="_self">tvm::relay::SparseTransposeAttrs</a></td><td class="desc">Attributes for sparse_transpose operator </td></tr>
-<tr id="row_98_30_116_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_116_" class="arrow" onclick="toggleFolder('98_30_116_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SplitAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_116_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SplitAttrs.html" target="_self">tvm::relay::SplitAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_117_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_117_" class="arrow" onclick="toggleFolder('98_30_117_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SqueezeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_117_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SqueezeAttrs.html" target="_self">tvm::relay::SqueezeAttrs</a></td><td class="desc">Attributes used in squeeze operators </td></tr>
-<tr id="row_98_30_118_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_118_" class="arrow" onclick="toggleFolder('98_30_118_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< StackAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_118_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1StackAttrs.html" target="_self">tvm::relay::StackAttrs</a></td><td class="desc">Attributes used in stack operators </td></tr>
-<tr id="row_98_30_119_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_119_" class="arrow" onclick="toggleFolder('98_30_119_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< StridedSliceAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_119_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1StridedSliceAttrs.html" target="_self">tvm::relay::StridedSliceAttrs</a></td><td class="desc">Attributes for StridedSlice operator </td></tr>
-<tr id="row_98_30_120_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_120_" class="arrow" onclick="toggleFolder('98_30_120_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SubPixelAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_120_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SubPixelAttrs.html" target="_self">tvm::relay::SubPixelAttrs</a></td><td class="desc">Attributes used in subpixel operators </td></tr>
-<tr id="row_98_30_121_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_121_" class="arrow" onclick="toggleFolder('98_30_121_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TakeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_121_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TakeAttrs.html" target="_self">tvm::relay::TakeAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_122_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_122_" class="arrow" onclick="toggleFolder('98_30_122_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ThreefryGenerateAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_122_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ThreefryGenerateAttrs.html" target="_self">tvm::relay::ThreefryGenerateAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_123_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_123_" class="arrow" onclick="toggleFolder('98_30_123_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TileAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_123_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TileAttrs.html" target="_self">tvm::relay::TileAttrs</a></td><td class="desc">Attributes used in tile operators </td></tr>
-<tr id="row_98_30_124_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_124_" class="arrow" onclick="toggleFolder('98_30_124_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TopKAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_124_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TopKAttrs.html" target="_self">tvm::relay::TopKAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_125_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_125_" class="arrow" onclick="toggleFolder('98_30_125_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TransposeAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_125_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TransposeAttrs.html" target="_self">tvm::relay::TransposeAttrs</a></td><td class="desc">Attributes used in transpose operators </td></tr>
-<tr id="row_98_30_126_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_126_" class="arrow" onclick="toggleFolder('98_30_126_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UniformAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_126_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UniformAttrs.html" target="_self">tvm::relay::UniformAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_127_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_127_" class="arrow" onclick="toggleFolder('98_30_127_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UniqueAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_127_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UniqueAttrs.html" target="_self">tvm::relay::UniqueAttrs</a></td><td class="desc">Attributes used in unique operator </td></tr>
-<tr id="row_98_30_128_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_128_" class="arrow" onclick="toggleFolder('98_30_128_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UpSampling3DAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_128_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UpSampling3DAttrs.html" target="_self">tvm::relay::UpSampling3DAttrs</a></td><td class="desc">Attributes for upsampling3d operator </td></tr>
-<tr id="row_98_30_129_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_129_" class="arrow" onclick="toggleFolder('98_30_129_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UpSamplingAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_129_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UpSamplingAttrs.html" target="_self">tvm::relay::UpSamplingAttrs</a></td><td class="desc">Attributes for upsampling operator </td></tr>
-<tr id="row_98_30_130_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_130_" class="arrow" onclick="toggleFolder('98_30_130_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< VarianceAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_130_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1VarianceAttrs.html" target="_self">tvm::relay::VarianceAttrs</a></td><td class="desc"></td></tr>
-<tr id="row_98_30_131_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_131_" class="arrow" onclick="toggleFolder('98_30_131_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< VirtualDeviceNode ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_131_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1VirtualDeviceNode.html" target="_self">tvm::VirtualDeviceNode</a></td><td class="desc">Describes at compile time the constraints on where data is to be stored at runtime down to the (virtual) device and memory scope level, and how to compile code to compute that data. Used by the [...]
-<tr id="row_98_30_132_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_132_" class="arrow" onclick="toggleFolder('98_30_132_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< YoloReorgAttrs ></a></td><td class="desc"></td></tr>
-<tr id="row_98_30_132_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1YoloReorgAttrs.html" target="_self">tvm::relay::YoloReorgAttrs</a></td><td class="desc">Attributes used in yolo reorg operators </td></tr>
-<tr id="row_98_30_133_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DerivedType ></a></td><td class="desc">The base class of the all the Use "curiously recurring template pattern" </td></tr>
-<tr id="row_98_30_134_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1DictAttrsNode.html" target="_self">tvm::DictAttrsNode</a></td><td class="desc">Specialized attribute type that is backed by a map. The <a class="el" href="classtvm_1_1DictAttrsNode.html" title="Specialized attribute type that is backed by a map. The DictAttrsNode implements the Att [...]
+<tr id="row_98_30_21_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_21_" class="arrow" onclick="toggleFolder('98_30_21_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< BroadcastAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_21_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1BroadcastAttrs.html" target="_self">tvm::relay::qnn::BroadcastAttrs</a></td><td class="desc">Attribute for broadcast operator </td></tr>
+<tr id="row_98_30_22_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_22_" class="arrow" onclick="toggleFolder('98_30_22_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CallLoweredAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_22_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CallLoweredAttrs.html" target="_self">tvm::relay::CallLoweredAttrs</a></td><td class="desc">Metadata for calls to TIR functions, useful for program analysis crossing Relay and TIR </td></tr>
+<tr id="row_98_30_23_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_23_" class="arrow" onclick="toggleFolder('98_30_23_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CastAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_23_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CastAttrs.html" target="_self">tvm::relay::CastAttrs</a></td><td class="desc">Data type cast </td></tr>
+<tr id="row_98_30_24_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_24_" class="arrow" onclick="toggleFolder('98_30_24_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CastHintAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_24_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CastHintAttrs.html" target="_self">tvm::relay::CastHintAttrs</a></td><td class="desc">Annotate an expression to be cast into specific data type </td></tr>
+<tr id="row_98_30_25_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_25_" class="arrow" onclick="toggleFolder('98_30_25_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ClipAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_25_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ClipAttrs.html" target="_self">tvm::relay::ClipAttrs</a></td><td class="desc">Attributes for Clip operator </td></tr>
+<tr id="row_98_30_26_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_26_" class="arrow" onclick="toggleFolder('98_30_26_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CompilerAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_26_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CompilerAttrs.html" target="_self">tvm::relay::CompilerAttrs</a></td><td class="desc">Options for the operators used to annotate a compiler </td></tr>
+<tr id="row_98_30_27_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_27_" class="arrow" onclick="toggleFolder('98_30_27_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConcatenateAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_27_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConcatenateAttrs.html" target="_self">tvm::relay::ConcatenateAttrs</a></td><td class="desc">Attributes used in concatenate operators </td></tr>
+<tr id="row_98_30_28_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_28_" class="arrow" onclick="toggleFolder('98_30_28_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv1DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_28_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv1DAttrs.html" target="_self">tvm::relay::Conv1DAttrs</a></td><td class="desc">Attributes used in 1D convolution operators </td></tr>
+<tr id="row_98_30_29_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_29_" class="arrow" onclick="toggleFolder('98_30_29_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv1DTransposeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_29_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv1DTransposeAttrs.html" target="_self">tvm::relay::Conv1DTransposeAttrs</a></td><td class="desc">Attributes used in 1D transposed convolution operator </td></tr>
+<tr id="row_98_30_30_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_30_" class="arrow" onclick="toggleFolder('98_30_30_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_30_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DAttrs.html" target="_self">tvm::relay::Conv2DAttrs</a></td><td class="desc">Attributes used in convolution operators </td></tr>
+<tr id="row_98_30_31_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_31_" class="arrow" onclick="toggleFolder('98_30_31_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DTransposeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_31_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DTransposeAttrs.html" target="_self">tvm::relay::Conv2DTransposeAttrs</a></td><td class="desc">Attributes used in transposed convolution operator </td></tr>
+<tr id="row_98_30_32_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_32_" class="arrow" onclick="toggleFolder('98_30_32_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DWinogradAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_32_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DWinogradAttrs.html" target="_self">tvm::relay::Conv2DWinogradAttrs</a></td><td class="desc">Attributes used in convolution operators with winograd algorithm </td></tr>
+<tr id="row_98_30_33_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_33_" class="arrow" onclick="toggleFolder('98_30_33_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv2DWinogradNNPACKWeightTransformAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_33_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv2DWinogradNNPACKWeightTransformAttrs.html" target="_self">tvm::relay::Conv2DWinogradNNPACKWeightTransformAttrs</a></td><td class="desc">Attributes used in winograd weight transformation operators </td></tr>
+<tr id="row_98_30_34_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_34_" class="arrow" onclick="toggleFolder('98_30_34_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_34_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DAttrs.html" target="_self">tvm::relay::Conv3DAttrs</a></td><td class="desc">Attributes used in convolution operators </td></tr>
+<tr id="row_98_30_35_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_35_" class="arrow" onclick="toggleFolder('98_30_35_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DTransposeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_35_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DTransposeAttrs.html" target="_self">tvm::relay::Conv3DTransposeAttrs</a></td><td class="desc">Attributes used in transposed convolution operator </td></tr>
+<tr id="row_98_30_36_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_36_" class="arrow" onclick="toggleFolder('98_30_36_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Conv3DWinogradAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_36_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Conv3DWinogradAttrs.html" target="_self">tvm::relay::Conv3DWinogradAttrs</a></td><td class="desc">Attributes used in 3d winograd convolution operators </td></tr>
+<tr id="row_98_30_37_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_37_" class="arrow" onclick="toggleFolder('98_30_37_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConvGemmWeightTransformAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_37_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConvGemmWeightTransformAttrs.html" target="_self">tvm::relay::ConvGemmWeightTransformAttrs</a></td><td class="desc">Attributes used in gemm weight transformation operators </td></tr>
+<tr id="row_98_30_38_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_38_" class="arrow" onclick="toggleFolder('98_30_38_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ConvWinogradWeightTransformAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_38_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ConvWinogradWeightTransformAttrs.html" target="_self">tvm::relay::ConvWinogradWeightTransformAttrs</a></td><td class="desc">Attributes used in winograd weight transformation operators </td></tr>
+<tr id="row_98_30_39_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_39_" class="arrow" onclick="toggleFolder('98_30_39_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CorrelationAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_39_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CorrelationAttrs.html" target="_self">tvm::relay::CorrelationAttrs</a></td><td class="desc">Attributes used in correlation operators </td></tr>
+<tr id="row_98_30_40_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_40_" class="arrow" onclick="toggleFolder('98_30_40_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< CropAndResizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_40_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1CropAndResizeAttrs.html" target="_self">tvm::relay::CropAndResizeAttrs</a></td><td class="desc">Attributes used in image crop_and_resize operator </td></tr>
+<tr id="row_98_30_41_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_41_" class="arrow" onclick="toggleFolder('98_30_41_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DebugAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_41_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DebugAttrs.html" target="_self">tvm::relay::DebugAttrs</a></td><td class="desc">Options for the debug operators </td></tr>
+<tr id="row_98_30_42_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_42_" class="arrow" onclick="toggleFolder('98_30_42_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DeformableConv2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_42_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DeformableConv2DAttrs.html" target="_self">tvm::relay::DeformableConv2DAttrs</a></td><td class="desc">Attributes for DeformableConv2D operator </td></tr>
+<tr id="row_98_30_43_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_43_" class="arrow" onclick="toggleFolder('98_30_43_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DenseAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_43_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DenseAttrs.html" target="_self">tvm::relay::DenseAttrs</a></td><td class="desc">Attributes for dense operator </td></tr>
+<tr id="row_98_30_44_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_44_" class="arrow" onclick="toggleFolder('98_30_44_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DensePackAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_44_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DensePackAttrs.html" target="_self">tvm::relay::DensePackAttrs</a></td><td class="desc">Attributes for dense_pack operator </td></tr>
+<tr id="row_98_30_45_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_45_" class="arrow" onclick="toggleFolder('98_30_45_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DequantizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_45_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1DequantizeAttrs.html" target="_self">tvm::relay::qnn::DequantizeAttrs</a></td><td class="desc">Attribute for dequantize operator </td></tr>
+<tr id="row_98_30_46_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_46_" class="arrow" onclick="toggleFolder('98_30_46_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DeviceCopyAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_46_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DeviceCopyAttrs.html" target="_self">tvm::relay::DeviceCopyAttrs</a></td><td class="desc">Options for the device copy operators </td></tr>
