[ET-VK][Ops] aten.convolution (Depthwise) #2884
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## Summary We introduce support for the convolution cases covered by [ATen-VK's default Depthwise implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L68). This is achieved by - reusing the [existing `conv2d_dw.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d_dw.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L80-L132) to the GPU in `conv2d_dw_prepack_weights.glsl`. The implementation is on-par with ATen-VK's Depthwise. This means it only covers: - `in_channels == groups`, `out_channels == groups` A full implementation would cover, for any positive integer K: - `in_channels == groups`, `out_channels == groups * K` Differential Revision: [D55813511](https://our.internmc.facebook.com/intern/diff/D55813511/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/2884
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## Summary We introduce support for the convolution cases covered by [ATen-VK's default Depthwise implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L68). This is achieved by - reusing the [existing `conv2d_dw.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d_dw.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L80-L132) to the GPU in `conv2d_dw_prepack_weights.glsl`. The implementation is on-par with ATen-VK's Depthwise. This means it only covers: - `in_channels == groups`, `out_channels == groups` A full implementation would cover, for any positive integer K: - `in_channels == groups`, `out_channels == groups * K` Differential Revision: [D55813511](https://our.internmc.facebook.com/intern/diff/D55813511/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D55813511 |
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Pull Request resolved: #2884 ## Summary We introduce support for the convolution cases covered by [ATen-VK's default Depthwise implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L68). This is achieved by - reusing the [existing `conv2d_dw.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d_dw.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L80-L132) to the GPU in `conv2d_dw_prepack_weights.glsl`. The implementation is on-par with ATen-VK's Depthwise. This means it only covers: - `in_channels == groups`, `out_channels == groups` A full implementation would cover, for any positive integer K: - `in_channels == groups`, `out_channels == groups * K` ghstack-source-id: 221721752 @exported-using-ghexport Differential Revision: [D55813511](https://our.internmc.facebook.com/intern/diff/D55813511/)
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## Summary We introduce support for the convolution cases covered by [ATen-VK's default Depthwise implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L68). This is achieved by - reusing the [existing `conv2d_dw.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d_dw.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L80-L132) to the GPU in `conv2d_dw_prepack_weights.glsl`. The implementation is on-par with ATen-VK's Depthwise. This means it only covers: - `in_channels == groups`, `out_channels == groups` A full implementation would cover, for any positive integer K: - `in_channels == groups`, `out_channels == groups * K` Differential Revision: [D55813511](https://our.internmc.facebook.com/intern/diff/D55813511/) ghstack-source-id: 221526244 Pull Request resolved: pytorch/executorch#2884
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Stack from ghstack (oldest at bottom):
Summary
We introduce support for the convolution cases covered by ATen-VK's default Depthwise implementation. This is achieved by
conv2d_dw.glsl, andconv2d_dw_prepack_weights.glsl.The implementation is on-par with ATen-VK's Depthwise. This means it only covers:
in_channels == groups,out_channels == groupsA full implementation would cover, for any positive integer K:
in_channels == groups,out_channels == groups * KDifferential Revision: D55813511