def initialize_rnn_state(state):
 if isinstance(state, tf.nn.rnn_cell.LSTMStateTuple):
  c = state.c.eval()
  h = state.h.eval()
  return (c, h)
 else:
  new_state = state.eval()
  return new_state

def initialize_rnn_state ( state ) : if isinstance ( state , tf . nn . rnn_cell . LSTMStateTuple ) : c = state . c . eval ( ) h = state . h . eval ( ) return ( c , h ) else : new_state = state . eval ( ) return new_state
return the initialized rnn state .