Trace attention inference patterns with p=0, cleanup #109118
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| args2 = self._clone_inputs(args1) | ||
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| for training in [False, True]: | ||
| for training in [False] + ([True] if check_train else []): |
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nit [False, Train] if check_train else [False]
When dropout is traced in inference, it creates a clone() instead of training pattern of rand() etc. This was partially addressed by manually #108141, however that did not cover all of the patterns that included dropout, and there is no reason we should have to specify them manually. This updates the inference patterns generated to trace with dropout_p = 0.0. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng Xia-Weiwen wenzhe-nrv jiayisunx peterbell10 ipiszy ngimel yf225 chenyang78 kadeng muchulee8 aakhundov [ghstack-poisoned]
When dropout is traced in inference, it creates a clone() instead of training pattern of rand() etc. This was partially addressed by manually #108141, however that did not cover all of the patterns that included dropout, and there is no reason we should have to specify them manually. This updates the inference patterns generated to trace with dropout_p = 0.0. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng Xia-Weiwen wenzhe-nrv jiayisunx peterbell10 ipiszy ngimel yf225 chenyang78 kadeng muchulee8 aakhundov [ghstack-poisoned]
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When dropout is traced in inference, it creates a clone() instead of training pattern of rand() etc. This was partially addressed by manually #108141, however that did not cover all of the patterns that included dropout, and there is no reason we should have to specify them manually. This updates the inference patterns generated to trace with dropout_p = 0.0. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng Xia-Weiwen wenzhe-nrv jiayisunx peterbell10 ipiszy ngimel yf225 chenyang78 kadeng muchulee8 aakhundov [ghstack-poisoned]
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Stack from ghstack (oldest at bottom):
When dropout is traced in inference, it creates a clone() instead of training pattern of rand() etc. This was partially addressed by manually #108141, however that did not cover all of the patterns that included dropout, and there is no reason we should have to specify them manually.
This updates the inference patterns generated to trace with dropout_p = 0.0.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @ngimel @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov