Remove host-side branch on F.accuracy with ignore_label
#8364
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
|
Thank you for the PR.
I believe it causes a warning if How about using the previous code when |
|
Thank you for your quick review. |
|
Thank you! |
niboshi
added
cat:bug
niboshi
changed the title
F.accuracy with ignore_label
|
Jenkins CI test (for commit 070a110, target branch master) failed with status FAILURE. |
|
Test failure is unrelated. |
niboshi
added a commit
to niboshi/chainer
that referenced
this pull request
Nov 1, 2019
Remove host-side branch on `F.accuracy` with `ignore_label`
This was referenced Nov 1, 2019
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Outdated suggestions cannot be applied.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.
Current F.accuracy with
ignore_labelimplementation requires host-side branchif total == 0.This causes unnecessary sync between forward and backward computation.
By this PR, we can avoid this synchronization so it can accelerate CPU-intensive model training (i.e. Mixed-precision training)
I've tried the Advanced Indexing feature, but it cannot help.