recurrent_convolutional.py 文件源码

def reset_states(self):
        assert self.stateful, 'Layer must be stateful.'
        input_shape = self.input_shape
        if not input_shape[0]:
            raise Exception('If a RNN is stateful, a complete ' +
                            'input_shape must be provided ' +
                            '(including batch size).')

        if self.return_sequences:
            out_row, out_col, out_filter = self.output_shape[2:]
        else:
            out_row, out_col, out_filter = self.output_shape[1:]

        if hasattr(self, 'states'):
            K.set_value(self.states[0],
                        np.zeros((input_shape[0],
                                  out_row, out_col, out_filter)))
            K.set_value(self.states[1],
                        np.zeros((input_shape[0],
                                  out_row, out_col, out_filter)))
        else:
            self.states = [K.zeros((input_shape[0],
                                    out_row, out_col, out_filter)),
                           K.zeros((input_shape[0],
                                    out_row, out_col, out_filter))]