[ET-VK][Ops] aten.convolution (SlidingWindow) #2812
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## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon For our CUNET model, the first two are required and the third is useful. 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/2812
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 8fee216 with merge base d3326a2 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon For our CUNET model, the first two are required and the third is useful. 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) ghstack-source-id: 220997713 Pull Request resolved: #2812
## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon For our CUNET model, the first two are required and the third is useful. 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) [ghstack-poisoned]
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Apr 3, 2024
Pull Request resolved: #2812 ## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon For our CUNET model, the first two are required and the third is useful. 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias ghstack-source-id: 221059609 @exported-using-ghexport Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/)
## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) [ghstack-poisoned]
This was referenced Apr 3, 2024
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Apr 4, 2024
Pull Request resolved: #2812 ## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Internal: For our CUNET model, the first two are required and the third is useful. ghstack-source-id: 221233078 @exported-using-ghexport Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/)
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Apr 4, 2024
## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D55346778 |
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## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. ## Coming soon 1. Transpose convolution 2. Depthwise convolution (for completeness) 3. Pointwise convolution (for optimization) 4. Null bias Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D55346778 |
jorgep31415
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Apr 8, 2024
Pull Request resolved: #2812 ## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. We will handle Transpose, Depthwise, and Pointwise in the rest of this stack. Internal: For our CUNET model, SlidingWindow, Transpose, Depthwise are required and Pointwise is a useful optimization. ghstack-source-id: 221721750 @exported-using-ghexport Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/)
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Pull Request resolved: pytorch/executorch#2812 ## The Operator `nn.Module` invocations of [`nn.Conv2d`](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html#torch.nn.Conv2d) and [`nn.ConvTranspose2d`](https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d) get compiled to `aten.convolution.default` in the Edge Dialect, which carries the signature ``` - func: convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor ``` ## Summary (cases handled) We introduce support for the convolution cases covered by [ATen-VK's default SlidingWindow implementation](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L73). This is achieved by - reusing the [existing `conv2d.glsl`](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/glsl/conv2d.glsl), and - [moving special weights prepacking from CPU](https://github.com/pytorch/pytorch/blob/09c72eaa3f69f90402c86a30abf4fc621298578c/aten/src/ATen/native/vulkan/ops/Convolution.cpp#L134-L235) to the GPU in `conv2d_prepack_weights.glsl`. We also include resizing support for dynamic shapes. Note that only height and width of the input can vary. ## Cases not handled The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing: 1. **Groups G > 1.** Largely not covered by ATen-VK. `G = in_channels` is covered by ATen-VK's Depthwise impl and will be added soon. 2. **Batch (input) N > 1.** Not covered by ATen-VK. 3. **Padding > 0 while Dilation, Kernel > 1.** Not covered by ATen-VK. We will handle Transpose, Depthwise, and Pointwise in the rest of this stack. Internal: For our CUNET model, SlidingWindow, Transpose, Depthwise are required and Pointwise is a useful optimization. ghstack-source-id: 221526243 @exported-using-ghexport Differential Revision: [D55346778](https://our.internmc.facebook.com/intern/diff/D55346778/)
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Stack from ghstack (oldest at bottom):
The Operator
nn.Moduleinvocations ofnn.Conv2dandnn.ConvTranspose2dget compiled toaten.convolution.defaultin the Edge Dialect, which carries the signatureSummary (cases handled)
We introduce support for the convolution cases covered by ATen-VK's default SlidingWindow implementation. This is achieved by
conv2d.glsl, andconv2d_prepack_weights.glsl.We also include resizing support for dynamic shapes. Note that only height and width of the input can vary.
Cases not handled
The implementation is on-par with ATen-VK's SlidingWindow. This means the following cases are missing:
G = in_channelsis covered by ATen-VK's Depthwise impl and will be added soon.Coming soon
Differential Revision: D55346778