layers.py 文件源码

def next_inp(self, time, output):
        """Returns the next input.

        Arguments:
          time: a `int` or unit `Tensor` representing the current timestep.
          output: a `2D Tensor` of shape `[batch_size, output_size]` representing
            the current output.

        *NOTE* that at time `t+1` the desired decoder input is the output
        from the previous step, `t`, it means that at timestep `t` the next
        input is the desired output for the very same timestep, if decoder
        inputs have been provided -- otherwise is just the current output.
        """
        if self._inputs_ta:
            output = tf.cond(
                time < self._inputs_ta.size(),
                lambda: self._inputs_ta.read(time),
                lambda: self.zero_output())  # pylint: disable=W0108
        next_inp = ops.fit(output, self._inp_size)
        return next_inp