import tensorflow as tf

            state = tf.concat([state, context, pos, new_weights], axis=1)
            return state, logits

    def _time_step(time, input_, input_symbol, pos, state, output, outputs, states, weights, attns, prev_weights,
                   samples, context):
        if decoder.conditional_rnn:
            with tf.variable_scope('conditional_1'):
                output, state = update(state, input_)
        elif decoder.update_first:
            output, state = update(state, input_, None, input_symbol)

        context, new_weights = look(time, output, input_, pos=pos, prev_weights=prev_weights, context=context)
