Inductor cpp wrapper: support QConv #112373
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/112373
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 8387bba with merge base bbd5b93 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Oct 30, 2023
jgong5
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desertfire
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| ) | ||
| self.cpp_kernel_overlad_name = "binary" | ||
| self.cpp_kernel_key = "qconv2d_pointwise_binary" | ||
| self.cpp_op_schema = """ |
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Is it possible to read this kind of schema from somewhere instead of keep adding them for more and more ops?
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Let me submit a subsequent PR to clean this up. Created an issue to track it: #112552
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Align the type of `post_op_args` in the schema of `onednn::qlinear_pointwise` to be the same as other fusion OPs like qconv, conv, conv_transpose, linear by changing from `float[]` to `Scalar?[]`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L260-L266 https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/mkldnn/RegisterMkldnnOpContextClass.cpp#L48-L59 Pull Request resolved: #112378 Approved by: https://github.com/jgong5, https://github.com/desertfire ghstack dependencies: #112373
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Based on the `Argument types` section in this [file](https://github.com/pytorch/pytorch/tree/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native#func), for non-inplace `Tensor` type in schema, it should be mapped to C++ argument of type `const Tensor&`. For `quantized_max_pool1d` and `quantized_max_pool2d`, the type of the `qx` input is `Tensor` type in the schema, thus modified the C++ type to be `const Tensor&`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L222-L223 Pull Request resolved: #112379 Approved by: https://github.com/jgong5, https://github.com/jansel ghstack dependencies: #112373, #112378
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Pull Request resolved: pytorch#112373 Approved by: https://github.com/jgong5, https://github.com/desertfire
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Align the type of `post_op_args` in the schema of `onednn::qlinear_pointwise` to be the same as other fusion OPs like qconv, conv, conv_transpose, linear by changing from `float[]` to `Scalar?[]`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L260-L266 https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/mkldnn/RegisterMkldnnOpContextClass.cpp#L48-L59 Pull Request resolved: pytorch#112378 Approved by: https://github.com/jgong5, https://github.com/desertfire ghstack dependencies: pytorch#112373
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Based on the `Argument types` section in this [file](https://github.com/pytorch/pytorch/tree/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native#func), for non-inplace `Tensor` type in schema, it should be mapped to C++ argument of type `const Tensor&`. For `quantized_max_pool1d` and `quantized_max_pool2d`, the type of the `qx` input is `Tensor` type in the schema, thus modified the C++ type to be `const Tensor&`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L222-L223 Pull Request resolved: pytorch#112379 Approved by: https://github.com/jgong5, https://github.com/jansel ghstack dependencies: pytorch#112373, pytorch#112378
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Pull Request resolved: pytorch#112373 Approved by: https://github.com/jgong5, https://github.com/desertfire
Skylion007
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Align the type of `post_op_args` in the schema of `onednn::qlinear_pointwise` to be the same as other fusion OPs like qconv, conv, conv_transpose, linear by changing from `float[]` to `Scalar?[]`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L260-L266 https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/mkldnn/RegisterMkldnnOpContextClass.cpp#L48-L59 Pull Request resolved: pytorch#112378 Approved by: https://github.com/jgong5, https://github.com/desertfire ghstack dependencies: pytorch#112373
Skylion007
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Based on the `Argument types` section in this [file](https://github.com/pytorch/pytorch/tree/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native#func), for non-inplace `Tensor` type in schema, it should be mapped to C++ argument of type `const Tensor&`. For `quantized_max_pool1d` and `quantized_max_pool2d`, the type of the `qx` input is `Tensor` type in the schema, thus modified the C++ type to be `const Tensor&`: https://github.com/pytorch/pytorch/blob/cb942ef2b12134bfaa1727295380fe00ebb537c0/aten/src/ATen/native/quantized/library.cpp#L222-L223 Pull Request resolved: pytorch#112379 Approved by: https://github.com/jgong5, https://github.com/jansel ghstack dependencies: pytorch#112373, pytorch#112378
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Stack from ghstack (oldest at bottom):
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov @ColinPeppler