custom_layers.py 文件源码

def preprocess_input(self, x):
        if self.consume_less == 'cpu':
            input_shape = self.input_spec[0].shape
            input_dim = input_shape[2]
            timesteps = input_shape[1]
            return time_distributed_dense(x, self.W, None, self.dropout_W,
                                          input_dim, self.output_dim,
                                          timesteps)
        else:
            return x

    # override Recurrent's get_initial_states function to load the trainable
    # initial hidden state