I have written an RNN language model using TensorFlow. The model is implemented as an RNN
class. The graph structure is built in the constructor, while RN
A simple way to feed in an RNN state is to simply feed in both components of the state tuple individually.
# Constructing the graph
self.state = rnn_cell.zero_state(...)
self.output, self.next_state = tf.nn.dynamic_rnn(
rnn_cell,
self.input,
initial_state=self.state)
# Running with initial state
output, state = sess.run([self.output, self.next_state], feed_dict={
self.input: input
})
# Running with subsequent state:
output, state = sess.run([self.output, self.next_state], feed_dict={
self.input: input,
self.state[0]: state[0],
self.state[1]: state[1]
})