-
Notifications
You must be signed in to change notification settings - Fork 205
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
[BE] replace the extra DeviceMesh _flatten with mesh access #667
Merged
Merged
Changes from all commits
Commits
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
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
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
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,28 @@ | ||
# Copyright (c) Meta Platforms, Inc. and affiliates. | ||
# All rights reserved. | ||
# | ||
# This source code is licensed under the BSD-style license found in the | ||
# LICENSE file in the root directory of this source tree. | ||
from typing import Optional | ||
|
||
import torch | ||
from torchtitan.logging import logger | ||
|
||
|
||
def check_if_feature_in_pytorch( | ||
feature_name: str, | ||
pull_request: str, | ||
min_nightly_version: Optional[str] = None, | ||
) -> None: | ||
if "git" in torch.__version__: # pytorch is built from source | ||
# notify users to check if the pull request is included in their pytorch | ||
logger.warning( | ||
"detected that the pytorch is built from source. Please make sure the PR " | ||
f"({pull_request_link}) is included in pytorch for correct {feature_name}." | ||
) | ||
elif min_nightly_version is not None and torch.__version__ < min_nightly_version: | ||
logger.warning( | ||
f"detected that the pytorch version {torch.__version__} is older than " | ||
f"{min_nightly_version}. Please upgrade a newer version to include the " | ||
f"change in ({pull_request_link}) for correct {feature_name}." | ||
) |
Oops, something went wrong.
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.
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.
@fegin
Since we are already suggesting user to use latest PyTorch nightly, I wonder how necessary it is to include such messages, as multiple features would depend on non-stable release. E.g. for PP, we constantly see new features, without such try-catches.
Not saying this is not good, but there seems to be a trade-off / sacrifice for dev velocity and simplicity.
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.
I'm okay to remove it. Or we can periodically cleanup (like weekly). In general, this is not just for the end users but also for developers like us who may not up the local PyTorch reguarly.