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Outdated suggestions cannot be applied.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.
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
[PyTorch] Add context parallel support for packed dataset in THD format #9540
[PyTorch] Add context parallel support for packed dataset in THD format #9540
Changes from 1 commit
c938bdd
525003e
3c69f8e
9d01092
6d240de
b9a5af4
9b506fe
File filter
Filter by extension
Conversations
Jump to
There are no files selected for viewing
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.
the position_ids means the token_id in packed sequence? how is this argument used in training fwd and bwd?
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.
The position_ids is the position of the tokens in a sequence (e.g. [0,1,2, ... , seq_len-1]). In a packed sequence, we have a list of position_ids since the packed sequence is composed of many individual sequences. I'm not too sure if that's what you mean by token_id. It's used the same way as input_ids in training fwd and bwd.
Check notice
Code scanning / CodeQL
Unused import Note