+<tr id="row_98_30_47_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_47_" class="arrow" onclick="toggleFolder('98_30_47_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DilateAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_47_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DilateAttrs.html" target="_self">tvm::relay::DilateAttrs</a></td><td class="desc">Attributes used in dilate operator </td></tr>
+<tr id="row_98_30_48_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_48_" class="arrow" onclick="toggleFolder('98_30_48_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Dilation2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_48_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Dilation2DAttrs.html" target="_self">tvm::relay::Dilation2DAttrs</a></td><td class="desc">Attributes used in dilation operators </td></tr>
+<tr id="row_98_30_49_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_49_" class="arrow" onclick="toggleFolder('98_30_49_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DropoutAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_49_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DropoutAttrs.html" target="_self">tvm::relay::DropoutAttrs</a></td><td class="desc">Attributes used in dropout operator </td></tr>
+<tr id="row_98_30_50_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_50_" class="arrow" onclick="toggleFolder('98_30_50_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DynExpandDimsAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_50_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1DynExpandDimsAttrs.html" target="_self">tvm::relay::DynExpandDimsAttrs</a></td><td class="desc">Attributes used in dynamic expand_dims operators </td></tr>
+<tr id="row_98_30_51_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_51_" class="arrow" onclick="toggleFolder('98_30_51_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< EinsumAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_51_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1EinsumAttrs.html" target="_self">tvm::relay::EinsumAttrs</a></td><td class="desc">Attributes used in einsum operator </td></tr>
+<tr id="row_98_30_52_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_52_" class="arrow" onclick="toggleFolder('98_30_52_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ExpandDimsAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_52_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ExpandDimsAttrs.html" target="_self">tvm::relay::ExpandDimsAttrs</a></td><td class="desc">Attributes used in expand_dims operators </td></tr>
+<tr id="row_98_30_53_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_53_" class="arrow" onclick="toggleFolder('98_30_53_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< FIFOBufferAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_53_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1FIFOBufferAttrs.html" target="_self">tvm::relay::FIFOBufferAttrs</a></td><td class="desc">Attributes for FIFO buffer operator </td></tr>
+<tr id="row_98_30_54_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_54_" class="arrow" onclick="toggleFolder('98_30_54_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< FixedPointMultiplyAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_54_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1FixedPointMultiplyAttrs.html" target="_self">tvm::relay::FixedPointMultiplyAttrs</a></td><td class="desc">Attributes for FixedPointMultiply operator </td></tr>
+<tr id="row_98_30_55_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_55_" class="arrow" onclick="toggleFolder('98_30_55_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GatherAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_55_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GatherAttrs.html" target="_self">tvm::relay::GatherAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_56_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_56_" class="arrow" onclick="toggleFolder('98_30_56_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GatherNDAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_56_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GatherNDAttrs.html" target="_self">tvm::relay::GatherNDAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_57_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_57_" class="arrow" onclick="toggleFolder('98_30_57_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GetValidCountsAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_57_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GetValidCountsAttrs.html" target="_self">tvm::relay::GetValidCountsAttrs</a></td><td class="desc">Attributes used in get_valid_counts operator </td></tr>
+<tr id="row_98_30_58_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_58_" class="arrow" onclick="toggleFolder('98_30_58_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GlobalPool2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_58_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GlobalPool2DAttrs.html" target="_self">tvm::relay::GlobalPool2DAttrs</a></td><td class="desc">Attributes for global pool operator </td></tr>
+<tr id="row_98_30_59_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_59_" class="arrow" onclick="toggleFolder('98_30_59_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GridSampleAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_59_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GridSampleAttrs.html" target="_self">tvm::relay::GridSampleAttrs</a></td><td class="desc">Attributes used in image grid_sample operator </td></tr>
+<tr id="row_98_30_60_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_60_" class="arrow" onclick="toggleFolder('98_30_60_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< GroupNormAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_60_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1GroupNormAttrs.html" target="_self">tvm::relay::GroupNormAttrs</a></td><td class="desc">Attributes used in group_norm operator </td></tr>
+<tr id="row_98_30_61_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_61_" class="arrow" onclick="toggleFolder('98_30_61_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< InitOpAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_61_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1InitOpAttrs.html" target="_self">tvm::relay::InitOpAttrs</a></td><td class="desc">Attributes that specify a tensor </td></tr>
+<tr id="row_98_30_62_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_62_" class="arrow" onclick="toggleFolder('98_30_62_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< InstanceNormAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_62_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1InstanceNormAttrs.html" target="_self">tvm::relay::InstanceNormAttrs</a></td><td class="desc">Attributes used in instance_norm operator </td></tr>
+<tr id="row_98_30_63_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_63_" class="arrow" onclick="toggleFolder('98_30_63_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< L2NormalizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_63_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1L2NormalizeAttrs.html" target="_self">tvm::relay::L2NormalizeAttrs</a></td><td class="desc">Attributes for L2Normalize operator </td></tr>
+<tr id="row_98_30_64_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_64_" class="arrow" onclick="toggleFolder('98_30_64_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LayerNormAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_64_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LayerNormAttrs.html" target="_self">tvm::relay::LayerNormAttrs</a></td><td class="desc">Attributes used in layer_norm operator </td></tr>
+<tr id="row_98_30_65_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_65_" class="arrow" onclick="toggleFolder('98_30_65_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LayoutTransformAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_65_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LayoutTransformAttrs.html" target="_self">tvm::relay::LayoutTransformAttrs</a></td><td class="desc">Attributes for LayoutTransform operator </td></tr>
+<tr id="row_98_30_66_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_66_" class="arrow" onclick="toggleFolder('98_30_66_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LeakyReluAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_66_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LeakyReluAttrs.html" target="_self">tvm::relay::LeakyReluAttrs</a></td><td class="desc">Attributes for leaky relu operator </td></tr>
+<tr id="row_98_30_67_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_67_" class="arrow" onclick="toggleFolder('98_30_67_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< LRNAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_67_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1LRNAttrs.html" target="_self">tvm::relay::LRNAttrs</a></td><td class="desc">Attributes for LRN operator </td></tr>
+<tr id="row_98_30_68_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_68_" class="arrow" onclick="toggleFolder('98_30_68_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MatmulAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_68_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MatmulAttrs.html" target="_self">tvm::relay::MatmulAttrs</a></td><td class="desc">Attributes for matmul operator </td></tr>
+<tr id="row_98_30_69_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_69_" class="arrow" onclick="toggleFolder('98_30_69_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MatrixSetDiagAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_69_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MatrixSetDiagAttrs.html" target="_self">tvm::relay::MatrixSetDiagAttrs</a></td><td class="desc">Attributes used in matrix_set_diag operator </td></tr>
+<tr id="row_98_30_70_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_70_" class="arrow" onclick="toggleFolder('98_30_70_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool1DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_70_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool1DAttrs.html" target="_self">tvm::relay::MaxPool1DAttrs</a></td><td class="desc">Attributes for 1D max pool operator </td></tr>
+<tr id="row_98_30_71_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_71_" class="arrow" onclick="toggleFolder('98_30_71_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_71_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool2DAttrs.html" target="_self">tvm::relay::MaxPool2DAttrs</a></td><td class="desc">Attributes for max pool operator </td></tr>
+<tr id="row_98_30_72_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_72_" class="arrow" onclick="toggleFolder('98_30_72_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MaxPool3DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_72_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MaxPool3DAttrs.html" target="_self">tvm::relay::MaxPool3DAttrs</a></td><td class="desc">Attributes for 3D max pool operator </td></tr>
+<tr id="row_98_30_73_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_73_" class="arrow" onclick="toggleFolder('98_30_73_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MeshgridAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_73_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MeshgridAttrs.html" target="_self">tvm::relay::MeshgridAttrs</a></td><td class="desc">Attributes used in meshgrid operators </td></tr>
+<tr id="row_98_30_74_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_74_" class="arrow" onclick="toggleFolder('98_30_74_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MirrorPadAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_74_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MirrorPadAttrs.html" target="_self">tvm::relay::MirrorPadAttrs</a></td><td class="desc">Attributes used for the MirrorPadding operator </td></tr>
+<tr id="row_98_30_75_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_75_" class="arrow" onclick="toggleFolder('98_30_75_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MultiBoxPriorAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_75_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MultiBoxPriorAttrs.html" target="_self">tvm::relay::MultiBoxPriorAttrs</a></td><td class="desc">Attributes used in multibox_prior operators </td></tr>
+<tr id="row_98_30_76_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_76_" class="arrow" onclick="toggleFolder('98_30_76_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< MultiBoxTransformLocAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_76_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1MultiBoxTransformLocAttrs.html" target="_self">tvm::relay::MultiBoxTransformLocAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_77_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_77_" class="arrow" onclick="toggleFolder('98_30_77_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NdarraySizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_77_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NdarraySizeAttrs.html" target="_self">tvm::relay::NdarraySizeAttrs</a></td><td class="desc">Attributes for ndarray_size operator </td></tr>
+<tr id="row_98_30_78_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_78_" class="arrow" onclick="toggleFolder('98_30_78_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NLLLossAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_78_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NLLLossAttrs.html" target="_self">tvm::relay::NLLLossAttrs</a></td><td class="desc">Attributes used in NLLLoss operator </td></tr>
+<tr id="row_98_30_79_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_79_" class="arrow" onclick="toggleFolder('98_30_79_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NonMaximumSuppressionAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_79_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NonMaximumSuppressionAttrs.html" target="_self">tvm::relay::NonMaximumSuppressionAttrs</a></td><td class="desc">Attributes used in non_maximum_suppression operator </td></tr>
+<tr id="row_98_30_80_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_80_" class="arrow" onclick="toggleFolder('98_30_80_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< NormalAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_80_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1NormalAttrs.html" target="_self">tvm::relay::NormalAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_81_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_81_" class="arrow" onclick="toggleFolder('98_30_81_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< OnDeviceAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_81_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1OnDeviceAttrs.html" target="_self">tvm::relay::OnDeviceAttrs</a></td><td class="desc">Attributes for the "on_device" annotation (ie operator) </td></tr>
+<tr id="row_98_30_82_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_82_" class="arrow" onclick="toggleFolder('98_30_82_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< OneHotAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_82_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1OneHotAttrs.html" target="_self">tvm::relay::OneHotAttrs</a></td><td class="desc">Attributes used in one-hot operator </td></tr>
+<tr id="row_98_30_83_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_83_" class="arrow" onclick="toggleFolder('98_30_83_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< PadAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_83_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1PadAttrs.html" target="_self">tvm::relay::PadAttrs</a></td><td class="desc">Attributes used for the padding operator </td></tr>
+<tr id="row_98_30_84_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_84_" class="arrow" onclick="toggleFolder('98_30_84_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< PReluAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_84_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1PReluAttrs.html" target="_self">tvm::relay::PReluAttrs</a></td><td class="desc">Attributes for prelu operator </td></tr>
+<tr id="row_98_30_85_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_85_" class="arrow" onclick="toggleFolder('98_30_85_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ProposalAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_85_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ProposalAttrs.html" target="_self">tvm::relay::ProposalAttrs</a></td><td class="desc">Attributes used in proposal operators </td></tr>
+<tr id="row_98_30_86_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_86_" class="arrow" onclick="toggleFolder('98_30_86_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< QuantizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_86_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1QuantizeAttrs.html" target="_self">tvm::relay::qnn::QuantizeAttrs</a></td><td class="desc">Attribute for quantize operator </td></tr>
+<tr id="row_98_30_87_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_87_" class="arrow" onclick="toggleFolder('98_30_87_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReduceAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_87_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReduceAttrs.html" target="_self">tvm::relay::ReduceAttrs</a></td><td class="desc">Attributes for Reduce operators </td></tr>
+<tr id="row_98_30_88_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_88_" class="arrow" onclick="toggleFolder('98_30_88_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< RepeatAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_88_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1RepeatAttrs.html" target="_self">tvm::relay::RepeatAttrs</a></td><td class="desc">Attributes used in repeat operators </td></tr>
+<tr id="row_98_30_89_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_89_" class="arrow" onclick="toggleFolder('98_30_89_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< RequantizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_89_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1RequantizeAttrs.html" target="_self">tvm::relay::qnn::RequantizeAttrs</a></td><td class="desc">Attribute for requantize operator </td></tr>
+<tr id="row_98_30_90_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_90_" class="arrow" onclick="toggleFolder('98_30_90_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_90_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeAttrs.html" target="_self">tvm::relay::ReshapeAttrs</a></td><td class="desc">Attributes used in reshape operators </td></tr>
+<tr id="row_98_30_91_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_91_" class="arrow" onclick="toggleFolder('98_30_91_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeLikeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_91_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeLikeAttrs.html" target="_self">tvm::relay::ReshapeLikeAttrs</a></td><td class="desc">Attributes used in MXNet-style reshape_like operators </td></tr>
+<tr id="row_98_30_92_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_92_" class="arrow" onclick="toggleFolder('98_30_92_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReshapeTensorAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_92_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReshapeTensorAttrs.html" target="_self">tvm::relay::ReshapeTensorAttrs</a></td><td class="desc">Attributes for VM reshape_tensor operator </td></tr>
