tf.contrib.training.NextQueuedSequenceBatch.save_state()

tf.contrib.training.NextQueuedSequenceBatch.save_state(state_name, value, name=None)

Returns an op to save the current batch of state state_name.

Args:

• state_name: string, matches a key provided in initial_states.

• value: A Tensor. Its type must match that of initial_states[state_name].dtype. If we had at input:

  initial_states[state_name].get_shape() == [d1, d2, ...]
  

  then the shape of value must match:

  tf.shape(value) == [batch_size, d1, d2, ...]
  

• name: string (optional). The name scope for newly created ops.

Returns:

A control flow op that stores the new state of each entry into the state saver. This op must be run for every iteration that accesses data from the state saver (otherwise the state saver will never progress through its states and run out of capacity).

Raises:

• KeyError: if state_name does not match any of the initial states declared in initial_states.