-
Notifications
You must be signed in to change notification settings - Fork 3.4k
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
Default benchmark
based on deterministic
flag
#11944
Default benchmark
based on deterministic
flag
#11944
Conversation
for more information, see https://pre-commit.ci
…rshrimali/pytorch-lightning into feature/9128_benchmark_trainer_default
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.
LGTM!
I pushed one commit with docs changes after searching for how to properly reference another parameter. Also added one reference to PyTorch's docs about randomness.
Co-authored-by: Carlos Mocholí <[email protected]>
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.
LGTM!
…rshrimali/pytorch-lightning into feature/9128_benchmark_trainer_default
Co-authored-by: Adrian Wälchli <[email protected]>
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.
GTLM
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.
LGTM
small comments.
Co-authored-by: Rohit Gupta <[email protected]>
Co-authored-by: Carlos Mocholí <[email protected]>
Co-authored-by: Carlos Mocholí <[email protected]>
…hmark_trainer_default
What does this PR do?
benchmark
flag ofTrainer
classOptional
, and defaults to the value based ondeterministic
flag. Also allows manually overwriting the flag.Fixes #9128.
Does your PR introduce any breaking changes? If yes, please list them.
No!
Before submitting
PR review
Anyone in the community is welcome to review the PR.
Before you start reviewing make sure you have read Review guidelines. In short, see the following bullet-list:
Did you have fun?
Thanks to @carmocca for helping me with this PR. 🎉