Migrate thnn_conv_depthwise2d from THC to ATen #62281
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Closes gh-24646, gh-24647 There is no `TensorIterator` equivalent to these kernels so this is just migrating the existing kernels over to the ATen style. I've benchmarked for contiguous tensors with this script: ``` import torch shape = (10, 10, 100, 100) x = torch.randn(*shape, device='cuda') w = torch.randn((10, 1, 5, 5), device='cuda') for _ in range(100): torch.nn.functional.conv2d(x, w, groups=10) ``` and similarly for backwards. I see these as the same to within measurement error. | | Master Forward (us) | This PR Forward (us) | |------------------:|:-------------------:|:--------------------:| | Forward | 133.5 | 133.6 | | Backward (input) | 1,102 | 1,119 | | Backward (weight) | 2,220 | 2,217 | [ghstack-poisoned]
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💊 CI failures summary and remediationsAs of commit f02533e (more details on the Dr. CI page): ✅ None of the CI failures appear to be your fault 💚
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🚧 1 fixed upstream failure:These were probably caused by upstream breakages that were already fixed.
Please rebase on the
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Closes gh-24646, gh-24647 There is no `TensorIterator` equivalent to these kernels so this is just migrating the existing kernels over to the ATen style. I've benchmarked for contiguous tensors with this script: ``` import torch shape = (10, 10, 100, 100) x = torch.randn(*shape, device='cuda') w = torch.randn((10, 1, 5, 5), device='cuda') for _ in range(100): torch.nn.functional.conv2d(x, w, groups=10) ``` and similarly for backwards. I see these as the same to within measurement error. | | Master Forward (us) | This PR Forward (us) | |------------------:|:-------------------:|:--------------------:| | Forward | 133.5 | 133.6 | | Backward (input) | 1,102 | 1,119 | | Backward (weight) | 2,220 | 2,217 | ghstack-source-id: a0555c8 Pull Request resolved: #62281
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Stack from ghstack:
Closes gh-24646, Closes gh-24647
There is no
TensorIteratorequivalent to these kernels so this is justmigrating the existing kernels over to the ATen style.
I've benchmarked for contiguous tensors with this script:
and similarly for backwards. I see these as the same to within measurement error.
Differential Revision: D29943062