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[ET-VK][conv1d] Route conv1d to height-packed implementations in export pipeline#18334

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[ET-VK][conv1d] Route conv1d to height-packed implementations in export pipeline#18334
meta-codesync[bot] merged 5 commits intogh/SS-JIA/496/basefrom
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@SS-JIA SS-JIA commented Mar 19, 2026

Stack from ghstack (oldest at bottom):

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: D97344090

…rt pipeline

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)

[ghstack-poisoned]
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pytorch-bot bot commented Mar 19, 2026

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18334

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure, 2 Unrelated Failures

As of commit 036f144 with merge base 7c79395 (image):

NEW FAILURE - The following job has failed:

BROKEN TRUNK - The following jobs failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

This comment was automatically generated by Dr. CI and updates every 15 minutes.

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This PR needs a release notes: label

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ssjia added 2 commits March 19, 2026 15:48
…ons in export pipeline"

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)

[ghstack-poisoned]
…ons in export pipeline"

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)

[ghstack-poisoned]
…ons in export pipeline"

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)

[ghstack-poisoned]
SS-JIA pushed a commit that referenced this pull request Mar 27, 2026
…rt pipeline

Pull Request resolved: #18334

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.
ghstack-source-id: 358872575
@exported-using-ghexport

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)
…ons in export pipeline"

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)

[ghstack-poisoned]
@meta-codesync meta-codesync bot merged commit 3a2c1bb into gh/SS-JIA/496/base Mar 27, 2026
157 of 162 checks passed
@meta-codesync meta-codesync bot deleted the gh/SS-JIA/496/head branch March 27, 2026 22:00
@meta-codesync meta-codesync bot temporarily deployed to cherry-pick-bot March 27, 2026 22:00 Inactive
SS-JIA pushed a commit that referenced this pull request Mar 27, 2026
…rt pipeline

Pull Request resolved: #18334

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.
ghstack-source-id: 358903217
@exported-using-ghexport

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)
SS-JIA pushed a commit that referenced this pull request Mar 27, 2026
…rt pipeline

Pull Request resolved: #18334

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.
ghstack-source-id: 358903217
@exported-using-ghexport

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)
SS-JIA pushed a commit that referenced this pull request Mar 27, 2026
…rt pipeline

Pull Request resolved: #18334

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.
ghstack-source-id: 358903217
@exported-using-ghexport

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)
rascani pushed a commit to rascani/executorch that referenced this pull request Apr 1, 2026
…rt pipeline

Pull Request resolved: pytorch#18334

Integrate the new height-packed conv1d_pw and conv1d_dw operators into the
aten.convolution.default dispatch path so they are automatically used during
model export.

In op_registry.py, add a pick_conv_storage function that inspects the
convolution node at partition time. For 1D convolutions where the op is
pointwise (kernel_size=1) or depthwise (groups=C_in) and channels are 4-aligned,
it selects HEIGHT_PACKED_TEXTURE for input/output instead of the default
CHANNELS_PACKED_TEXTURE. All other cases (conv2d, grouped conv1d with K>1,
unaligned channels) retain channels-packed behavior.

In Convolution.cpp, add a height-packed routing block at the top of the conv1d
path. When the input tensor is height-packed, it dispatches to
et_vk.conv1d_pw.default or et_vk.conv1d_dw.default via VK_GET_OP_FN. Falls
through to the existing channels-packed add_conv1d_node path otherwise.
ghstack-source-id: 358903217
@exported-using-ghexport

Differential Revision: [D97344090](https://our.internmc.facebook.com/intern/diff/D97344090/)
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