+<tr id="row_98_30_93_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_93_" class="arrow" onclick="toggleFolder('98_30_93_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize1DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_93_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize1DAttrs.html" target="_self">tvm::relay::Resize1DAttrs</a></td><td class="desc">Attributes used in image resize1d operator </td></tr>
+<tr id="row_98_30_94_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_94_" class="arrow" onclick="toggleFolder('98_30_94_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_94_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize2DAttrs.html" target="_self">tvm::relay::Resize2DAttrs</a></td><td class="desc">Attributes used in image resize2d operator </td></tr>
+<tr id="row_98_30_95_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_95_" class="arrow" onclick="toggleFolder('98_30_95_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< Resize3DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_95_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1Resize3DAttrs.html" target="_self">tvm::relay::Resize3DAttrs</a></td><td class="desc">Attributes used in image resize3d operator </td></tr>
+<tr id="row_98_30_96_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_96_" class="arrow" onclick="toggleFolder('98_30_96_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReverseAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_96_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReverseAttrs.html" target="_self">tvm::relay::ReverseAttrs</a></td><td class="desc">Attributes used in reverse operators </td></tr>
+<tr id="row_98_30_97_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_97_" class="arrow" onclick="toggleFolder('98_30_97_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ReverseSequenceAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_97_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ReverseSequenceAttrs.html" target="_self">tvm::relay::ReverseSequenceAttrs</a></td><td class="desc">Attributes used in reverse_sequence operators </td></tr>
+<tr id="row_98_30_98_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_98_" class="arrow" onclick="toggleFolder('98_30_98_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ROIAlignAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_98_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ROIAlignAttrs.html" target="_self">tvm::relay::ROIAlignAttrs</a></td><td class="desc">Attributes used in roi_align operators </td></tr>
+<tr id="row_98_30_99_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_99_" class="arrow" onclick="toggleFolder('98_30_99_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ROIPoolAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_99_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ROIPoolAttrs.html" target="_self">tvm::relay::ROIPoolAttrs</a></td><td class="desc">Attributes used in roi_pool operators </td></tr>
+<tr id="row_98_30_100_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_100_" class="arrow" onclick="toggleFolder('98_30_100_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScanopAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_100_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScanopAttrs.html" target="_self">tvm::relay::ScanopAttrs</a></td><td class="desc">Attributes used in cumsum and cumprod operator </td></tr>
+<tr id="row_98_30_101_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_101_" class="arrow" onclick="toggleFolder('98_30_101_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterAddAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_101_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterAddAttrs.html" target="_self">tvm::relay::ScatterAddAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_102_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_102_" class="arrow" onclick="toggleFolder('98_30_102_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_102_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterAttrs.html" target="_self">tvm::relay::ScatterAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_103_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_103_" class="arrow" onclick="toggleFolder('98_30_103_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ScatterNDAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_103_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ScatterNDAttrs.html" target="_self">tvm::relay::ScatterNDAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_104_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_104_" class="arrow" onclick="toggleFolder('98_30_104_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SearchSortedAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_104_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SearchSortedAttrs.html" target="_self">tvm::relay::SearchSortedAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_105_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_105_" class="arrow" onclick="toggleFolder('98_30_105_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SequenceMaskAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_105_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SequenceMaskAttrs.html" target="_self">tvm::relay::SequenceMaskAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_106_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_106_" class="arrow" onclick="toggleFolder('98_30_106_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ShapeFuncAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_106_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ShapeFuncAttrs.html" target="_self">tvm::relay::ShapeFuncAttrs</a></td><td class="desc">Options for the shape function operator </td></tr>
+<tr id="row_98_30_107_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_107_" class="arrow" onclick="toggleFolder('98_30_107_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ShapeOfAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_107_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ShapeOfAttrs.html" target="_self">tvm::relay::ShapeOfAttrs</a></td><td class="desc">Attributes for ShapeOf operator </td></tr>
+<tr id="row_98_30_108_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_108_" class="arrow" onclick="toggleFolder('98_30_108_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SimulatedQuantizeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_108_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1qnn_1_1SimulatedQuantizeAttrs.html" target="_self">tvm::relay::qnn::SimulatedQuantizeAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_109_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_109_" class="arrow" onclick="toggleFolder('98_30_109_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SliceLikeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_109_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SliceLikeAttrs.html" target="_self">tvm::relay::SliceLikeAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_110_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_110_" class="arrow" onclick="toggleFolder('98_30_110_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SlidingWindowAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_110_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SlidingWindowAttrs.html" target="_self">tvm::relay::SlidingWindowAttrs</a></td><td class="desc">Attributes used for the sliding_window operator </td></tr>
+<tr id="row_98_30_111_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_111_" class="arrow" onclick="toggleFolder('98_30_111_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SoftmaxAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_111_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SoftmaxAttrs.html" target="_self">tvm::relay::SoftmaxAttrs</a></td><td class="desc">Attributes used in softmax operators </td></tr>
+<tr id="row_98_30_112_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_112_" class="arrow" onclick="toggleFolder('98_30_112_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SpaceToBatchNDAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_112_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SpaceToBatchNDAttrs.html" target="_self">tvm::relay::SpaceToBatchNDAttrs</a></td><td class="desc">Attributes used in SpaceToBatchND operator </td></tr>
+<tr id="row_98_30_113_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_113_" class="arrow" onclick="toggleFolder('98_30_113_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseConv2DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_113_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseConv2DAttrs.html" target="_self">tvm::relay::SparseConv2DAttrs</a></td><td class="desc">Attributes for sparse_dense operator </td></tr>
+<tr id="row_98_30_114_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_114_" class="arrow" onclick="toggleFolder('98_30_114_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseDenseAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_114_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseDenseAttrs.html" target="_self">tvm::relay::SparseDenseAttrs</a></td><td class="desc">Attributes for sparse_dense operator </td></tr>
+<tr id="row_98_30_115_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_115_" class="arrow" onclick="toggleFolder('98_30_115_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseToDenseAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_115_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseToDenseAttrs.html" target="_self">tvm::relay::SparseToDenseAttrs</a></td><td class="desc">Attributes used in sparse_to_dense operator </td></tr>
+<tr id="row_98_30_116_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_116_" class="arrow" onclick="toggleFolder('98_30_116_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SparseTransposeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_116_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SparseTransposeAttrs.html" target="_self">tvm::relay::SparseTransposeAttrs</a></td><td class="desc">Attributes for sparse_transpose operator </td></tr>
+<tr id="row_98_30_117_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_117_" class="arrow" onclick="toggleFolder('98_30_117_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SplitAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_117_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SplitAttrs.html" target="_self">tvm::relay::SplitAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_118_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_118_" class="arrow" onclick="toggleFolder('98_30_118_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SqueezeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_118_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SqueezeAttrs.html" target="_self">tvm::relay::SqueezeAttrs</a></td><td class="desc">Attributes used in squeeze operators </td></tr>
+<tr id="row_98_30_119_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_119_" class="arrow" onclick="toggleFolder('98_30_119_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< StackAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_119_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1StackAttrs.html" target="_self">tvm::relay::StackAttrs</a></td><td class="desc">Attributes used in stack operators </td></tr>
+<tr id="row_98_30_120_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_120_" class="arrow" onclick="toggleFolder('98_30_120_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< StridedSliceAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_120_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1StridedSliceAttrs.html" target="_self">tvm::relay::StridedSliceAttrs</a></td><td class="desc">Attributes for StridedSlice operator </td></tr>
+<tr id="row_98_30_121_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_121_" class="arrow" onclick="toggleFolder('98_30_121_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< SubPixelAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_121_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1SubPixelAttrs.html" target="_self">tvm::relay::SubPixelAttrs</a></td><td class="desc">Attributes used in subpixel operators </td></tr>
+<tr id="row_98_30_122_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_122_" class="arrow" onclick="toggleFolder('98_30_122_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TakeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_122_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TakeAttrs.html" target="_self">tvm::relay::TakeAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_123_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_123_" class="arrow" onclick="toggleFolder('98_30_123_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< ThreefryGenerateAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_123_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1ThreefryGenerateAttrs.html" target="_self">tvm::relay::ThreefryGenerateAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_124_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_124_" class="arrow" onclick="toggleFolder('98_30_124_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TileAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_124_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TileAttrs.html" target="_self">tvm::relay::TileAttrs</a></td><td class="desc">Attributes used in tile operators </td></tr>
+<tr id="row_98_30_125_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_125_" class="arrow" onclick="toggleFolder('98_30_125_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TopKAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_125_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TopKAttrs.html" target="_self">tvm::relay::TopKAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_126_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_126_" class="arrow" onclick="toggleFolder('98_30_126_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< TransposeAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_126_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1TransposeAttrs.html" target="_self">tvm::relay::TransposeAttrs</a></td><td class="desc">Attributes used in transpose operators </td></tr>
+<tr id="row_98_30_127_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_127_" class="arrow" onclick="toggleFolder('98_30_127_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UniformAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_127_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UniformAttrs.html" target="_self">tvm::relay::UniformAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_128_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_128_" class="arrow" onclick="toggleFolder('98_30_128_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UniqueAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_128_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UniqueAttrs.html" target="_self">tvm::relay::UniqueAttrs</a></td><td class="desc">Attributes used in unique operator </td></tr>
+<tr id="row_98_30_129_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_129_" class="arrow" onclick="toggleFolder('98_30_129_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UpSampling3DAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_129_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UpSampling3DAttrs.html" target="_self">tvm::relay::UpSampling3DAttrs</a></td><td class="desc">Attributes for upsampling3d operator </td></tr>
+<tr id="row_98_30_130_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_130_" class="arrow" onclick="toggleFolder('98_30_130_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< UpSamplingAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_130_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1UpSamplingAttrs.html" target="_self">tvm::relay::UpSamplingAttrs</a></td><td class="desc">Attributes for upsampling operator </td></tr>
+<tr id="row_98_30_131_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_131_" class="arrow" onclick="toggleFolder('98_30_131_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< VarianceAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_131_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1VarianceAttrs.html" target="_self">tvm::relay::VarianceAttrs</a></td><td class="desc"></td></tr>
+<tr id="row_98_30_132_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_132_" class="arrow" onclick="toggleFolder('98_30_132_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< VirtualDeviceNode ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_132_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1VirtualDeviceNode.html" target="_self">tvm::VirtualDeviceNode</a></td><td class="desc">Describes at compile time the constraints on where data is to be stored at runtime down to the (virtual) device and memory scope level, and how to compile code to compute that data. Used by the [...]
+<tr id="row_98_30_133_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_30_133_" class="arrow" onclick="toggleFolder('98_30_133_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< YoloReorgAttrs ></a></td><td class="desc"></td></tr>
+<tr id="row_98_30_133_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1relay_1_1YoloReorgAttrs.html" target="_self">tvm::relay::YoloReorgAttrs</a></td><td class="desc">Attributes used in yolo reorg operators </td></tr>
+<tr id="row_98_30_134_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1AttrsNode.html" target="_self">tvm::AttrsNode< DerivedType ></a></td><td class="desc">The base class of the all the Use "curiously recurring template pattern" </td></tr>
+<tr id="row_98_30_135_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1DictAttrsNode.html" target="_self">tvm::DictAttrsNode</a></td><td class="desc">Specialized attribute type that is backed by a map. The <a class="el" href="classtvm_1_1DictAttrsNode.html" title="Specialized attribute type that is backed by a map. The DictAttrsNode implements the Att [...]
<tr id="row_98_31_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_98_31_" class="arrow" onclick="toggleFolder('98_31_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1BaseExprNode.html" target="_self">tvm::BaseExprNode</a></td><td class="desc">Base type of all the expressions </td></tr>
<tr id="row_98_31_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_98_31_0_" class="arrow" onclick="toggleFolder('98_31_0_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1PrimExprNode.html" target="_self">tvm::PrimExprNode</a></td><td class="desc">Base node of all primitive expressions </td></tr>
<tr id="row_98_31_0_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_98_31_0_0_" class="arrow" onclick="toggleFolder('98_31_0_0_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1tir_1_1BinaryOpNode.html" target="_self">tvm::tir::BinaryOpNode< AddNode ></a></td><td class="desc"></td></tr>
@@ -1224,8 +1226,8 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_122_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_1relay_1_1PatternVisitor.html" target="_self">tvm::relay::PatternVisitor</a></td><td class="desc">A simple visitor wrapper around <a class="el" href="classtvm_1_1relay_1_1PatternFunctor.html" title="A dynamical functor on ADT patterns that dispatches on its first argument. You can use t [...]
