Arm backend: Give SiLU its own output quantization params - #21437

Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom
vacu9708:silu
Jul 31, 2026
Merged

Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom
vacu9708:silu

Conversation

@vacu9708

@vacu9708vacu9708 commented Jul 28, 2026•
edited by pytorch-bot Bot
Loading

Copy link
Copy Markdown
Contributor

Summary

SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.
This commit gives SiLU its own output quantization spec.

Where this happens:

QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)

Why quantization sharing is wrong for SiLU:

image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.

Changes

FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.

Testing

pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed

cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani

@pytorch-bot

pytorch-botBot commented Jul 28, 2026•
edited
Loading

Copy link
Copy Markdown

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437

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

⚠️ 1 Awaiting Approval

As of commit 92c3e64 with merge base 14dab10 (image):

AWAITING APPROVAL - The following workflow needs approval before CI can run:

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

@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 Jul 28, 2026
@github-actionsgithub-actionsBot added ciflow/trunk module: arm Issues related to arm backend labels Jul 28, 2026
@pytorch-bot

pytorch-botBot commented Jul 28, 2026•
edited
Loading

Copy link
Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.

@vacu9708

vacu9708 commented Jul 29, 2026

Copy link
Copy Markdown
ContributorAuthor

@pytorchbot label "release notes: arm"

@pytorch-botpytorch-botBot added the release notes: arm Changes to the ARM backend delegate label Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708 changed the title Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all added the module: quantization Issues related to quantization label Jul 29, 2026
@zingozingo added the partner: arm For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm label Jul 30, 2026
Erik-Lundell
Erik-Lundell approved these changes Jul 31, 2026
View reviewed changes

@Erik-LundellErik-Lundell left a comment

Copy link
Copy Markdown
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.

@Erik-Lundell
Erik-Lundell merged commit 761c64c into pytorch:mainJul 31, 2026
518 of 519 checks passed
Sign up for freeto join this conversation on GitHub. Already have an account? Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees

No one assigned

Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects

None yet

Milestone

No milestone

Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, '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" + '

Skip to content
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, '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
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, '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
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all

, '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); }
})();
})();

Skip to content
Arm backend: Give SiLU its own output quantization params - #21437
Merged
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Jul 31, 2026
Merged
Arm backend: Give SiLU its own output quantization params#21437
Erik-Lundell merged 1 commit into
pytorch:mainfrom 
vacu9708:silu
Conversation
@vacu9708
@vacu9708vacu9708
commented
Jul 28, 2026•

edited by pytorch-bot
Bot
Loading

Copy link


Copy Markdown

Contributor
Summary
SiLU's quantized output is forced to reuse its input's quantization scale, which wastes resolution for no benefit.

