Getting state of predictions in LSTMs

[sachinruk]

This is a cross post from: https://stackoverflow.com/questions/45582185/getting-state-of-predictions-in-lstms

I have since tried to redo the model as:

batch_size = 64

model = Sequential()
model.add(Embedding(len_vocab, 64, batch_size=batch_size))
model.add(LSTM(256, return_sequences=True, stateful=True))
model.add(TimeDistributed(Dense(len_vocab, activation='softmax')))

model.compile(loss='sparse_categorical_crossentropy', optimizer='adam')
model.summary()

However, now I cannot predict one letter at a time as it is expecting a batch_size of inputs.

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