<tr id="row_123_"><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_1profiling_1_1Profiler.html" target="_self">tvm::runtime::profiling::Profiler</a></td><td class="desc"></td></tr>
<tr id="row_124_" 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_1ReflectionVTable.html" target="_self">tvm::ReflectionVTable</a></td><td class="desc">Virtual function table to support IR/AST node reflection </td></tr>
-<tr id="row_125_"><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_1Registry.html" target="_self">tvm::runtime::Registry</a></td><td class="desc"><a class="el" href="classtvm_1_1runtime_1_1Registry.html" title="Registry for global function. ">Registry</a> for global function </td></tr>
-<tr id="row_126_" 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_1ReflectionVTable_1_1Registry.html" target="_self">tvm::ReflectionVTable::Registry</a></td><td class="desc"><a class="el" href="classtvm_1_1ReflectionVTable_1_1Registry.html" title="Registry of a reflection table. ">Registry</a> of a reflection table </td></tr>
+<tr id="row_125_"><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_1ReflectionVTable_1_1Registry.html" target="_self">tvm::ReflectionVTable::Registry</a></td><td class="desc"><a class="el" href="classtvm_1_1ReflectionVTable_1_1Registry.html" title="Registry of a reflection table. ">Registry</a> of a reflection table </td></tr>
+<tr id="row_126_" 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_1Registry.html" target="_self">tvm::runtime::Registry</a></td><td class="desc"><a class="el" href="classtvm_1_1runtime_1_1Registry.html" title="Registry for global function. ">Registry</a> for global function </td></tr>
<tr id="row_127_"><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_1ReprPrinter.html" target="_self">tvm::ReprPrinter</a></td><td class="desc">A printer class to print the AST/IR nodes </td></tr>
<tr id="row_128_" 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_1ReverseIterAdapter.html" target="_self">tvm::runtime::ReverseIterAdapter< Converter, TIter ></a></td><td class="desc">Iterator adapter that adapts TIter to return another type </td></tr>
<tr id="row_129_"><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_1arith_1_1RewriteSimplifier.html" target="_self">tvm::arith::RewriteSimplifier</a></td><td class="desc">Rewrite-rule based simplifier </td></tr>
@@ -1259,8 +1261,8 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_153_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_153_" class="arrow" onclick="toggleFolder('153_')">►</span><span class="icona"><span class="icon">C</span></span><b>true_type</b></td><td class="desc"></td></tr>
<tr id="row_153_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="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_154_" 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__workspace__t.html" target="_self">tvm_workspace_t</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="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_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="structTVMArgs.html" target="_self">TVMArgs</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="structTVMArgs.html" target="_self">TVMArgs</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="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_1TVMArgsSetter.html" target="_self">tvm::runtime::TVMArgsSetter</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="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_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="structTVMFuncRegistry.html" target="_self">TVMFuncRegistry</a></td><td class="desc">A data structure that facilitates function lookup by C-string name </td></tr>
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index d78a8cc9b..755258c4b 100644
--- a/docs/reference/api/doxygen/inherit_graph_10.svg
+++ b/docs/reference/api/doxygen/inherit_graph_10.svg
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+<title>Node1212</title>
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</a>
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-<!-- Node1208->Node1210 -->
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<g id="edge2" class="edge">
-<title>Node1208->Node1210</title>
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index 548411798..601029b72 100644
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+++ b/docs/reference/api/doxygen/inherit_graph_107.svg
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<title>Graphical Class Hierarchy</title>
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+<title>Node1220</title>
<g id="a_node1"><a xlink:href="classtvm_1_1runtime_1_1NDArray_1_1ContainerBase.html" target="_top" xlink:title="The container base structure contains all the fields except for the Object header. ">
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</a>
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+<polygon fill="#ffffff" stroke="#000000" points="241,-9617 241,-9647 369,-9647 369,-9617 241,-9617"/>
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-<!-- Node1165 -->
+<!-- Node1167 -->
<g id="node3" class="node">
-<title>Node1165</title>
+<title>Node1167</title>
<g id="a_node3"><a xlink:href="classtvm_1_1runtime_1_1InplaceArrayBase.html" target="_top" xlink:title="Base template for classes with array like memory layout. ">
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@@ -45,70 +45,70 @@
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<g id="node4" class="node">
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+<text text-anchor="start" x="15.5" y="-9588" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::InplaceArray</text>
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-<text text-anchor="middle" x="305" y="-1546.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TimerNode</text>
-</a>
-</g>
-</g>
-<!-- Node0->Node512 -->
-<g id="edge516" class="edge">
-<title>Node0->Node512</title>
-<path fill="none" stroke="#191970" d="M84.7351,-3233.8338C91.6065,-3047.6444 145.6412,-1633.4807 204,-1568 212.1318,-1558.8758 223.1432,-1553.2742 234.911,-1549.9632"/>
-<polygon fill="#191970" stroke="#191970" points="81.2277,-3233.9715 84.3585,-3244.0932 88.223,-3234.2284 81.2277,-3233.9715"/>
-</g>
-<!-- Node513 -->
-<g id="node518" class="node">
-<title>Node513</title>
-<g id="a_node518"><a xlink:href="classtvm_1_1runtime_1_1vm_1_1StorageObj.html" target="_top" xlink:title="An object representing a storage allocation. ">
-<polygon fill="#ffffff" stroke="#000000" points="224,-1501.5 224,-1520.5 386,-1520.5 386,-1501.5 224,-1501.5"/>
-<text text-anchor="middle" x="305" y="-1508.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::vm::StorageObj</text>
+<g id="a_node517"><a xlink:href="classtvm_1_1runtime_1_1StringObj.html" target="_top" xlink:title="An object representing string. It's POD type. ">
+<polygon fill="#ffffff" stroke="#000000" points="239.5,-1577.5 239.5,-1596.5 370.5,-1596.5 370.5,-1577.5 239.5,-1577.5"/>
+<text text-anchor="middle" x="305" y="-1584.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::StringObj</text>
</a>
</g>
</g>
-<!-- Node0->Node513 -->
-<g id="edge517" class="edge">
-<title>Node0->Node513</title>
-<path fill="none" stroke="#191970" d="M84.6883,-3234.2408C91.2796,-3047.4058 144.2939,-1597.0978 204,-1530 209.456,-1523.8686 216.2123,-1519.3271 223.6254,-1516.0023"/>
-<polygon fill="#191970" stroke="#191970" points="81.1886,-3234.1737 84.3357,-3244.2903 88.1843,-3234.4192 81.1886,-3234.1737"/>
+<!-- Node0->Node512 -->
+<g id="edge516" class="edge">
+<title>Node0->Node512</title>
+<path fill="none" stroke="#191970" d="M84.7514,-3234.2878C91.7722,-3052.2902 146.8975,-1669.9658 204,-1606 213.1492,-1595.7511 225.932,-1589.9486 239.3348,-1586.845"/>
+<polygon fill="#191970" stroke="#191970" points="81.2527,-3234.1894 84.3666,-3244.3163 88.2476,-3234.4579 81.2527,-3234.1894"/>
</g>
<!-- Node514 -->
<g id="node519" class="node">
<title>Node514</title>
-<g id="a_node519"><a xlink:href="classtvm_1_1SourceNameNode.html" target="_top" xlink:title="The name of a source fragment. ">
-<polygon fill="#ffffff" stroke="#000000" points="240,-1463.5 240,-1482.5 370,-1482.5 370,-1463.5 240,-1463.5"/>
-<text text-anchor="middle" x="305" y="-1470.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::SourceNameNode</text>
+<g id="a_node519"><a xlink:href="classtvm_1_1runtime_1_1TimerNode.html" target="_top" xlink:title="Base class for all implementations. ">
+<polygon fill="#ffffff" stroke="#000000" points="235,-1539.5 235,-1558.5 375,-1558.5 375,-1539.5 235,-1539.5"/>
+<text text-anchor="middle" x="305" y="-1546.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::TimerNode</text>
</a>
</g>
</g>
<!-- Node0->Node514 -->
<g id="edge518" class="edge">
<title>Node0->Node514</title>
-<path fill="none" stroke="#191970" d="M84.6529,-3234.3874C91.011,-3045.8897 142.973,-1560.6854 204,-1492 213.2437,-1481.5963 226.2308,-1475.7685 239.822,-1472.694"/>
-<polygon fill="#191970" stroke="#191970" points="81.1511,-3234.3853 84.3139,-3244.4971 88.1472,-3234.62 81.1511,-3234.3853"/>
+<path fill="none" stroke="#191970" d="M84.7351,-3233.8338C91.6065,-3047.6444 145.6412,-1633.4807 204,-1568 212.1318,-1558.8758 223.1432,-1553.2742 234.911,-1549.9632"/>
+<polygon fill="#191970" stroke="#191970" points="81.2277,-3233.9715 84.3585,-3244.0932 88.223,-3234.2284 81.2277,-3233.9715"/>
</g>
<!-- Node515 -->
<g id="node520" class="node">
<title>Node515</title>
-<g id="a_node520"><a xlink:href="classtvm_1_1SpanNode.html" target="_top" xlink:title="Stores locations in frontend source that generated a node. ">
-<polygon fill="#ffffff" stroke="#000000" points="259,-1425.5 259,-1444.5 351,-1444.5 351,-1425.5 259,-1425.5"/>
-<text text-anchor="middle" x="305" y="-1432.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::SpanNode</text>
+<g id="a_node520"><a xlink:href="classtvm_1_1runtime_1_1vm_1_1StorageObj.html" target="_top" xlink:title="An object representing a storage allocation. ">
+<polygon fill="#ffffff" stroke="#000000" points="224,-1501.5 224,-1520.5 386,-1520.5 386,-1501.5 224,-1501.5"/>
+<text text-anchor="middle" x="305" y="-1508.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::runtime::vm::StorageObj</text>
</a>
</g>
</g>
<!-- Node0->Node515 -->
<g id="edge519" class="edge">
<title>Node0->Node515</title>
-<path fill="none" stroke="#191970" d="M84.6284,-3234.2519C90.8002,-3042.9194 141.6821,-1524.2395 204,-1454 217.5583,-1438.7182 239.193,-1433.3056 258.9672,-1431.9909"/>
-<polygon fill="#191970" stroke="#191970" points="81.1289,-3234.1853 84.3064,-3244.2923 88.1253,-3234.4097 81.1289,-3234.1853"/>
+<path fill="none" stroke="#191970" d="M84.6883,-3234.2408C91.2796,-3047.4058 144.2939,-1597.0978 204,-1530 209.456,-1523.8686 216.2123,-1519.3271 223.6254,-1516.0023"/>
+<polygon fill="#191970" stroke="#191970" points="81.1886,-3234.1737 84.3357,-3244.2903 88.1843,-3234.4192 81.1886,-3234.1737"/>
</g>
<!-- Node516 -->
<g id="node521" class="node">
<title>Node516</title>
-<g id="a_node521"><a xlink:href="classtvm_1_1TargetKindNode.html" target="_top" xlink:title="Target kind, specifies the kind of the target. ">
-<polygon fill="#ffffff" stroke="#000000" points="245.5,-1387.5 245.5,-1406.5 364.5,-1406.5 364.5,-1387.5 245.5,-1387.5"/>
-<text text-anchor="middle" x="305" y="-1394.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetKindNode</text>
+<g id="a_node521"><a xlink:href="classtvm_1_1SourceNameNode.html" target="_top" xlink:title="The name of a source fragment. ">
+<polygon fill="#ffffff" stroke="#000000" points="240,-1463.5 240,-1482.5 370,-1482.5 370,-1463.5 240,-1463.5"/>
+<text text-anchor="middle" x="305" y="-1470.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::SourceNameNode</text>
</a>
</g>
</g>
<!-- Node0->Node516 -->
<g id="edge520" class="edge">
<title>Node0->Node516</title>
-<path fill="none" stroke="#191970" d="M84.6134,-3233.8354C90.6411,-3038.4679 140.4215,-1487.7595 204,-1416 214.4715,-1404.1811 229.7735,-1398.2632 245.3147,-1395.5787"/>
-<polygon fill="#191970" stroke="#191970" points="81.1072,-3233.985 84.299,-3244.0876 88.1039,-3234.1996 81.1072,-3233.985"/>
+<path fill="none" stroke="#191970" d="M84.6529,-3234.3874C91.011,-3045.8897 142.973,-1560.6854 204,-1492 213.2437,-1481.5963 226.2308,-1475.7685 239.822,-1472.694"/>
+<polygon fill="#191970" stroke="#191970" points="81.1511,-3234.3853 84.3139,-3244.4971 88.1472,-3234.62 81.1511,-3234.3853"/>
</g>
<!-- Node517 -->
<g id="node522" class="node">
<title>Node517</title>
-<g id="a_node522"><a xlink:href="classtvm_1_1TargetNode.html" target="_top" xlink:title="Compilation target. ">
-<polygon fill="#ffffff" stroke="#000000" points="256,-1349.5 256,-1368.5 354,-1368.5 354,-1349.5 256,-1349.5"/>
-<text text-anchor="middle" x="305" y="-1356.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetNode</text>
+<g id="a_node522"><a xlink:href="classtvm_1_1SpanNode.html" target="_top" xlink:title="Stores locations in frontend source that generated a node. ">
+<polygon fill="#ffffff" stroke="#000000" points="259,-1425.5 259,-1444.5 351,-1444.5 351,-1425.5 259,-1425.5"/>
+<text text-anchor="middle" x="305" y="-1432.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::SpanNode</text>
</a>
</g>
</g>
<!-- Node0->Node517 -->
<g id="edge521" class="edge">
<title>Node0->Node517</title>
-<path fill="none" stroke="#191970" d="M84.5718,-3234.3188C90.3341,-3038.8321 139.0622,-1451.391 204,-1378 216.8284,-1363.5017 236.9253,-1357.88 255.8253,-1356.215"/>
-<polygon fill="#191970" stroke="#191970" points="81.0732,-3234.223 84.2788,-3244.3212 88.0702,-3234.428 81.0732,-3234.223"/>
