Support sine operator on XNNPACK - #14711

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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.

Differential Revision: D83623086

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@GregoryComerGregoryComer added the release notes: xnnpack Changes to the XNNPack backend delegate label Oct 1, 2025
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.

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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
@GregoryComer
GregoryComer merged commit 6efddba into pytorch:mainOct 13, 2025
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cherry pick on to 1.0?

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cherry pick on to 1.0?

I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.

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@pytorchbot cherry-pick --onto release/1.0 -c critical

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@GregoryComer@pytorchbot
Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711

The cherry pick PR is at #15144 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated:

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Comment threadbackends/xnnpack/test/ops/test_sin.py
Comment on lines +82 to +83
[0.0, 0.1, 0.5, 0.785398],
[-0.5, -0.785398, 1.5708, -1.5708],

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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?

jirioc pushed a commit to nxp-upstream/executorch that referenced this pull request Dec 19, 2025
@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Support sine operator on XNNPACK - #14711
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Support sine operator on XNNPACK#14711
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Note: Links to docs will display an error until the docs builds have been completed.
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
@GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
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Comment threadbackends/xnnpack/test/ops/test_sin.py

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 [0.0, 0.1, 0.5, 0.785398],
 [-0.5, -0.785398, 1.5708, -1.5708],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
jirioc pushed a commit
to nxp-upstream/executorch
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@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Support sine operator on XNNPACK - #14711
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Support sine operator on XNNPACK#14711
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14711
Note: Links to docs will display an error until the docs builds have been completed.
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
@GregoryComer
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merged commit 6efddba
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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@GregoryComer@pytorchbot
Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
The cherry pick PR is at #15144 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated:
Details for Dev Infra team
Raised by workflow job
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Comment threadbackends/xnnpack/test/ops/test_sin.py

Comment on lines

+82
 to 
+83

 [0.0, 0.1, 0.5, 0.785398],
 [-0.5, -0.785398, 1.5708, -1.5708],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
jirioc pushed a commit
to nxp-upstream/executorch
that referenced
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Dec 19, 2025
@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Support sine operator on XNNPACK - #14711
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14711
Note: Links to docs will display an error until the docs builds have been completed.
❌ 2 New Failures, 1 Cancelled Job
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
The cherry pick PR is at #15144 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated:
Details for Dev Infra team
Raised by workflow job
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Comment threadbackends/xnnpack/test/ops/test_sin.py

Comment on lines

+82
 to 
+83

 [0.0, 0.1, 0.5, 0.785398],
 [-0.5, -0.785398, 1.5708, -1.5708],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
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Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
@GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
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Comment threadbackends/xnnpack/test/ops/test_sin.py

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 [0.0, 0.1, 0.5, 0.785398],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
jirioc pushed a commit
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@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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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");
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Support sine operator on XNNPACK - #14711
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
@GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
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Comment threadbackends/xnnpack/test/ops/test_sin.py

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 [0.0, 0.1, 0.5, 0.785398],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
jirioc pushed a commit
to nxp-upstream/executorch
that referenced
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Dec 19, 2025
@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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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");
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
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Comment threadbackends/xnnpack/test/ops/test_sin.py

Comment on lines

+82
 to 
+83

 [0.0, 0.1, 0.5, 0.785398],
 [-0.5, -0.785398, 1.5708, -1.5708],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
jirioc pushed a commit
to nxp-upstream/executorch
that referenced
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Dec 19, 2025
@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14711
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@GregoryComer has exported this pull request. If you are a Meta employee, you can view the originating Diff in D83623086.
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Cosine is coming in D83623619, will export as a PR once this is merged because I didn't use ghexport.
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Support sine operator on XNNPACK (pytorch#14711)
68f6f0e
Summary:
Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
Pulled By: GregoryComer
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cherry pick on to 1.0?
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cherry pick on to 1.0?
I wasn't originally planning to, given that it's late, but it's reasonably low risk so I'm okay to pick it if you'd like.
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@pytorchbot cherry-pick --onto release/1.0 -c critical
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Support sine operator on XNNPACK (#14711)
2e2916b
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
(cherry picked from commit 6efddba)
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Cherry picking #14711
The cherry pick PR is at #15144 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated:
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 [0.0, 0.1, 0.5, 0.785398],
 [-0.5, -0.785398, 1.5708, -1.5708],
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XNNPACK does use a faster approximation algorithm, and does have tests against std::sin(), with atol/rotl = 3*std::numeric_limits<T>::epsilon() and 5*std::numeric_limits<T>::epsilon(), which is also used by ET::Portable::sin(), so some tolerance will be required. I guess we can increase the tensor sizes here and perhaps find the tolerance required, and live with that for now?
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@GregoryComer@jirioc
Support sine operator on XNNPACK (pytorch#14711)
0084e2e
Summary: Wire up the unary sine operator in xnnpack for fp32 and fp16.
Differential Revision: D83623086
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