Make iter persistent for AdagradW #4147
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This pull request was exported from Phabricator. Differential Revision: D74717848 |
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Summary: X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: Pull Request resolved: pytorch#4147 X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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This pull request was exported from Phabricator. Differential Revision: D74717848 |
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Summary: Pull Request resolved: pytorch#4147 X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: Pull Request resolved: pytorch#4147 X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary: Pull Request resolved: pytorch#4147 X-link: facebookresearch/FBGEMM#1228 Make iter persistent for AdagradW optimizer state saving. This is to avoid potential loss of the iter information when training is restarted. Reviewed By: q10 Differential Revision: D74717848
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Summary:
Make iter persistent for AdagradW optimizer state saving.
This is to avoid potential loss of the iter information when training is restarted.
Differential Revision: D74717848