[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663

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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #21598 by @JCNTH
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig
Differential Revision: D114936143
@diff-train-skip-merge

@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663

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

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@meta-clameta-claBot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Aug 7, 2026
JCNTHand others added 3 commits August 7, 2026 10:32
@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH merged commit d73d0bc into gh/JCNTH/204/origAug 7, 2026
7 checks passed
@JCNTH
JCNTH deleted the gh/JCNTH/205/orig branch August 7, 2026 17:32
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[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
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Merged
[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
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JCNTHand others
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@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

7 checks passed

@JCNTH
JCNTH
deleted the

gh/JCNTH/205/orig

branch
August 7, 2026 17:32
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[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
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gh/JCNTH/205/orig
Aug 7, 2026
Merged
[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
As of commit daad2d1 with merge base ad3a71f (image):

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@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

7 checks passed

@JCNTH
JCNTH
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gh/JCNTH/205/orig

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August 7, 2026 17:32
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

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Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
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@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

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@JCNTH
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
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[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
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added 3 commits
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@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

7 checks passed

@JCNTH
JCNTH
deleted the

gh/JCNTH/205/orig

branch
August 7, 2026 17:32
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
Merged
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gh/JCNTH/205/orig
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Merged
[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
As of commit daad2d1 with merge base ad3a71f (image):

💚 Looks good so far! There are no failures yet. 💚
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JCNTHand others
added 3 commits
August 7, 2026 10:32
@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

7 checks passed

@JCNTH
JCNTH
deleted the

gh/JCNTH/205/orig

branch
August 7, 2026 17:32
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
Merged
JCNTH merged 4 commits into
gh/JCNTH/204/origfrom 
gh/JCNTH/205/orig
Aug 7, 2026
Merged
[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
JCNTH merged 4 commits into
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gh/JCNTH/205/orig
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

@diff-train-skip-merge
@JCNTH
[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
Note: Links to docs will display an error until the docs builds have been completed.
⏳ No Failures, 8 Pending
As of commit daad2d1 with merge base ad3a71f (image):

💚 Looks good so far! There are no failures yet. 💚
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@meta-clameta-claBot
added
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JCNTHand others
added 3 commits
August 7, 2026 10:32
@JCNTH
[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
@pytorchbot@JCNTH
[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
daad2d1
@JCNTH
JCNTH
merged commit d73d0bc
into
gh/JCNTH/204/origAug 7, 2026

7 checks passed

@JCNTH
JCNTH
deleted the

gh/JCNTH/205/orig

branch
August 7, 2026 17:32
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
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[ExecuTorch][WebGPU] Support byte-packed BOOL storage - #21663
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[ExecuTorch][WebGPU] Support byte-packed BOOL storage#21663
JCNTH merged 4 commits into
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gh/JCNTH/205/orig
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This PR was created by the merge bot to help merge the original PR into the main branch.

ghstack PR number: #21598 by @JCNTH

^ Please use this as the source of truth for the PR details, comments, and reviews

ghstack PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/base

ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/head

Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/204/orig

Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/205/orig

Differential Revision: D114936143

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[ExecuTorch][WebGPU] Support byte-packed BOOL storage
ee718bf
**Support exact byte-packed BOOL tensors**
WebGPU storage and transfers require four-byte alignment while serialized `BOOL` tensors use one logical byte per element. The runtime now preserves exact `BOOL` dtype and logical byte counts while padding physical storage, uploads, and readback.
Key changes:
- Compare output — packs guarded tail lanes for arbitrary nonzero lengths.
- `BOOL`-to-fp32 — decodes packed values numerically instead of reinterpreting bytes.
- `_to_copy` routing — mirrors Vulkan exact-dtype conversion intent in `backends/vulkan/runtime/graph/ops/impl/View.cpp:183` while keeping `BOOL` separate from `INT8` and `UINT8`.
- Generated sources — refresh WGSL registry output and drift digests.
Logical tensor sizes and existing non-`BOOL` routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936143](https://our.internmc.facebook.com/intern/diff/D114936143/)
ghstack-source-id: 411044625
Pull-Request: #21598
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21663
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[ExecuTorch][WebGPU] Test byte-packed BOOL tails
9b9e5ac
**Exercise byte-packed BOOL tails through export and native execution**
Manifest and export coverage now proves exact `BOOL` storage and numeric `BOOL`-to-fp32 conversion across word-aligned and tail lengths. The native driver preserves `BOOL` metadata and compares canonical raw 0/1 bytes rather than semantic truth values.
Key changes:
- Length coverage — exercises 1, 4, 5, and 67 elements.
- Export assertions — keep the fp32 cast inside the delegate while `INT8` stays outside the `BOOL` route.
- Native validation — checks direct inputs, comparison outputs, and raw tail bytes.
This is coverage-only; runtime kernels are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936146](https://our.internmc.facebook.com/intern/diff/D114936146/)
ghstack-source-id: 411044629
Pull-Request: #21599
@JCNTH
[ExecuTorch][WebGPU] Support general groups=1 Conv1d
bb40df4
**Add a buffer-only groups=1 Conv1d kernel for Voxtral encoder shapes**
The WebGPU backend handled only K=1 pointwise and depthwise Conv1d, leaving non-transposed groups=1 K=3 encoder convolutions unsupported.
**Before**
- Groups=1 K>1 graphs had no valid WebGPU route.
**After**
- A direct NCL buffer kernel supports groups=1 convolution with stride, padding, dilation, and optional bias.
Key changes:
- `add_conv1d_node` — validates fp32 operands, geometry, shapes, and shader index ranges.
- `conv1d.wgsl` — mirrors Vulkan output indexing in `backends/vulkan/runtime/graph/ops/glsl/conv1d.glsl:78`, stride/padding at `:86`, and the kernel FMA loop at `:108`.
- Dispatch and resize hooks — fold x/y workgroups and recompute live parameters safely.
- Generated sources — refresh WGSL headers, registry output, and drift digests.
The route remains limited to non-transposed groups=1 fp32 convolution; existing pointwise and depthwise routes are unchanged.
Co-authored-with: Claude Code.
Differential Revision: [D114936145](https://our.internmc.facebook.com/intern/diff/D114936145/)
ghstack-source-id: 411044636
Pull-Request: #21600
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[ExecuTorch][WebGPU] Cover Conv1d routes and dynamic manifests (#21666)
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