feedback.py 文件源码

def next_inputs(self, time, sample_ids=None, prev_finished=None):
        if sample_ids is None or self.teacher_rate > 0.:
            finished = tf.greater_equal(time + 1, self.sequence_length)
        else:
            finished = math_ops.logical_or(
                tf.greater_equal(time + 1, self.max_step),
                tf.equal(self.eos_id, sample_ids))

        if self.teacher_rate == 1. or (sample_ids is None):
            next_input_ids = self._input_tas.read(time)
            return finished, self.lookup(next_input_ids)

        if self.teacher_rate > 0.:
            # scheduled
            teacher_rates = tf.less_equal(
                tf.random_uniform(tf.shape(sample_ids), minval=0., maxval=1.),
                self.teacher_rate)
            teacher_rates = tf.to_int32(teacher_rates)

            next_input_ids = (teacher_rates * self._input_tas.read(time)
                              + (1 - teacher_rates) * sample_ids)
        else:
            next_input_ids = sample_ids

        return finished, self.lookup(next_input_ids)