This commit gives SiLU its own output quantization spec.
Where this happens:
QuantizerMechanismsilu.defaultsilu_.default
Composable (_TOSAQuantizerV2, default since #19758)TOSAQuantizationConfig.<br>SHARED_OUTPUT_ACT_QSPEC_PATTERNSshared (bug)shared (bug)
Legacy (_TOSAQuantizerV1)quantization_annotator.py op setsown qspecshared (bug)
Why quantization sharing is wrong for SiLU:
image
  • SiLU non-linearly compresses and warps its input range:
    • Unlike ReLU, which maintains a 1:1 linear mapping ($y = x$) for non-negative inputs, SiLU is non-linear across its entire domain.
    • For negative inputs, its output never goes below -0.278, no matter how negative the input gets. So its output range is always narrower than its input's. Reusing the input scale misaligns the quantization bins with the actual output distribution, wasting resolution.
  • Reusing the input's scale doesn't save any computation at runtime: SiLU runs as a lookup table (class TableOps) whose entries are precomputed at compile time, not runtime.
Changes
FileChangeWhy
quantizer/quantization_config.pyRemove silu.default/silu_.default from SHARED_OUTPUT_ACT_QSPEC_PATTERNSThe accuracy loss as described above.
quantizer/quantization_annotator.pyMove silu_.default into _one_to_one, next to silu.defaultThe legacy annotator classified the two variants differently. #17202 put silu.default in _one_to_one (own qspec) but silu_.default in _one_to_one_shared_input_or_input_act_qspec (shared qspec).
test/ops/test_silu.pySilu.forward clones its inputLatent bug found while working on this change: SiLU(inplace=True) was mutating the test pipeline's shared input tensor which the pipeline reuses. It stayed invisible because the buggy (too large) output scale made the comparison helper(compare_rel_frobenius_and_cosine_similarity()) treat every value as noise and skip the check entirely, so the test kept passing without validating anything.
test/misc/test_shared_qspecs.pyAdd NonSharedQspecSilu + test_silu_does_not_share_input_qspecCheck the emitted q/dq parameters, the same way the rest of test_shared_qspecs.py checks sharing.
Testing
pytest backends/arm/test/misc/test_shared_qspecs.py
# 17 passed
pytest backends/arm/test/ops/test_silu.py -k "not vgf"# 34 passed, 32 xfailed
cc @kimishpatel@jerryzh168@digantdesai@freddan80@per@zingo@oscarandersson8218@mansnils@Sebastian-Larsson@robell@rascani
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21437
Note: Links to docs will display an error until the docs builds have been completed.
⚠️ 1 Awaiting Approval
As of commit 92c3e64 with merge base 14dab10 (image):
AWAITING APPROVAL - The following workflow needs approval before CI can run:
This comment was automatically generated by Dr. CI and updates every 15 minutes.
@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
Jul 28, 2026
@github-actionsgithub-actionsBot
added

ciflow/trunk

module: arm
Issues related to arm backend
labels
Jul 28, 2026
@pytorch-bot
pytorch-botBot
commented
Jul 28, 2026•

edited

Loading

Copy link


Copy Markdown

Workflows were awaiting approval. CI has now been triggered for the ciflow labels on this PR.
@vacu9708
vacu9708
commented
Jul 29, 2026

Copy link


Copy Markdown

ContributorAuthor
@pytorchbot label "release notes: arm"
@pytorch-botpytorch-botBot
added
the 
release notes: arm
Changes to the ARM backend delegate
label
Jul 29, 2026
@vacu9708
Arm backend: give SiLU its own output quantization spec
92c3e64
Issue:
1. SiLU's quantized output was forced to reuse its input's quantization
scale, wasting resolution since SiLU's output range is always
narrower than its input's.
2. The composable quantizer and `silu_.default` was
separately misclassified in the legacy annotator since pytorch#17202.
Fix:
Give SiLU its own output qspec.
Also fixes an unrelated latent bug that this change exposed.
Signed-off-by: Youngsik Yang <vacu9708@gmail.com>
@vacu9708vacu9708
changed the title
Arm backend: Give SiLU its own output quantization specArm backend: Give SiLU its own output quantization paramsJul 29, 2026
@nil-is-allnil-is-all
added
the 
module: quantization
Issues related to quantization
label
Jul 29, 2026
@zingozingo
added
the 
partner: arm
For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm
label
Jul 30, 2026
Erik-Lundell
Erik-Lundell
approved these changes
Jul 31, 2026
View reviewed changes
@Erik-LundellErik-Lundell
left a comment


Copy link


Copy Markdown

Collaborator
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, thanks for the thorough PR.
@Erik-Lundell
Erik-Lundell
merged commit 761c64c
into
pytorch:mainJul 31, 2026

518 of 519 checks passed

Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers

@Erik-LundellErik-LundellErik-Lundell approved these changes
@digantdesaidigantdesaiAwaiting requested review from digantdesaidigantdesai is a code owner

Assignees


No one assigned


Labels

ciflow/trunkCLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: armIssues related to arm backendmodule: quantizationIssues related to quantizationpartner: armFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Armrelease notes: armChanges to the ARM backend delegate

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@vacu9708@Erik-Lundell@zingo@nil-is-all