+<path fill="none" stroke="#191970" d="M84.6284,-3234.2519C90.8002,-3042.9194 141.6821,-1524.2395 204,-1454 217.5583,-1438.7182 239.193,-1433.3056 258.9672,-1431.9909"/>
+<polygon fill="#191970" stroke="#191970" points="81.1289,-3234.1853 84.3064,-3244.2923 88.1253,-3234.4097 81.1289,-3234.1853"/>
</g>
<!-- Node518 -->
<g id="node523" class="node">
<title>Node518</title>
-<g id="a_node523"><a xlink:href="classtvm_1_1TargetTagNode.html" target="_top" xlink:title="A target tag. ">
-<polygon fill="#ffffff" stroke="#000000" points="248,-1311.5 248,-1330.5 362,-1330.5 362,-1311.5 248,-1311.5"/>
-<text text-anchor="middle" x="305" y="-1318.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetTagNode</text>
+<g id="a_node523"><a xlink:href="classtvm_1_1TargetKindNode.html" target="_top" xlink:title="Target kind, specifies the kind of the target. ">
+<polygon fill="#ffffff" stroke="#000000" points="245.5,-1387.5 245.5,-1406.5 364.5,-1406.5 364.5,-1387.5 245.5,-1387.5"/>
+<text text-anchor="middle" x="305" y="-1394.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetKindNode</text>
</a>
</g>
</g>
<!-- Node0->Node518 -->
<g id="edge522" class="edge">
<title>Node0->Node518</title>
-<path fill="none" stroke="#191970" d="M84.5574,-3233.9205C90.1784,-3034.4782 137.7995,-1414.9134 204,-1340 215.0469,-1327.4991 231.4975,-1321.5952 247.9308,-1319.137"/>
-<polygon fill="#191970" stroke="#191970" points="81.053,-3234.0313 84.2716,-3244.1254 88.0503,-3234.2273 81.053,-3234.0313"/>
+<path fill="none" stroke="#191970" d="M84.6134,-3233.8354C90.6411,-3038.4679 140.4215,-1487.7595 204,-1416 214.4715,-1404.1811 229.7735,-1398.2632 245.3147,-1395.5787"/>
+<polygon fill="#191970" stroke="#191970" points="81.1072,-3233.985 84.299,-3244.0876 88.1039,-3234.1996 81.1072,-3233.985"/>
</g>
<!-- Node519 -->
<g id="node524" class="node">
<title>Node519</title>
-<g id="a_node524"><a xlink:href="classtvm_1_1te_1_1IterVarAttrNode.html" target="_top" xlink:title="node container for IterVar attr ">
-<polygon fill="#ffffff" stroke="#000000" points="238,-1273.5 238,-1292.5 372,-1292.5 372,-1273.5 238,-1273.5"/>
-<text text-anchor="middle" x="305" y="-1280.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::IterVarAttrNode</text>
+<g id="a_node524"><a xlink:href="classtvm_1_1TargetNode.html" target="_top" xlink:title="Compilation target. ">
+<polygon fill="#ffffff" stroke="#000000" points="256,-1349.5 256,-1368.5 354,-1368.5 354,-1349.5 256,-1349.5"/>
+<text text-anchor="middle" x="305" y="-1356.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetNode</text>
</a>
</g>
</g>
<!-- Node0->Node519 -->
<g id="edge523" class="edge">
<title>Node0->Node519</title>
-<path fill="none" stroke="#191970" d="M84.5263,-3234.1404C89.9278,-3033.4966 136.4679,-1378.514 204,-1302 212.7961,-1292.0341 225.0262,-1286.2595 237.9468,-1283.0808"/>
-<polygon fill="#191970" stroke="#191970" points="81.0213,-3234.2858 84.2527,-3244.3758 88.0188,-3234.4729 81.0213,-3234.2858"/>
+<path fill="none" stroke="#191970" d="M84.5718,-3234.3188C90.3341,-3038.8321 139.0622,-1451.391 204,-1378 216.8284,-1363.5017 236.9253,-1357.88 255.8253,-1356.215"/>
+<polygon fill="#191970" stroke="#191970" points="81.0732,-3234.223 84.2788,-3244.3212 88.0702,-3234.428 81.0732,-3234.223"/>
</g>
<!-- Node520 -->
<g id="node525" class="node">
<title>Node520</title>
-<g id="a_node525"><a xlink:href="classtvm_1_1te_1_1IterVarRelationNode.html" target="_top" xlink:title="base node of iteration var ">
-<polygon fill="#ffffff" stroke="#000000" points="227.5,-1235.5 227.5,-1254.5 382.5,-1254.5 382.5,-1235.5 227.5,-1235.5"/>
-<text text-anchor="middle" x="305" y="-1242.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::IterVarRelationNode</text>
+<g id="a_node525"><a xlink:href="classtvm_1_1TargetTagNode.html" target="_top" xlink:title="A target tag. ">
+<polygon fill="#ffffff" stroke="#000000" points="248,-1311.5 248,-1330.5 362,-1330.5 362,-1311.5 248,-1311.5"/>
+<text text-anchor="middle" x="305" y="-1318.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::TargetTagNode</text>
</a>
</g>
</g>
<!-- Node0->Node520 -->
<g id="edge524" class="edge">
<title>Node0->Node520</title>
-<path fill="none" stroke="#191970" d="M84.5045,-3234.0587C89.729,-3030.8891 135.1695,-1342.0771 204,-1264 210.3714,-1256.7726 218.5489,-1251.7489 227.4869,-1248.3208"/>
-<polygon fill="#191970" stroke="#191970" points="81.0024,-3234.1025 84.2458,-3244.1886 88.0001,-3234.2812 81.0024,-3234.1025"/>
+<path fill="none" stroke="#191970" d="M84.5574,-3233.9205C90.1784,-3034.4782 137.7995,-1414.9134 204,-1340 215.0469,-1327.4991 231.4975,-1321.5952 247.9308,-1319.137"/>
+<polygon fill="#191970" stroke="#191970" points="81.053,-3234.0313 84.2716,-3244.1254 88.0503,-3234.2273 81.053,-3234.0313"/>
</g>
-<!-- Node526 -->
-<g id="node531" class="node">
-<title>Node526</title>
-<g id="a_node531"><a xlink:href="classtvm_1_1te_1_1OperationNode.html" target="_top" xlink:title="Base class of all operation nodes. ">
-<polygon fill="#ffffff" stroke="#000000" points="239.5,-1197.5 239.5,-1216.5 370.5,-1216.5 370.5,-1197.5 239.5,-1197.5"/>
-<text text-anchor="middle" x="305" y="-1204.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::OperationNode</text>
+<!-- Node521 -->
+<g id="node526" class="node">
+<title>Node521</title>
+<g id="a_node526"><a xlink:href="classtvm_1_1te_1_1IterVarAttrNode.html" target="_top" xlink:title="node container for IterVar attr ">
+<polygon fill="#ffffff" stroke="#000000" points="238,-1273.5 238,-1292.5 372,-1292.5 372,-1273.5 238,-1273.5"/>
+<text text-anchor="middle" x="305" y="-1280.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::IterVarAttrNode</text>
</a>
</g>
</g>
-<!-- Node0->Node526 -->
-<g id="edge530" class="edge">
-<title>Node0->Node526</title>
-<path fill="none" stroke="#191970" d="M84.4753,-3234.3067C89.4863,-3030.1432 133.8332,-1305.6833 204,-1226 213.1384,-1215.6222 226.0002,-1209.7866 239.4935,-1206.694"/>
-<polygon fill="#191970" stroke="#191970" points="80.9728,-3234.3725 84.2281,-3244.4548 87.9707,-3234.5431 80.9728,-3234.3725"/>
+<!-- Node0->Node521 -->
+<g id="edge525" class="edge">
+<title>Node0->Node521</title>
+<path fill="none" stroke="#191970" d="M84.5263,-3234.1404C89.9278,-3033.4966 136.4679,-1378.514 204,-1302 212.7961,-1292.0341 225.0262,-1286.2595 237.9468,-1283.0808"/>
+<polygon fill="#191970" stroke="#191970" points="81.0213,-3234.2858 84.2527,-3244.3758 88.0188,-3234.4729 81.0213,-3234.2858"/>
</g>
-<!-- Node534 -->
-<g id="node539" class="node">
-<title>Node534</title>
-<g id="a_node539"><a xlink:href="classtvm_1_1te_1_1ScheduleNode.html" target="_top" xlink:title="node container for schedule ">
-<polygon fill="#ffffff" stroke="#000000" points="241,-1159.5 241,-1178.5 369,-1178.5 369,-1159.5 241,-1159.5"/>
-<text text-anchor="middle" x="305" y="-1166.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::ScheduleNode</text>
+<!-- Node522 -->
+<g id="node527" class="node">
+<title>Node522</title>
+<g id="a_node527"><a xlink:href="classtvm_1_1te_1_1IterVarRelationNode.html" target="_top" xlink:title="base node of iteration var ">
+<polygon fill="#ffffff" stroke="#000000" points="227.5,-1235.5 227.5,-1254.5 382.5,-1254.5 382.5,-1235.5 227.5,-1235.5"/>
+<text text-anchor="middle" x="305" y="-1242.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::IterVarRelationNode</text>
</a>
</g>
</g>
-<!-- Node0->Node534 -->
-<g id="edge538" class="edge">
-<title>Node0->Node534</title>
-<path fill="none" stroke="#191970" d="M84.4547,-3234.2475C89.2932,-3027.7019 132.5315,-1269.2504 204,-1188 213.4273,-1177.2824 226.8259,-1171.4078 240.793,-1168.396"/>
-<polygon fill="#191970" stroke="#191970" points="80.955,-3234.1974 84.2216,-3244.2761 87.9532,-3234.3602 80.955,-3234.1974"/>
+<!-- Node0->Node522 -->
+<g id="edge526" class="edge">
+<title>Node0->Node522</title>
+<path fill="none" stroke="#191970" d="M84.5045,-3234.0587C89.729,-3030.8891 135.1695,-1342.0771 204,-1264 210.3714,-1256.7726 218.5489,-1251.7489 227.4869,-1248.3208"/>
+<polygon fill="#191970" stroke="#191970" points="81.0024,-3234.1025 84.2458,-3244.1886 88.0001,-3234.2812 81.0024,-3234.1025"/>
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-<!-- Node535 -->
-<g id="node540" class="node">
-<title>Node535</title>
-<g id="a_node540"><a xlink:href="classtvm_1_1te_1_1SpecializedConditionNode.html" target="_top" xlink:title="Container for specialization conditions. ">
-<polygon fill="#ffffff" stroke="#000000" points="212.5,-1121.5 212.5,-1140.5 397.5,-1140.5 397.5,-1121.5 212.5,-1121.5"/>
-<text text-anchor="middle" x="305" y="-1128.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::SpecializedConditionNode</text>
+<!-- Node528 -->
+<g id="node533" class="node">
+<title>Node528</title>
+<g id="a_node533"><a xlink:href="classtvm_1_1te_1_1OperationNode.html" target="_top" xlink:title="Base class of all operation nodes. ">
+<polygon fill="#ffffff" stroke="#000000" points="239.5,-1197.5 239.5,-1216.5 370.5,-1216.5 370.5,-1197.5 239.5,-1197.5"/>
+<text text-anchor="middle" x="305" y="-1204.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::te::OperationNode</text>
</a>
</g>
</g>
-<!-- Node0->Node535 -->
-<g id="edge539" class="edge">
-<title>Node0->Node535</title>
-<path fill="none" stroke="#191970" d="M84.4416,-3233.8845C89.1442,-3023.5435 131.2646,-1232.7779 204,-1150 207.1798,-1146.3811 210.8124,-1143.3143 214.7669,-1140.7232"/>
-<polygon fill="#191970" stroke="#191970" points="80.9378,-3234.0223 84.215,-3244.0975 87.936,-3234.1776 80.9378,-3234.0223"/>
+<!-- Node0->Node528 -->
+<g id="edge532" class="edge">
+<title>Node0->Node528</title>
+<path fill="none" stroke="#191970" d="M84.4753,-3234.3067C89.4863,-3030.1432 133.8332,-1305.6833 204,-1226 213.1384,-1215.6222 226.0002,-1209.7866 239.4935,-1206.694"/>
+<polygon fill="#191970" stroke="#191970" points="80.9728,-3234.3725 84.2281,-3244.4548 87.9707,-3234.5431 80.9728,-3234.3725"/>
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<!-- Node536 -->
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<g id="a_node93"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< BatchMatmul\lAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-6643" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">NDAttrs ></text>
+<polygon fill="#ffffff" stroke="#000000" points="454.5,-6785 454.5,-6815 624.5,-6815 624.5,-6785 454.5,-6785"/>
+<text text-anchor="start" x="462.5" y="-6803" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BatchToSpace</text>
+<text text-anchor="middle" x="539.5" y="-6792" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">NDAttrs ></text>
</a>
</g>
</g>
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<g id="edge92" class="edge">
<title>Node55->Node88</title>
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-<polygon fill="#191970" stroke="#191970" points="373.2537,-6131.902 362.7581,-6133.3487 371.8651,-6138.7629 373.2537,-6131.902"/>
+<path fill="none" stroke="#191970" d="M372.4646,-6169.1817C385.2335,-6172.3814 397.2978,-6178.139 406,-6188 492.4741,-6285.9897 358.7586,-6674.2497 442,-6775 445.5617,-6779.3109 449.7564,-6782.9346 454.3702,-6785.9757"/>
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<!-- Node90 -->
<g id="node99" class="node">
<title>Node90</title>
<g id="a_node99"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< BiasAddAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-6604.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BiasAddAttrs ></text>
+<polygon fill="#ffffff" stroke="#000000" points="451.5,-6746.5 451.5,-6765.5 627.5,-6765.5 627.5,-6746.5 451.5,-6746.5"/>
+<text text-anchor="middle" x="539.5" y="-6753.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BiasAddAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node90 -->
<g id="edge94" class="edge">
<title>Node55->Node90</title>
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-<polygon fill="#191970" stroke="#191970" points="373.2023,-6131.9474 362.7068,-6133.3948 371.8142,-6138.8084 373.2023,-6131.9474"/>
+<path fill="none" stroke="#191970" d="M372.432,-6169.2105C385.203,-6172.4083 397.2764,-6178.1579 406,-6188 486.9498,-6279.3289 361.8007,-6644.0114 442,-6736 445.6337,-6740.1679 449.8824,-6743.6063 454.5356,-6746.4324"/>
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<!-- Node92 -->
<g id="node101" class="node">
<title>Node92</title>
<g id="a_node101"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< BinaryConv2\lDAttrs \>">
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-<text text-anchor="start" x="465.5" y="-6566" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BinaryConv2</text>
-<text text-anchor="middle" x="539.5" y="-6555" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DAttrs ></text>
+<polygon fill="#ffffff" stroke="#000000" points="457.5,-6697 457.5,-6727 621.5,-6727 621.5,-6697 457.5,-6697"/>
+<text text-anchor="start" x="465.5" y="-6715" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BinaryConv2</text>
+<text text-anchor="middle" x="539.5" y="-6704" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node92 -->
<g id="edge96" class="edge">
<title>Node55->Node92</title>
-<path fill="none" stroke="#191970" d="M372.4319,-6135.4488C385.1399,-6138.6446 397.188,-6144.333 406,-6154 463.7386,-6217.3406 386.352,-6472.8151 442,-6538 446.3115,-6543.0503 451.4912,-6547.1522 457.1865,-6550.4759"/>
-<polygon fill="#191970" stroke="#191970" points="373.1234,-6132.0179 362.628,-6133.4663 371.7359,-6138.879 373.1234,-6132.0179"/>
+<path fill="none" stroke="#191970" d="M372.384,-6169.2532C385.1581,-6172.4483 397.2449,-6178.186 406,-6188 480.0109,-6270.9622 370.7264,-6601.6746 442,-6687 446.257,-6692.0963 451.3985,-6696.2305 457.0681,-6699.5759"/>
