rnn_base.py 文件源码

def noisy_inputs(self) -> tf.Tensor:
        """
        Return the input sequence, with noise added according to the `input_noise` parameter.

        If the `input_noise` parameter is not set, this method simply returns the input sequence. Otherwise, return a 
        tensor in which each time step of the input sequence is randomly set to zeros with probability given by the
        `input_noise` parameter.

        Returns
        -------
        tf.Tensor
            The input sequence, with noise added according to the `input_noise` parameter
        """
        if self.input_noise is None:
            return self.inputs

        # drop entire time steps with probability self.noise
        randoms = tf.random_uniform([self.max_step, self.batch_size], minval=0, maxval=1)
        randoms = tf.stack([randoms] * self.num_features, axis=2)

        result = tf.where(randoms > self.input_noise, self.inputs, tf.zeros_like(self.inputs))

        return result