layers.py 文件源码

def get_output_for(self, input, **kwargs):
        input_shape = tf.shape(input)
        n_batches = input_shape[0]
        n_steps = input_shape[1]
        input = tf.reshape(input, tf.pack([n_batches, n_steps, -1]))
        c0s = tf.tile(
            tf.reshape(self.c0, (1, self.num_units)),
            (n_batches, 1)
        )
        h0s = self.nonlinearity(c0s)
        # flatten extra dimensions
        shuffled_input = tf.transpose(input, (1, 0, 2))
        hcs = tf.scan(
            self.step,
            elems=shuffled_input,
            initializer=tf.concat(1, [h0s, c0s])
        )
        shuffled_hcs = tf.transpose(hcs, (1, 0, 2))
        shuffled_hs = shuffled_hcs[:, :, :self.num_units]
        shuffled_cs = shuffled_hcs[:, :, self.num_units:]
        return shuffled_hs