rnn_decoder initial_state

[bwang482]

Thanks so much for your code hunkim! It is very helpful!

Can I ask a quick question please? Am I right to think: within one batch, every time you feed model.initial_state: state to model, it overrides
self.initial_state = cell.zero_state(args.batch_size, tf.float32) (because this zero_state initialisation is also in model def__init__() thus I am not too sure whether it can be overriden )?

Thanks!

[sunxiaobiu]

The value of initial_state is updated after processing each batch of words:
outputs, last_state = seq2seq.rnn_decoder(inputs, self.initial_state, cell, loop_function=loop if infer else None, scope='rnnlm')
the zero_state model def__init__() is to initiliaze the state of the memory.
the last_state hold the state of the memory after each batch of words.

[Songweiping]

Hi @sunxiaobiu @hunkim, I am confused with initial_state, too.
After a batch, you feed feed[c]=state[i].c, feed[h]=state[i].h to model. Does this mean using last state of last batch as initial state of current batch? In outputs,last_state = seq2seq.rnn_decoder(inputs, self.initial_state, cell, loop_function=loop if infer else None, scope='rnnlm', self.initial_state would not be zero_state after first batch, am I right?
Thanks!