New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
fix lint #66572
fix lint #66572
Conversation
CI Flow Status⚛️ CI FlowRuleset - Version:
You can add a comment to the PR and tag @pytorchbot with the following commands: # ciflow rerun, "ciflow/default" will always be added automatically
@pytorchbot ciflow rerun
# ciflow rerun with additional labels "-l <ciflow/label_name>", which is equivalent to adding these labels manually and trigger the rerun
@pytorchbot ciflow rerun -l ciflow/scheduled -l ciflow/slow For more information, please take a look at the CI Flow Wiki. |
🔗 Helpful links
💊 CI failures summary and remediationsAs of commit ba48dcd (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 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 to the (internal) Dr. CI Users group. |
@suo has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
Summary: Pull Request resolved: pytorch#66572 Test Plan: Imported from OSS Reviewed By: seemethere Differential Revision: D31624043 Pulled By: suo fbshipit-source-id: 9db9cee3140d78c2a2f0c937be84755206fee1dd
* Handle shared memory cases in MathBithFallback (#63602) Summary: Pull Request resolved: #63602 This PR fixes the case when a read and write is performed on a memory shared between mutable and (or) non-mutable arguments. Example: ``` a=torch.tensor([1+1j]) b=a.conj() b.add_(a) # should return tensor([2]) but returns tensor ([2-2j]) ``` The issue here is that in the conjugate fallback, we resolve the conjugation in-place for mutable arguments which can be a problem as shown above in the case when other input arguments share memory with the mutable argument(s). This PR fixes this issue by: 1. first scanning through the operator input arguments and creating a vector of mutable arguments that have the conj bit set to `True` (and accordingly setting the flag `check_for_alias_with_mut_arg ` to `True` or `False`). 2. Iterating through all the arguments. At this time we only look at the non-mutable arguments. If `check_for_alias_with_mut_arg` is set to `True`, then we iterate through `mutable_inputs` to check if the current arg tensor in question doesn't alias any of the entries in `mutable_inputs`. If yes, then we clone the non-mutable tensor arg, else we resolve the conjugation as before. 3. Now we look through the mutable_inputs vector (which contains only mutable input tensors with conj bit set to `True`). We in-place conjugate each of the entries in the vector. 4. Do the computation. 5. Re-conjugate the mutable argument tensors. NOTE: `TensorLists` are not fully handled in ConjugateFallback. Please see the in-line comment for more details. Fixes #59943 Test Plan: Imported from OSS Reviewed By: gmagogsfm Differential Revision: D30466905 Pulled By: anjali411 fbshipit-source-id: 58058e5e6481da04a12d03f743c1491942a6cc9b * fix lint (#66572) Summary: Pull Request resolved: #66572 Test Plan: Imported from OSS Reviewed By: seemethere Differential Revision: D31624043 Pulled By: suo fbshipit-source-id: 9db9cee3140d78c2a2f0c937be84755206fee1dd Co-authored-by: anjali411 <chourdiaanjali123@gmail.com> Co-authored-by: Michael Suo <suo@fb.com>
Summary: Pull Request resolved: #66572 Test Plan: Imported from OSS Reviewed By: seemethere Differential Revision: D31624043 Pulled By: suo fbshipit-source-id: 9db9cee3140d78c2a2f0c937be84755206fee1dd
Stack from ghstack:
Differential Revision: D31624043