code: def initial_state(self, batch_size, dtype=tf.float32, trainable=False,
                      trainable_initializers=None, trainable_regularizers=None,
                      name=None):
      
      core_initial_state = self._core.initial_state(
          batch_size, dtype=dtype, trainable=trainable,
          trainable_initializers=trainable_initializers,
          trainable_regularizers=trainable_regularizers, name=name)
  
      dropout_masks = [None] * len(self._dropout_state_size)
      def set_dropout_mask(index, state, keep_prob):
        if index is not None:
          ones = tf.ones_like(state, dtype=dtype)
          dropout_masks[index] = tf.nn.dropout(ones, keep_prob=keep_prob)
      tf.contrib.framework.nest.map_structure(
          set_dropout_mask,
          self._dropout_indexes, core_initial_state, self._keep_probs)
  
      return core_initial_state, dropout_masks
docs: Builds the default start state tensor of zeros.