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fchollet / deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"
MIT License
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5.14 Training Convnet with data-augmentation generators #152

Open ghimireadarsh opened 3 years ago

ghimireadarsh commented 3 years ago

Why the batchsize = 32, should it not be 20? Since the steps_per_epoch = 100 and there is issue when using the generator in this way, since the batchsize is not matching up with amount of data being generated. Thus the current keras generator requires to use repeat() in generator to matchup data generated. Correct me if I am wrong

ghimireadarsh commented 3 years ago

Steps per epoch should be equal to sample//batch_size

cocoma16 commented 3 years ago

I have the same question when I use batchsize=32, it gives me the error. 63/100 [=================>............] - ETA: 7s - loss: 0.6931 - acc: 0.5150WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least steps_per_epoch * epochs batches (in this case, 10000 batches). You may need to use the repeat() function when building your dataset.