Comments (2)
Thank you for your bug report!
It seems that the data on your disk is smaller than the data for a mini-batch, can that be? If you rerun the full data preprocessing pipeline, do you still have the error? What also might help is to change the seed that you pass into the StreamBatcher:
train_batcher = StreamBatcher(Config.dataset, 'train', Config.batch_size, randomize=True, keys=input_keys, seed=88888888)
Furthermore, it would be helpful if you can replicate this bug with an existing dataset and configuration so that I can replicate it. With this I should be able to fix the bug quickly.
from conve.
There were some issues with the batch size in the evaluation procedure. The training and test batch size can now also be different. See 5feb358 for details.
I do not think this addresses the issue, but without further information, I am not able to replicate the error above.
from conve.
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from conve.