-
Notifications
You must be signed in to change notification settings - Fork 3.5k
Set devices to 1 when it's just Trainer(accelerator='auto')
#10192
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
Conversation
for more information, see https://pre-commit.ci
Shouldn't we use all available devices for that type of device then? |
Then what would be the difference between |
for more information, see https://pre-commit.ci
I am putting this PR on hold. IMO, if a user just does Trainer(accelerator="auto"), we should crash it and ask them to pass devices=x or gpus if it had GPUs.(like we do right now) Rather than assigning only one device for them. @PyTorchLightning/core-contributors |
It could also default to |
@kaushikb11 where is the discussion/issue/RFC describing what these PRs are trying to accomplish? it is very hard to review this without that background. |
I'm not aware of the context outside this PR at all, but I don't think we should accept this change. If it were more common to use only one device out of multiple devices than using all of them, it'd be fine, but it's not common, right? In my opinion, it should default to |
Codecov Report
@@ Coverage Diff @@
## master #10192 +/- ##
========================================
- Coverage 92% 89% -4%
========================================
Files 181 181
Lines 16424 16424
========================================
- Hits 15178 14545 -633
- Misses 1246 1879 +633 |
IMO, I believe accelerator="auto" should be the default and devices become a required argument. |
|
What does this PR do?
Set devices to 1 when it's just
Trainer(accelerator='auto')
Does your PR introduce any breaking changes? If yes, please list them.
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?
Make sure you had fun coding 🙃