Fix passing Accelerator objects to the accelerator flag with devices=x & resolve training type plugin
#10773
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kaushikb11
added
accelerator
bug
kaushikb11
requested review from
awaelchli,
Borda,
carmocca,
justusschock,
rohitgr7,
SeanNaren,
tchaton and
williamFalcon
as code owners
kaushikb11
changed the title
kaushikb11
changed the title
Accelerator objects to the accelerator flag with devices=x & resolve training type plugin
rohitgr7
reviewed
Nov 26, 2021
awaelchli
reviewed
Nov 27, 2021
awaelchli
approved these changes
Nov 29, 2021
| - Fixed passing `Accelerator` objects to the accelerator flag with `devices=x` ([#10773](https://github.com/PyTorchLightning/pytorch-lightning/pull/10773)) | ||
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| - Resolve training type plugin when passed within `Accelerator` ([#10773](https://github.com/PyTorchLightning/pytorch-lightning/pull/10773)) |
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I am confused by this fix. IMO it is not worth doing that considering the refactors that happen right now for 1.6. I could however see this being included in 1.5.x
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@awaelchli But it would be required for 1.5.x, right?
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Yes sure, it can be merged to master first, then be included in 1.5.x, but then tests that you add here become mostly outdated immediately after. That's all I'm saying.
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In that case, let's just change the target branch to the bugfix release branch
tchaton
approved these changes
Nov 30, 2021
| ] | ||
| assert not trainer.training_type_plugin.sync_batchnorm | ||
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| trainer = Trainer(accelerator=CPUAccelerator(PrecisionPlugin(), DDPPlugin()), devices=2, sync_batchnorm=True) |
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Suggested change
| trainer = Trainer(accelerator=CPUAccelerator(PrecisionPlugin(), DDPPlugin()), devices=2, sync_batchnorm=True) | |
| trainer = Trainer(accelerator=CPUAccelerator(PrecisionPlugin(), DDPPlugin()), devices=2) |
Borda
approved these changes
Nov 30, 2021
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Closing it. As the issue has been resolved after the AcceleratorConnector refactor |
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What does this PR do?
Fixes #10592
Fixes #10775
Does your PR introduce any breaking changes? If yes, please list them.
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cc @Borda @tchaton @akihironitta