+<polygon fill="#191970" stroke="#191970" points="373.0179,-6165.8107 362.5255,-6167.2801 371.6441,-6172.6746 373.0179,-6165.8107"/>
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<!-- Node94 -->
<g id="node103" class="node">
<title>Node94</title>
<g id="a_node103"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< BinaryDense\lAttrs \>">
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-<text text-anchor="start" x="465.5" y="-6517" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BinaryDense</text>
-<text text-anchor="middle" x="539.5" y="-6506" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<polygon fill="#ffffff" stroke="#000000" points="457.5,-6648 457.5,-6678 621.5,-6678 621.5,-6648 457.5,-6648"/>
+<text text-anchor="start" x="465.5" y="-6666" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BinaryDense</text>
+<text text-anchor="middle" x="539.5" y="-6655" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node94 -->
<g id="edge98" class="edge">
<title>Node55->Node94</title>
-<path fill="none" stroke="#191970" d="M372.3319,-6135.5405C385.0465,-6138.7303 397.1226,-6144.393 406,-6154 507.6283,-6263.9799 344.0023,-6375.773 442,-6489 446.3456,-6494.021 451.5494,-6498.1022 457.2609,-6501.412"/>
-<polygon fill="#191970" stroke="#191970" points="373.0222,-6132.1093 362.527,-6133.559 371.6355,-6138.9706 373.0222,-6132.1093"/>
+<path fill="none" stroke="#191970" d="M372.533,-6169.3573C385.2343,-6172.5591 397.2541,-6178.2731 406,-6188 473.0748,-6262.5987 377.3869,-6561.2593 442,-6638 446.2769,-6643.0796 451.4324,-6647.2021 457.1114,-6650.5396"/>
+<polygon fill="#191970" stroke="#191970" points="373.2258,-6165.9266 362.7303,-6167.3737 371.8374,-6172.7876 373.2258,-6165.9266"/>
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<!-- Node96 -->
<g id="node105" class="node">
<title>Node96</title>
<g id="a_node105"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< BitPackAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-6467.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BitPackAttrs ></text>
+<polygon fill="#ffffff" stroke="#000000" points="453,-6609.5 453,-6628.5 626,-6628.5 626,-6609.5 453,-6609.5"/>
+<text text-anchor="middle" x="539.5" y="-6616.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< BitPackAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node96 -->
<g id="edge100" class="edge">
<title>Node55->Node96</title>
-<path fill="none" stroke="#191970" d="M372.8088,-6135.7824C385.3179,-6138.9912 397.1915,-6144.6002 406,-6154 496.6187,-6250.7011 352.1761,-6352.5601 442,-6450 445.8649,-6454.1926 450.3536,-6457.6367 455.2409,-6460.4555"/>
-<polygon fill="#191970" stroke="#191970" points="373.1875,-6132.287 362.6869,-6133.697 371.7749,-6139.143 373.1875,-6132.287"/>
+<path fill="none" stroke="#191970" d="M372.4771,-6169.4078C385.1821,-6172.6062 397.2175,-6178.3061 406,-6188 467.5569,-6255.945 381.0015,-6530.5532 442,-6599 445.6789,-6603.1281 449.9614,-6606.5366 454.6393,-6609.341"/>
+<polygon fill="#191970" stroke="#191970" points="373.1692,-6165.9769 362.6737,-6167.4247 371.7813,-6172.838 373.1692,-6165.9769"/>
</g>
<!-- Node98 -->
<g id="node107" class="node">
<title>Node98</title>
-<g id="a_node107"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CallLowered\lAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="458.5,-6411 458.5,-6441 620.5,-6441 620.5,-6411 458.5,-6411"/>
-<text text-anchor="start" x="466.5" y="-6429" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CallLowered</text>
-<text text-anchor="middle" x="539.5" y="-6418" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node107"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Broadcast\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="464,-6560 464,-6590 615,-6590 615,-6560 464,-6560"/>
+<text text-anchor="start" x="472" y="-6578" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Broadcast</text>
+<text text-anchor="middle" x="539.5" y="-6567" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node98 -->
<g id="edge102" class="edge">
<title>Node55->Node98</title>
-<path fill="none" stroke="#191970" d="M372.6375,-6135.9448C385.1588,-6139.1421 397.0807,-6144.7053 406,-6154 482.8116,-6234.0446 367.8323,-6318.4996 442,-6401 446.6731,-6406.1981 452.2662,-6410.3822 458.3778,-6413.7422"/>
-<polygon fill="#191970" stroke="#191970" points="373.0132,-6132.4489 362.513,-6133.8619 371.6026,-6139.3053 373.0132,-6132.4489"/>
+<path fill="none" stroke="#191970" d="M372.3903,-6169.4869C385.101,-6172.6801 397.1607,-6178.3579 406,-6188 460.6287,-6247.5903 389.3382,-6488.6645 442,-6550 447.9194,-6556.8943 455.4568,-6562.0193 463.7108,-6565.8093"/>
+<polygon fill="#191970" stroke="#191970" points="373.0812,-6166.0558 362.5859,-6167.5047 371.694,-6172.917 373.0812,-6166.0558"/>
</g>
<!-- Node100 -->
<g id="node109" class="node">
<title>Node100</title>
-<g id="a_node109"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CastAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="460.5,-6372.5 460.5,-6391.5 618.5,-6391.5 618.5,-6372.5 460.5,-6372.5"/>
-<text text-anchor="middle" x="539.5" y="-6379.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CastAttrs ></text>
+<g id="a_node109"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CallLowered\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="458.5,-6511 458.5,-6541 620.5,-6541 620.5,-6511 458.5,-6511"/>
+<text text-anchor="start" x="466.5" y="-6529" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CallLowered</text>
+<text text-anchor="middle" x="539.5" y="-6518" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node100 -->
<g id="edge104" class="edge">
<title>Node55->Node100</title>
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-<polygon fill="#191970" stroke="#191970" points="373.0856,-6132.6976 362.583,-6134.0923 371.663,-6139.5516 373.0856,-6132.6976"/>
+<path fill="none" stroke="#191970" d="M372.8562,-6169.7381C385.3619,-6172.9501 397.2221,-6178.5716 406,-6188 501.416,-6290.4875 349.9676,-6395.4636 442,-6501 446.594,-6506.2681 452.1328,-6510.5003 458.2089,-6513.8917"/>
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</g>
<!-- Node102 -->
<g id="node111" class="node">
<title>Node102</title>
-<g id="a_node111"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CastHint\lAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="467.5,-6323 467.5,-6353 611.5,-6353 611.5,-6323 467.5,-6323"/>
-<text text-anchor="start" x="475.5" y="-6341" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CastHint</text>
-<text text-anchor="middle" x="539.5" y="-6330" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node111"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CastAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="460.5,-6472.5 460.5,-6491.5 618.5,-6491.5 618.5,-6472.5 460.5,-6472.5"/>
+<text text-anchor="middle" x="539.5" y="-6479.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CastAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node102 -->
<g id="edge106" class="edge">
<title>Node55->Node102</title>
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-<polygon fill="#191970" stroke="#191970" points="373.2512,-6133.1884 362.7441,-6134.5485 371.806,-6140.0376 373.2512,-6133.1884"/>
+<path fill="none" stroke="#191970" d="M372.7391,-6169.848C385.2532,-6173.0522 397.1464,-6178.6427 406,-6188 490.4153,-6277.2181 358.318,-6372.0937 442,-6462 447.18,-6467.5653 453.4597,-6471.8084 460.3079,-6475.0193"/>
+<polygon fill="#191970" stroke="#191970" points="373.1166,-6166.3524 362.6162,-6167.7636 371.7048,-6173.2086 373.1166,-6166.3524"/>
</g>
<!-- Node104 -->
<g id="node113" class="node">
<title>Node104</title>
-<g id="a_node113"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ClipAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="462,-6284.5 462,-6303.5 617,-6303.5 617,-6284.5 462,-6284.5"/>
-<text text-anchor="middle" x="539.5" y="-6291.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ClipAttrs ></text>
+<g id="a_node113"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CastHint\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="467.5,-6423 467.5,-6453 611.5,-6453 611.5,-6423 467.5,-6423"/>
+<text text-anchor="start" x="475.5" y="-6441" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CastHint</text>
+<text text-anchor="middle" x="539.5" y="-6430" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node104 -->
<g id="edge108" class="edge">
<title>Node55->Node104</title>
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-<polygon fill="#191970" stroke="#191970" points="373.0402,-6133.7506 362.532,-6135.103 371.59,-6140.5987 373.0402,-6133.7506"/>
+<path fill="none" stroke="#191970" d="M372.7431,-6170.0937C385.1967,-6173.2922 397.0653,-6178.8181 406,-6188 476.6263,-6260.5805 373.7716,-6338.1609 442,-6413 448.946,-6420.619 457.8692,-6426.0541 467.4892,-6429.9071"/>
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</g>
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<g id="node115" class="node">
<title>Node106</title>
-<g id="a_node115"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Compiler\lAttrs \>">
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-<text text-anchor="start" x="474.5" y="-6253" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Compiler</text>
-<text text-anchor="middle" x="539.5" y="-6242" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node115"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ClipAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="462,-6384.5 462,-6403.5 617,-6403.5 617,-6384.5 462,-6384.5"/>
+<text text-anchor="middle" x="539.5" y="-6391.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ClipAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node106 -->
<g id="edge110" class="edge">
<title>Node55->Node106</title>
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-<polygon fill="#191970" stroke="#191970" points="373.217,-6135.4387 362.7009,-6136.7276 371.7255,-6142.278 373.217,-6135.4387"/>
+<path fill="none" stroke="#191970" d="M372.7185,-6170.374C385.1146,-6173.5632 396.967,-6179.0142 406,-6188 465.6947,-6247.3828 382.7935,-6314.1304 442,-6374 447.5891,-6379.6517 454.3177,-6383.9181 461.5958,-6387.1145"/>
+<polygon fill="#191970" stroke="#191970" points="373.2091,-6166.9009 362.704,-6168.2769 371.7744,-6173.7523 373.2091,-6166.9009"/>
</g>
<!-- Node108 -->
<g id="node117" class="node">
<title>Node108</title>
-<g id="a_node117"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Concatenate\lAttrs \>">
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-<text text-anchor="start" x="465.5" y="-6204" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Concatenate</text>
-<text text-anchor="middle" x="539.5" y="-6193" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node117"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Compiler\lAttrs \>">
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+<text text-anchor="start" x="474.5" y="-6353" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Compiler</text>
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+<text text-anchor="start" x="465.5" y="-6304" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Concatenate</text>
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+<text text-anchor="middle" x="539.5" y="-6166.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Conv2DAttrs ></text>
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+<text text-anchor="start" x="454" y="-6079" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Conv2DWinograd</text>
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+<text text-anchor="middle" x="539.5" y="-5980.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Conv3DAttrs ></text>
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+<g id="a_node139"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ConvGemm\lWeightTransformAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="459.5,-5826 459.5,-5856 619.5,-5856 619.5,-5826 459.5,-5826"/>
+<text text-anchor="start" x="467.5" y="-5844" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ConvGemm</text>
+<text text-anchor="middle" x="539.5" y="-5833" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">WeightTransformAttrs ></text>
</a>
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<g id="edge134" class="edge">
<title>Node55->Node130</title>
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<g id="node141" class="node">
<title>Node132</title>
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-<text text-anchor="middle" x="539.5" y="-5635" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node141"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ConvWinograd\lWeightTransformAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="453,-5777 453,-5807 626,-5807 626,-5777 453,-5777"/>
+<text text-anchor="start" x="461" y="-5795" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ConvWinograd</text>
+<text text-anchor="middle" x="539.5" y="-5784" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">WeightTransformAttrs ></text>
</a>
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<title>Node55->Node132</title>
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<g id="node143" class="node">
<title>Node134</title>
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-<text text-anchor="start" x="460" y="-5597" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CropAndResize</text>
-<text text-anchor="middle" x="539.5" y="-5586" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node143"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Correlation\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="461.5,-5728 461.5,-5758 617.5,-5758 617.5,-5728 461.5,-5728"/>
