[blocked by #789] Fix/dataset check [wip] #883
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Hello @ethanwharris! Thanks for updating this PR. There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻 Comment last updated at 2020-02-17 16:35:12 UTC |
Borda
requested changes
Feb 17, 2020
| @@ -55,13 +55,24 @@ def init_train_dataloader(self, model): | |||
| self.get_train_dataloader = model.train_dataloader | |||
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| # determine number of training batches | |||
| if EXIST_ITER_DATASET and isinstance(self.get_train_dataloader().dataset, IterableDataset): | |||
| self.is_iterable_train_dataloader = ( | |||
| EXIST_ITER_DATASET and hasattr(self.get_train_dataloader(), 'dataset') and | |||
| self.train_percent_check) | ||
| except TypeError as e: | ||
| # Assume infinite data loading if the dataloader doesn't implement __len__ | ||
| if 'has no len' in str(e): |
Borda
changed the title
Borda
changed the title
|
Now handled in #955 |
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Before submitting
What does this PR do?
Fixes #840 - also touches part of #698
Changed Exception order so that MisconfigurationException will be called and given the correct error when using IterableDataset
Removed dependency on
Dataloader.datasetfollowing Handle abstract loader that doesn't have a dataset member #840Changed TQDM call to prevent error when
num_training_batches == float('inf')num_training_batches =float('inf')is now the default when train dataloader doesn't have__len__(in addition to when using anIterableDataset)Added test for training using an iterable
Note that these only apply to the train dataloader, test / val using
IterableDatasetwill still cause an error, but thought we should merge this first as stops a few annoying behavioursPR review
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