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[PyTorch] Add efficient isnan for NEON half by swolchok · Pull Request #139083 · pytorch/pytorch · GitHub
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[PyTorch] Add efficient isnan for NEON half #139083
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Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) [ghstack-poisoned]
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/139083
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 2d1d999 with merge base 86602a6 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This pull request was exported from Phabricator. Differential Revision: D65003321 |
This was referenced Oct 28, 2024
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Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) [ghstack-poisoned]
|
This pull request was exported from Phabricator. Differential Revision: D65003321 |
Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) [ghstack-poisoned]
|
This pull request was exported from Phabricator. Differential Revision: D65003321 |
Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) cc jgong5 mingfeima XiaobingSuper sanchitintel ashokei jingxu10 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D65003321 |
Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) cc jgong5 mingfeima XiaobingSuper sanchitintel ashokei jingxu10 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D65003321 |
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I have fixes for this but don't want to re-kick CI on ready-to-go diffs below it in the stack... |
malfet
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Oct 31, 2024
Same as the efficient one for float when f16 hardware support is available. Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) cc jgong5 mingfeima XiaobingSuper sanchitintel ashokei jingxu10 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D65003321 |
Same as the efficient one for float when f16 hardware support is available. Testing: Added exhaustive isnan test coverage Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) cc jgong5 mingfeima XiaobingSuper sanchitintel ashokei jingxu10 [ghstack-poisoned]
|
This pull request was exported from Phabricator. Differential Revision: D65003321 |
Same as the efficient one for float when f16 hardware support is available. Testing: Added exhaustive isnan test coverage Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) cc jgong5 mingfeima XiaobingSuper sanchitintel ashokei jingxu10 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D65003321 |
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@pytorchbot merge -f "Lint + builds + relevant tests are green" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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This is the first big milestone we've been building towards! (Following rev also hooks this up to actual gemv.) Testing: To check perf, I ran python torchchat.py generate stories110M --dtype fp16 --device cpu on an x86 machine without AVX512FP16. Observed roughly 5x tokens/sec increase. Differential Revision: [D64280688](https://our.internmc.facebook.com/intern/diff/D64280688/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D64280688/)! Pull Request resolved: #137918 Approved by: https://github.com/malfet ghstack dependencies: #139082, #139083
pytorchmergebot
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Nov 1, 2024
…rchitectures (#138005) Following up on previous rev to use fp16_gemv_trans in gemv, not just gemm-used-for-gemv. Differential Revision: [D64351092](https://our.internmc.facebook.com/intern/diff/D64351092/) Pull Request resolved: #138005 Approved by: https://github.com/malfet ghstack dependencies: #139082, #139083, #137918
pytorchmergebot
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Nov 1, 2024
No real reason to have the zero-beta restriction, so let's lift it. Testing: intentionally broke new paths locally to verify test coverage existed Differential Revision: [D64407752](https://our.internmc.facebook.com/intern/diff/D64407752/) Pull Request resolved: #138275 Approved by: https://github.com/malfet ghstack dependencies: #139082, #139083, #137918, #138005
rahulsingh-intel
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Nov 5, 2024
Same as the efficient one for float when f16 hardware support is available. Testing: Added exhaustive isnan test coverage Differential Revision: [D65003321](https://our.internmc.facebook.com/intern/diff/D65003321/) Pull Request resolved: pytorch#139083 Approved by: https://github.com/malfet ghstack dependencies: pytorch#139082
rahulsingh-intel
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to rahulsingh-intel/pytorch
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Nov 5, 2024
This is the first big milestone we've been building towards! (Following rev also hooks this up to actual gemv.) Testing: To check perf, I ran python torchchat.py generate stories110M --dtype fp16 --device cpu on an x86 machine without AVX512FP16. Observed roughly 5x tokens/sec increase. Differential Revision: [D64280688](https://our.internmc.facebook.com/intern/diff/D64280688/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D64280688/)! Pull Request resolved: pytorch#137918 Approved by: https://github.com/malfet ghstack dependencies: pytorch#139082, pytorch#139083
rahulsingh-intel
pushed a commit
to rahulsingh-intel/pytorch
that referenced
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Nov 5, 2024
…rchitectures (pytorch#138005) Following up on previous rev to use fp16_gemv_trans in gemv, not just gemm-used-for-gemv. Differential Revision: [D64351092](https://our.internmc.facebook.com/intern/diff/D64351092/) Pull Request resolved: pytorch#138005 Approved by: https://github.com/malfet ghstack dependencies: pytorch#139082, pytorch#139083, pytorch#137918
rahulsingh-intel
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Nov 5, 2024
No real reason to have the zero-beta restriction, so let's lift it. Testing: intentionally broke new paths locally to verify test coverage existed Differential Revision: [D64407752](https://our.internmc.facebook.com/intern/diff/D64407752/) Pull Request resolved: pytorch#138275 Approved by: https://github.com/malfet ghstack dependencies: pytorch#139082, pytorch#139083, pytorch#137918, pytorch#138005
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Stack from ghstack (oldest at bottom):
Same as the efficient one for float when f16 hardware support is available.
Testing: Added exhaustive isnan test coverage
Differential Revision: D65003321
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10