Remove some Half support in some binary CPU kernels #33021
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💊 CircleCI build failures summary and remediationsAs of commit 59e5908: Commit 59e5908 was recently pushed. Waiting for builds... This comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions on the GitHub issue tracker. This comment has been revised 2 times. |
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so, this was already released in 1.4.0. I don't think the backwards ones matter because you can't invoke them anyway (we can remove them if we want), but probably not worth doing for mse. |
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@gchanan OK, I added a warning to the MSE kernel. |
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They were probably mistakenly added as we do not intend to support Half on CPUs in general and in these situations Half type would probably be significantly slower than their float and double counterpart due to the lack of vectorization and the need of additional casting.
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@VitalyFedyunin merged this pull request in 45818a3. |
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Feb 11, 2020
…ions on CPU For reasons similar to pytorch#33021. Note that the support of half type has not been available in any releases yet.
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…ions on CPU (#33206) Summary: For reasons similar to #33021. Note that the support of half type has not been available in any releases yet so it should be safe to remove (All forward ones concerning this PR were added in daef363 and 8cb05e7) Pull Request resolved: #33206 Differential Revision: D19861137 Pulled By: ezyang fbshipit-source-id: 38a3a398a716a782c26a611c56ddeab7eb7ac79e
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Summary: They were probably mistakenly added as we do not intend to support Half on CPUs in general and in these situations Half type would probably be significantly slower than their float and double counterpart due to the lack of vectorization and the need of additional casting. cc XiaobingSuper Pull Request resolved: pytorch#33021 Differential Revision: D19795152 Pulled By: VitalyFedyunin fbshipit-source-id: b19796db88880a46557e1b2fd06e584d46093562
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…ions on CPU (pytorch#33206) Summary: For reasons similar to pytorch#33021. Note that the support of half type has not been available in any releases yet so it should be safe to remove (All forward ones concerning this PR were added in daef363 and 8cb05e7) Pull Request resolved: pytorch#33206 Differential Revision: D19861137 Pulled By: ezyang fbshipit-source-id: 38a3a398a716a782c26a611c56ddeab7eb7ac79e
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@VitalyFedyunin @gchanan This isn't BC-breaking, right? sigmoid_backward_kernel and tanh_backward_kernel can't be accessed directly and we added a warning for MSELoss |
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Confirmed with @VitalyFedyunin offline that this is not BC breaking |
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Was added by #33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: #139961 Approved by: https://github.com/jgong5
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Was added by pytorch#33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: pytorch#139961 Approved by: https://github.com/jgong5
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Was added by pytorch#33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: pytorch#139961 Approved by: https://github.com/jgong5
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Was added by pytorch#33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: pytorch#139961 Approved by: https://github.com/jgong5
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Was added by pytorch#33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: pytorch#139961 Approved by: https://github.com/jgong5
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Dec 11, 2024
Was added by pytorch#33021, but modern CPUs right now are quite capable of handling half precision types. Alternatively one can guard the warning with `#ifdef x86_64` Pull Request resolved: pytorch#139961 Approved by: https://github.com/jgong5
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They were probably mistakenly added as we do not intend to support Half
on CPUs in general and in these situations Half type would probably be
significantly slower than their float and double counterpart due to the
lack of vectorization and the need of additional casting.
cc @XiaobingSuper