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License: BSD 2-Clause "Simplified" License
Neural networks library on top of theano
License: BSD 2-Clause "Simplified" License
Consider storing a network's hyperparameters in a JSON or YAML file instead of hdf5.
hdf5 could be only used for storing weights.
So far, each Monitor can only monitor a single scalar. Would be nice to extend to vectors
In trainer.py, you define: self.n_train_batches = ds.n_train / self.batch_size
What happens if ds.n_train is not a multiple of self.batch_size? Eg n_train=166 and batch_size=20, then n_train_batches=8. So we are not using the last 6 elements in the training set.
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