import tensorflow as tf


        output_ = generate(output, input_, context)

        argmax = lambda: tf.argmax(output_, 1)
        target = lambda: inputs.read(time + 1)
        softmax = lambda: tf.squeeze(tf.multinomial(tf.log(tf.nn.softmax(output_)), num_samples=1),
                                     axis=1)

        use_target = tf.logical_and(time < time_steps - 1, tf.random_uniform([]) >= feed_previous)
        predicted_symbol = tf.case([
