relevance_based.py 文件源码

def _invert_DenseLayer(self,layer,feeder):
        # Warning they are swapped here
        feeder = self._put_rectifiers(feeder, layer)
        feeder = self._get_normalised_relevance_layer(layer, feeder)

        output_units = np.prod(L.get_output_shape(layer.input_layer)[1:])
        output_layer = L.DenseLayer(feeder, num_units=output_units)
        W = output_layer.W
        tmp_shape = np.asarray((-1,)+L.get_output_shape(output_layer)[1:])
        x_layer = L.ReshapeLayer(layer.input_layer, tmp_shape.tolist())
        output_layer = L.ElemwiseMergeLayer(incomings=[x_layer, output_layer],
                                            merge_function=T.mul)
        output_layer.W = W
        return output_layer