rnn.py 文件源码

def compile(self):
        """
        Compile the model. Should be called before training or running the model.
        Basically, this function just do checkings on model configurations,
            and create a Evaluator which contains an unrolled model
        :return: None
        """
        if self.is_compiled:  # In case of multiple compiles
            print("Already compiled!")
            return
        if self.input_shape is None or self.input_dtype is None:
            raise ValueError("input_shape or input_dtype is None, call set_input first!")
        if self.output_shape is None or self.output_dtype is None:
            raise ValueError("output_shape or output_dtype is None, call set_output first!")
        if self.target_shape is None or self.target_dtype is None:
            raise ValueError("target_shape or target_dtype is None, call set_target first!")
        if self.loss_func is None:
            raise ValueError("loss_func is None, call set_loss_func first!")
        # This operation creates no tf.Variables, no need for using variable scope
        self._cell = tf.nn.rnn_cell.MultiRNNCell(cells=self.cell_list)
        # All done
        self.is_compiled = True