Comments (1)
Found an issue in the above example. The iter(self.dataset)
call doesn't reset the iterator. So if a non-infinite validation iterator is used up it the __iter__
call returns an empty iterator. I guess we have to use set_state for __iter__
calls for validation datasets.
And in case of training we can assume it's infinite and just return without setting the state.
from infinibatch.
Related Issues (11)
- Fix triggers for unit tests HOT 1
- training stuck if data loader worker process has exceptions
- Few questions on real world usage of infinibatch while training models
- InfinitePermutationSourceIterator + distributed training + shuffle HOT 2
- Can we get the length of entire dataset from `chunked_dataset_iterator`?
- Iterator will stuck when use PrefetchIterator after ParallelMapIterator, hangs indefinitely at pool.map operation of ParallelMapIterator, any ideas?
- Support for cloud streaming
- Why is setup.py empty? HOT 5
- Edit author's list in setup.py
- Add FAQ for typical programming patterns
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from infinibatch.