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Allow dataloaders without sampler field present (#1907)

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* Allow dataloaders without sampler field present

Sometimes we have a custom dataloader that doesn't have a sampler, better to check that the field is there before reading it.

* chlog

Co-authored-by: Jirka <jirka@pytorchlightning.ai>
This commit is contained in:
Maxim Grechkin
2020-05-20 20:57:12 +00:00
committed by GitHub
co-authored by Jirka
parent c717873d26
commit 98f7842970
2 changed files with 4 additions and 1 deletions
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CHANGELOG.md
+3 -1
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@@ -10,7 +10,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
- Add Metric Base Classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
- Added type hints in `Trainer.fit()` and `Trainer.test()` to reflect that also a list of dataloaders can be passed in ([#1723](https://github.com/PyTorchLightning/pytorch-lightning/pull/1723)).
- Added type hints in `Trainer.fit()` and `Trainer.test()` to reflect that also a list of dataloaders can be passed in ([#1723](https://github.com/PyTorchLightning/pytorch-lightning/pull/1723))
- Allow dataloaders without sampler field present ([#1907](https://github.com/PyTorchLightning/pytorch-lightning/pull/1907))
### Changed
pytorch_lightning/trainer/training_loop.py
+1
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@@ -327,6 +327,7 @@ class TrainerTrainLoopMixin(ABC):
self.reset_train_dataloader(model)
# set seed for distributed sampler (enables shuffling for each epoch)
if (self.use_ddp or self.use_horovod) \
and hasattr(self.train_dataloader, 'sampler') \
and hasattr(self.train_dataloader.sampler, 'set_epoch'):
self.train_dataloader.sampler.set_epoch(epoch)