rnnlayer.py 文件源码

def preprocess_input(self, inputs, training=None):
        #if self.consume_less == 'cpu':
        #    input_shape = K.int_shape(x)
        #    input_dim = input_shape[2]
        #    timesteps = input_shape[1]

        #    x_z = time_distributed_dense(x, self.W_z, self.b_z, self.dropout_W,
        #                                 input_dim, self.units, timesteps)
        #    x_r = time_distributed_dense(x, self.W_r, self.b_r, self.dropout_W,
        #                                 input_dim, self.units, timesteps)
        #    x_h = time_distributed_dense(x, self.W_h, self.b_h, self.dropout_W,
        #                                 input_dim, self.units, timesteps)
        #    return K.concatenate([x_z, x_r, x_h], axis=2)
        #else:
        #    return x
        self.ha = K.dot(self.h, self.Ua) #time_distributed_dense(self.h, self.Ua)
        return inputs