Including mixed quant GRU op in Jarvis - #15011

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meta-codesync[bot] merged 1 commit into
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mgiordy:export-D81703253
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Merged

Including mixed quant GRU op in Jarvis#15011
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mgiordy:export-D81703253

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@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
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For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e 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" + '
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Including mixed quant GRU op in Jarvis - #15011

Merged
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

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@mgiordy

@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

@pytorch-bot

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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@mgiordy@skrtskrtfb
, '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('^' + ".*" + '
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Including mixed quant GRU op in Jarvis - #15011

Merged
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

Conversation

@mgiordy

@mgiordymgiordy commented Oct 10, 2025•
edited
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

@pytorch-bot

pytorch-botBot commented Oct 10, 2025•
edited
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

@meta-codesync

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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2 participants

@mgiordy@skrtskrtfb
, '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 \u003e 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('^' + ".*" + '
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Including mixed quant GRU op in Jarvis - #15011

Merged
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

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@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

@pytorch-bot

pytorch-botBot commented Oct 10, 2025•
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

@meta-codesync

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
@github-actions

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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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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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Including mixed quant GRU op in Jarvis - #15011

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Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
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mgiordy:export-D81703253

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@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
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For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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@mgiordy@skrtskrtfb
, '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('^' + ".*" + '
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Including mixed quant GRU op in Jarvis - #15011

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meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

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@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

@pytorch-bot

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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@mgiordy@skrtskrtfb
, '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

Including mixed quant GRU op in Jarvis - #15011

Merged
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

Conversation

@mgiordy

@mgiordymgiordy commented Oct 10, 2025•
edited
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

@pytorch-bot

pytorch-botBot commented Oct 10, 2025•
edited
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

There are 2 currently active SEVs. If your PR is affected, please view them below:

❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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

@meta-codesync

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
@github-actions

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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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@skrtskrtfbskrtskrtfbskrtskrtfb approved these changes

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Including mixed quant GRU op in Jarvis - #15011

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meta-codesync[bot] merged 1 commit into
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mgiordy:export-D81703253
Oct 12, 2025
Merged

Including mixed quant GRU op in Jarvis#15011
meta-codesync[bot] merged 1 commit into
pytorch:mainfrom
mgiordy:export-D81703253

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@mgiordy

@mgiordymgiordy commented Oct 10, 2025•
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Summary

This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.

#hthtemplate

Reviewed By: mcremon-meta

Differential Revision: D81703253

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pytorch-botBot commented Oct 10, 2025•
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15011

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

❗ 2 Active SEVs

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❌ 4 New Failures, 3 Unrelated Failures

As of commit b44d355 with merge base 09eac16 (image):

NEW FAILURES - The following jobs have failed:

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

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

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@mgiordy has exported this pull request. If you are a Meta employee, you can view the originating Diff in D81703253.

@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 Oct 10, 2025
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This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

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mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
0867b29
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 10, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
986d302
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Oct 11, 2025
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
5467c13
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
Marco Giordano@facebook-github-bot
Including mixed quant GRU op in Jarvis (pytorch#15011)
b44d355
Summary:
# Context
With the goal of porting mHML on Executorch, a few operators are missing.
The main focus is on improving performance for the operators used by the model.
# Summary
This diff includes a general and HiFi4 optimized GRU operator.
Specifically, it adds both a standard GRU implementation and a version optimized for HiFi4 DSPs, ensuring better performance on supported hardware.
---
#hthtemplate
Reviewed By: skrtskrtfb, mcremon-meta
Differential Revision: D81703253
@meta-codesync
meta-codesyncBot merged commit 703d25a into pytorch:mainOct 12, 2025
105 of 114 checks passed
jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@mgiordy@jirioc
Including mixed quant GRU op in Jarvis
2104245
Differential Revision: D81703253
Pull Request resolved: pytorch#15011
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