+<text text-anchor="start" x="469.5" y="-5746" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Correlation</text>
+<text text-anchor="middle" x="539.5" y="-5735" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
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<g id="edge138" class="edge">
<title>Node55->Node134</title>
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+<path fill="none" stroke="#191970" d="M309.1738,-6148.9714C324.894,-6075.3795 382.6632,-5821.3815 442,-5767 447.6547,-5761.8176 454.2458,-5757.7076 461.2844,-5754.4546"/>
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<g id="node145" class="node">
<title>Node136</title>
-<g id="a_node145"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DebugAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-5547.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DebugAttrs ></text>
+<g id="a_node145"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< CropAndResize\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="452,-5679 452,-5709 627,-5709 627,-5679 452,-5679"/>
+<text text-anchor="start" x="460" y="-5697" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< CropAndResize</text>
+<text text-anchor="middle" x="539.5" y="-5686" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
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<g id="edge140" class="edge">
<title>Node55->Node136</title>
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-<polygon fill="#191970" stroke="#191970" points="303.4509,-6115.125 305.9235,-6125.4272 310.4151,-6115.8316 303.4509,-6115.125"/>
+<path fill="none" stroke="#191970" d="M308.3675,-6149.1273C322.1281,-6070.1938 376.4761,-5780.1054 442,-5718 445.5426,-5714.6422 449.4766,-5711.7318 453.6741,-5709.2112"/>
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<g id="node147" class="node">
<title>Node138</title>
-<g id="a_node147"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Deformable\lConv2DAttrs \>">
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-<text text-anchor="start" x="467.5" y="-5509" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Deformable</text>
-<text text-anchor="middle" x="539.5" y="-5498" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Conv2DAttrs ></text>
+<g id="a_node147"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DebugAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="455.5,-5640.5 455.5,-5659.5 623.5,-5659.5 623.5,-5640.5 455.5,-5640.5"/>
+<text text-anchor="middle" x="539.5" y="-5647.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DebugAttrs ></text>
</a>
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</g>
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<g id="edge142" class="edge">
<title>Node55->Node138</title>
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-<polygon fill="#191970" stroke="#191970" points="303.2566,-6115.0262 305.8363,-6125.3021 310.2279,-6115.6603 303.2566,-6115.0262"/>
+<path fill="none" stroke="#191970" d="M307.6122,-6149.3492C319.182,-6065.2934 368.507,-5737.1795 442,-5669 446.0457,-5665.2468 450.6034,-5662.135 455.482,-5659.5629"/>
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<!-- Node140 -->
<g id="node149" class="node">
<title>Node140</title>
-<g id="a_node149"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DenseAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-5459.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DenseAttrs ></text>
+<g id="a_node149"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Deformable\lConv2DAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="459.5,-5591 459.5,-5621 619.5,-5621 619.5,-5591 459.5,-5591"/>
+<text text-anchor="start" x="467.5" y="-5609" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Deformable</text>
+<text text-anchor="middle" x="539.5" y="-5598" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Conv2DAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node140 -->
<g id="edge144" class="edge">
<title>Node55->Node140</title>
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-<polygon fill="#191970" stroke="#191970" points="302.7645,-6115.1982 305.5931,-6125.4085 309.7491,-6115.6628 302.7645,-6115.1982"/>
+<path fill="none" stroke="#191970" d="M307.3557,-6149.1049C318.1722,-6061.0393 365.8352,-5707.291 442,-5631 447.062,-5625.9297 453.0034,-5621.8422 459.4127,-5618.5527"/>
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<!-- Node142 -->
<g id="node151" class="node">
<title>Node142</title>
-<g id="a_node151"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DensePack\lAttrs \>">
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-<text text-anchor="start" x="470" y="-5421" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DensePack</text>
-<text text-anchor="middle" x="539.5" y="-5410" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node151"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DenseAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="456,-5552.5 456,-5571.5 623,-5571.5 623,-5552.5 456,-5552.5"/>
+<text text-anchor="middle" x="539.5" y="-5559.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DenseAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node142 -->
<g id="edge146" class="edge">
<title>Node55->Node142</title>
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+<path fill="none" stroke="#191970" d="M306.793,-6148.9604C315.5712,-6055.4252 357.0706,-5662.8888 442,-5581 446.0968,-5577.0499 450.7576,-5573.8024 455.7688,-5571.1421"/>
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<!-- Node144 -->
<g id="node153" class="node">
<title>Node144</title>
-<g id="a_node153"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Dequantize\lAttrs \>">
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-<text text-anchor="start" x="468.5" y="-5372" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Dequantize</text>
-<text text-anchor="middle" x="539.5" y="-5361" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node153"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DensePack\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="462,-5503 462,-5533 617,-5533 617,-5503 462,-5503"/>
+<text text-anchor="start" x="470" y="-5521" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DensePack</text>
+<text text-anchor="middle" x="539.5" y="-5510" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
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<g id="edge148" class="edge">
<title>Node55->Node144</title>
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+<path fill="none" stroke="#191970" d="M306.5742,-6149.3364C314.6607,-6053.1945 354.5835,-5633.5807 442,-5543 447.582,-5537.2159 454.3061,-5532.7033 461.5815,-5529.1919"/>
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<!-- Node146 -->
<g id="node155" class="node">
<title>Node146</title>
-<g id="a_node155"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DeviceCopy\lAttrs \>">
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-<text text-anchor="start" x="467" y="-5323" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DeviceCopy</text>
-<text text-anchor="middle" x="539.5" y="-5312" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node155"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Dequantize\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="460.5,-5454 460.5,-5484 618.5,-5484 618.5,-5454 460.5,-5454"/>
+<text text-anchor="start" x="468.5" y="-5472" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Dequantize</text>
+<text text-anchor="middle" x="539.5" y="-5461" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
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<g id="edge150" class="edge">
<title>Node55->Node146</title>
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+<path fill="none" stroke="#191970" d="M306.2321,-6149.0416C312.8881,-6047.7111 347.8046,-5591.1782 442,-5493 447.1896,-5487.591 453.3866,-5483.322 460.1062,-5479.9626"/>
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<g id="node157" class="node">
<title>Node148</title>
-<g id="a_node157"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DilateAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-5273.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DilateAttrs ></text>
+<g id="a_node157"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DeviceCopy\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="459,-5405 459,-5435 620,-5435 620,-5405 459,-5405"/>
+<text text-anchor="start" x="467" y="-5423" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DeviceCopy</text>
+<text text-anchor="middle" x="539.5" y="-5412" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node148 -->
<g id="edge152" class="edge">
<title>Node55->Node148</title>
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+<path fill="none" stroke="#191970" d="M305.9241,-6149.2904C311.2515,-6044.1614 341.4064,-5550.2408 442,-5444 446.7942,-5438.9367 452.4706,-5434.8697 458.6364,-5431.6113"/>
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<!-- Node150 -->
<g id="node159" class="node">
<title>Node150</title>
-<g id="a_node159"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Dilation2\lDAttrs \>">
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-<text text-anchor="start" x="474.5" y="-5235" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Dilation2</text>
-<text text-anchor="middle" x="539.5" y="-5224" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DAttrs ></text>
+<g id="a_node159"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DilateAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="456.5,-5366.5 456.5,-5385.5 622.5,-5385.5 622.5,-5366.5 456.5,-5366.5"/>
+<text text-anchor="middle" x="539.5" y="-5373.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DilateAttrs ></text>
</a>
</g>
</g>
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<g id="edge154" class="edge">
<title>Node55->Node150</title>
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<!-- Node152 -->
<g id="node161" class="node">
<title>Node152</title>
-<g id="a_node161"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DropoutAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-5185.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DropoutAttrs ></text>
+<g id="a_node161"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Dilation2\lDAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="466.5,-5317 466.5,-5347 612.5,-5347 612.5,-5317 466.5,-5317"/>
+<text text-anchor="start" x="474.5" y="-5335" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Dilation2</text>
+<text text-anchor="middle" x="539.5" y="-5324" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DAttrs ></text>
</a>
</g>
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<g id="edge156" class="edge">
<title>Node55->Node152</title>
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-<polygon fill="#191970" stroke="#191970" points="303.0513,-6115.1602 305.7477,-6125.4062 310.0292,-6115.715 303.0513,-6115.1602"/>
+<path fill="none" stroke="#191970" d="M305.5147,-6149.1214C308.837,-6036.3667 330.7854,-5477.9548 442,-5357 448.6235,-5349.7964 457.0147,-5344.5481 466.0834,-5340.7444"/>
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<!-- Node154 -->
<g id="node163" class="node">
<title>Node154</title>
-<g id="a_node163"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DynExpand\lDimsAttrs \>">
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-<text text-anchor="start" x="468.5" y="-5147" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DynExpand</text>
-<text text-anchor="middle" x="539.5" y="-5136" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DimsAttrs ></text>
+<g id="a_node163"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DropoutAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="451.5,-5278.5 451.5,-5297.5 627.5,-5297.5 627.5,-5278.5 451.5,-5278.5"/>
+<text text-anchor="middle" x="539.5" y="-5285.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DropoutAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node154 -->
<g id="edge158" class="edge">
<title>Node55->Node154</title>
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-<polygon fill="#191970" stroke="#191970" points="302.9906,-6115.1043 305.7212,-6125.3412 309.9704,-6115.6358 302.9906,-6115.1043"/>
+<path fill="none" stroke="#191970" d="M305.1896,-6149.264C306.727,-6032.483 320.5161,-5432.7926 442,-5307 445.594,-5303.2785 449.6847,-5300.1683 454.1062,-5297.5772"/>
+<polygon fill="#191970" stroke="#191970" points="301.6897,-6149.2486 305.0733,-6159.2885 308.6892,-6149.3299 301.6897,-6149.2486"/>
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<!-- Node156 -->
<g id="node165" class="node">
<title>Node156</title>
-<g id="a_node165"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< EinsumAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="453,-5090.5 453,-5109.5 626,-5109.5 626,-5090.5 453,-5090.5"/>
-<text text-anchor="middle" x="539.5" y="-5097.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< EinsumAttrs ></text>
+<g id="a_node165"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< DynExpand\lDimsAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="460.5,-5229 460.5,-5259 618.5,-5259 618.5,-5229 460.5,-5229"/>
+<text text-anchor="start" x="468.5" y="-5247" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< DynExpand</text>
+<text text-anchor="middle" x="539.5" y="-5236" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DimsAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node156 -->
<g id="edge160" class="edge">
