layers.py 文件源码

def apply(self, is_train, x, c, mask=None, context_mask=None):
        x = dropout(x, self.keep_probs, is_train)
        c = dropout(c, self.context_keep_probs, is_train)
        init = get_keras_initialization(self.init)
        x_w = tf.get_variable("merge_x_weights", (x.shape.as_list()[-1], self.output_size), initializer=init)
        c_w = tf.get_variable("merge_context_weights", (c.shape.as_list()[-1], self.output_size), initializer=init)
        output = tf.tensordot(x, x_w, axes=[[2], [0]]) + tf.expand_dims(tf.matmul(c, c_w), 1)
        if self.use_dots:
            dots = tf.einsum("aij,aj->aij", x, c)
            dot_w = tf.get_variable("dot_weights", (c.shape.as_list()[-1], self.output_size), initializer=init)
            output += tf.tensordot(dots, dot_w, axes=[[2], [0]])

        bais = tf.get_variable("merge_bias", (1, 1, self.output_size))
        output += bais
        return get_keras_activation(self.activation)(output)