-
Notifications
You must be signed in to change notification settings - Fork 3k
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
Support inplace update for PythonOp/Grad #17687
Merged
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
pengwa
added
the
training
issues related to ONNX Runtime training; typically submitted using template
label
Sep 25, 2023
askhade
reviewed
Sep 26, 2023
askhade
reviewed
Sep 26, 2023
askhade
reviewed
Sep 26, 2023
orttraining/orttraining/core/framework/torch/custom_function_register.cc
Show resolved
Hide resolved
askhade
reviewed
Sep 27, 2023
askhade
reviewed
Sep 27, 2023
pengwa
commented
Sep 27, 2023
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Thanks for the comment. Fixed most of them.
orttraining/orttraining/core/framework/torch/custom_function_register.cc
Show resolved
Hide resolved
…pythonop_inplace
…pythonop_inplace
askhade
reviewed
Oct 9, 2023
pengwa
force-pushed
the
pythonop_inplace
branch
from
October 9, 2023 23:44
0c98c49
to
58ea7d1
Compare
askhade
approved these changes
Oct 11, 2023
kleiti
pushed a commit
to kleiti/onnxruntime
that referenced
this pull request
Mar 22, 2024
### Support inplace update for PythonOp/Grad This PR is based on another PR microsoft#17685 branch, to make it easier to review. With PR: PR microsoft#17685, By default all PythonOp inputs/outputs are assumed to not be inplaced, if during run, we found some inplace update happens (by checking output data address with all inputs data address), we add clone before set it as PythonOp/Grad's outputs. In this case, results are correct, but implicit copies overheads are introduced. This PR allow users to define output input reuse map, to let ORT know how to do the reuse map, avoid such unnecessary copies.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Support inplace update for PythonOp/Grad
This PR is based on another PR #17685 branch, to make it easier to review.
With PR: PR #17685, By default all PythonOp inputs/outputs are assumed to not be inplaced, if during run, we found some inplace update happens (by checking output data address with all inputs data address), we add clone before set it as PythonOp/Grad's outputs. In this case, results are correct, but implicit copies overheads are introduced.
This PR allow users to define output input reuse map, to let ORT know how to do the reuse map, avoid such unnecessary copies.