<title>Node55->Node156</title>
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-<polygon fill="#191970" stroke="#191970" points="302.7859,-6115.2337 305.618,-6125.443 309.7706,-6115.6958 302.7859,-6115.2337"/>
+<path fill="none" stroke="#191970" d="M305.1552,-6149.2639C306.4976,-6029.8504 319.37,-5404.5416 442,-5269 447.1585,-5263.2984 453.424,-5258.8182 460.2636,-5255.3079"/>
+<polygon fill="#191970" stroke="#191970" points="301.6534,-6149.4399 305.0558,-6159.4735 308.6531,-6149.5081 301.6534,-6149.4399"/>
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<!-- Node158 -->
<g id="node167" class="node">
<title>Node158</title>
-<g id="a_node167"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ExpandDims\lAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="457.5,-5041 457.5,-5071 621.5,-5071 621.5,-5041 457.5,-5041"/>
-<text text-anchor="start" x="465.5" y="-5059" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ExpandDims</text>
-<text text-anchor="middle" x="539.5" y="-5048" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node167"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< EinsumAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="453,-5190.5 453,-5209.5 626,-5209.5 626,-5190.5 453,-5190.5"/>
+<text text-anchor="middle" x="539.5" y="-5197.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< EinsumAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node158 -->
<g id="edge162" class="edge">
<title>Node55->Node158</title>
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-<polygon fill="#191970" stroke="#191970" points="302.7406,-6115.2231 305.597,-6125.4256 309.7264,-6115.6687 302.7406,-6115.2231"/>
+<path fill="none" stroke="#191970" d="M306.4711,-6149.4292C316.3793,-6019.9221 375.0136,-5289.3685 442,-5219 445.5672,-5215.2527 449.6372,-5212.1228 454.0433,-5209.517"/>
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<!-- Node160 -->
<g id="node169" class="node">
<title>Node160</title>
-<g id="a_node169"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< FIFOBuffer\lAttrs \>">
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-<text text-anchor="start" x="471.5" y="-5010" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< FIFOBuffer</text>
-<text text-anchor="middle" x="539.5" y="-4999" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node169"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< ExpandDims\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="457.5,-5141 457.5,-5171 621.5,-5171 621.5,-5141 457.5,-5141"/>
+<text text-anchor="start" x="465.5" y="-5159" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< ExpandDims</text>
+<text text-anchor="middle" x="539.5" y="-5148" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
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<g id="edge164" class="edge">
<title>Node55->Node160</title>
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-<polygon fill="#191970" stroke="#191970" points="302.6181,-6115.111 305.5414,-6125.2946 309.6067,-6115.5107 302.6181,-6115.111"/>
+<path fill="none" stroke="#191970" d="M306.4345,-6149.1144C316.213,-6015.917 374.6924,-5256.3945 442,-5181 446.4223,-5176.0464 451.68,-5172.0126 457.4276,-5168.7346"/>
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<!-- Node162 -->
<g id="node171" class="node">
<title>Node162</title>
-<g id="a_node171"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< FixedPoint\lMultiplyAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="463.5,-4943 463.5,-4973 615.5,-4973 615.5,-4943 463.5,-4943"/>
-<text text-anchor="start" x="471.5" y="-4961" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< FixedPoint</text>
-<text text-anchor="middle" x="539.5" y="-4950" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">MultiplyAttrs ></text>
+<g id="a_node171"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< FIFOBuffer\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="463.5,-5092 463.5,-5122 615.5,-5122 615.5,-5092 463.5,-5092"/>
+<text text-anchor="start" x="471.5" y="-5110" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< FIFOBuffer</text>
+<text text-anchor="middle" x="539.5" y="-5099" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
</g>
</g>
<!-- Node55->Node162 -->
<g id="edge166" class="edge">
<title>Node55->Node162</title>
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-<polygon fill="#191970" stroke="#191970" points="302.5137,-6115.0323 305.493,-6125.1996 309.5044,-6115.3936 302.5137,-6115.0323"/>
+<path fill="none" stroke="#191970" d="M306.2977,-6148.955C315.3749,-6011.4081 371.0819,-5210.1923 442,-5131 447.931,-5124.377 455.3685,-5119.4403 463.4768,-5115.781"/>
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<!-- Node164 -->
<g id="node173" class="node">
<title>Node164</title>
-<g id="a_node173"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GatherAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="454.5,-4904.5 454.5,-4923.5 624.5,-4923.5 624.5,-4904.5 454.5,-4904.5"/>
-<text text-anchor="middle" x="539.5" y="-4911.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GatherAttrs ></text>
+<g id="a_node173"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< FixedPoint\lMultiplyAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="463.5,-5043 463.5,-5073 615.5,-5073 615.5,-5043 463.5,-5043"/>
+<text text-anchor="start" x="471.5" y="-5061" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< FixedPoint</text>
+<text text-anchor="middle" x="539.5" y="-5050" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">MultiplyAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node164 -->
<g id="edge168" class="edge">
<title>Node55->Node164</title>
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-<polygon fill="#191970" stroke="#191970" points="302.3574,-6115.3007 305.4107,-6125.446 309.3505,-6115.611 302.3574,-6115.3007"/>
+<path fill="none" stroke="#191970" d="M306.1512,-6149.3247C314.5214,-6009.1769 367.8049,-5165.341 442,-5082 447.9116,-5075.3597 455.3374,-5070.4126 463.4395,-5066.7476"/>
+<polygon fill="#191970" stroke="#191970" points="302.6494,-6149.2541 305.5523,-6159.4435 309.6371,-6149.6678 302.6494,-6149.2541"/>
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<!-- Node166 -->
<g id="node175" class="node">
<title>Node166</title>
-<g id="a_node175"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GatherNDAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-4873.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GatherNDAttrs ></text>
+<g id="a_node175"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GatherAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="454.5,-5004.5 454.5,-5023.5 624.5,-5023.5 624.5,-5004.5 454.5,-5004.5"/>
+<text text-anchor="middle" x="539.5" y="-5011.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GatherAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node166 -->
<g id="edge170" class="edge">
<title>Node55->Node166</title>
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-<polygon fill="#191970" stroke="#191970" points="302.2837,-6115.3537 305.3742,-6125.4877 309.278,-6115.6383 302.2837,-6115.3537"/>
+<path fill="none" stroke="#191970" d="M305.9972,-6149.2903C313.4594,-6005.2878 362.4731,-5118.5072 442,-5033 445.6409,-5029.0853 449.8297,-5025.8401 454.3804,-5023.1597"/>
+<polygon fill="#191970" stroke="#191970" points="302.4995,-6149.1585 305.4826,-6159.3247 309.4903,-6149.5171 302.4995,-6149.1585"/>
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<!-- Node168 -->
<g id="node177" class="node">
<title>Node168</title>
-<g id="a_node177"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GetValid\lCountsAttrs \>">
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-<text text-anchor="start" x="476" y="-4835" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GetValid</text>
-<text text-anchor="middle" x="539.5" y="-4824" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">CountsAttrs ></text>
+<g id="a_node177"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GatherNDAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="447,-4966.5 447,-4985.5 632,-4985.5 632,-4966.5 447,-4966.5"/>
+<text text-anchor="middle" x="539.5" y="-4973.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GatherNDAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node168 -->
<g id="edge172" class="edge">
<title>Node55->Node168</title>
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-<polygon fill="#191970" stroke="#191970" points="302.2798,-6115.0882 305.3779,-6125.2199 309.2743,-6115.3676 302.2798,-6115.0882"/>
+<path fill="none" stroke="#191970" d="M305.9264,-6149.093C312.9624,-6001.7287 359.9356,-5083.5766 442,-4995 445.3989,-4991.3313 449.279,-4988.25 453.4875,-4985.6701"/>
+<polygon fill="#191970" stroke="#191970" points="302.4183,-6149.1838 305.4427,-6159.3378 309.4105,-6149.514 302.4183,-6149.1838"/>
</g>
<!-- Node170 -->
<g id="node179" class="node">
<title>Node170</title>
-<g id="a_node179"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GlobalPool2\lDAttrs \>">
-<polygon fill="#ffffff" stroke="#000000" points="459,-4768 459,-4798 620,-4798 620,-4768 459,-4768"/>
-<text text-anchor="start" x="467" y="-4786" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GlobalPool2</text>
-<text text-anchor="middle" x="539.5" y="-4775" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">DAttrs ></text>
+<g id="a_node179"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GetValid\lCountsAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="468,-4917 468,-4947 611,-4947 611,-4917 468,-4917"/>
+<text text-anchor="start" x="476" y="-4935" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GetValid</text>
+<text text-anchor="middle" x="539.5" y="-4924" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">CountsAttrs ></text>
</a>
</g>
</g>
<!-- Node55->Node170 -->
<g id="edge174" class="edge">
<title>Node55->Node170</title>
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-<polygon fill="#191970" stroke="#191970" points="302.1878,-6115.0775 305.3332,-6125.1947 309.1834,-6115.3242 302.1878,-6115.0775"/>
+<path fill="none" stroke="#191970" d="M305.9097,-6148.9666C312.9067,-5998.6822 360.111,-5051.0902 442,-4957 448.8833,-4949.0911 457.8959,-4943.5162 467.6616,-4939.6157"/>
+<polygon fill="#191970" stroke="#191970" points="302.3935,-6149.2388 305.4298,-6159.3892 309.3861,-6149.5608 302.3935,-6149.2388"/>
</g>
<!-- Node172 -->
<g id="node181" class="node">
<title>Node172</title>
-<g id="a_node181"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< GridSample\lAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-4726" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
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+<text text-anchor="start" x="467" y="-4886" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GlobalPool2</text>
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+<text text-anchor="start" x="468" y="-4837" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< GridSample</text>
+<text text-anchor="middle" x="539.5" y="-4826" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
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<title>Node55->Node174</title>
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<g id="node185" class="node">
<title>Node176</title>
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+<text text-anchor="middle" x="539.5" y="-4777" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
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<title>Node55->Node176</title>
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<g id="node187" class="node">
<title>Node178</title>
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+<text text-anchor="middle" x="539.5" y="-4738.5" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< InitOpAttrs ></text>
</a>
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<g id="edge182" class="edge">
<title>Node55->Node178</title>
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<g id="node189" class="node">
<title>Node180</title>
-<g id="a_node189"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< L2Normalize\lAttrs \>">
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-<text text-anchor="middle" x="539.5" y="-4540" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
+<g id="a_node189"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< Instance\lNormAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="468,-4682 468,-4712 611,-4712 611,-4682 468,-4682"/>
+<text text-anchor="start" x="476" y="-4700" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< Instance</text>
+<text text-anchor="middle" x="539.5" y="-4689" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">NormAttrs ></text>
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<title>Node55->Node180</title>
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<g id="node191" class="node">
<title>Node182</title>
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+<g id="a_node191"><a xlink:href="classtvm_1_1AttrsNode.html" target="_top" xlink:title="tvm::AttrsNode\< L2Normalize\lAttrs \>">
+<polygon fill="#ffffff" stroke="#000000" points="457.5,-4633 457.5,-4663 621.5,-4663 621.5,-4633 457.5,-4633"/>
+<text text-anchor="start" x="465.5" y="-4651" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">tvm::AttrsNode< L2Normalize</text>
+<text text-anchor="middle" x="539.5" y="-4640" font-family="Helvetica,sans-Serif" font-size="10.00" fill="#000000">Attrs ></text>
</a>
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<title>Node55->Node182</title>
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... 12310 lines suppressed ...