def METHOD_NAME(conv, bn):
    '''fuse conv and bn for eval'''
    assert (not (conv.training or bn.training)), "Fusion only for eval!"
    fused_conv = copy.deepcopy(conv)
    fused_weight, fused_bias = _fuse_conv_bn_weights(
        fused_conv.weight, fused_conv.bias, bn._mean, bn._variance, bn._epsilon,
        bn.weight, bn.bias)
    fused_conv.weight.set_value(fused_weight)
    if fused_conv.bias is None:
        fused_conv.bias = paddle.create_parameter(
            shape=[fused_conv._out_channels], is_bias=True, dtype=bn.bias.dtype)
    fused_conv.bias.set_value(fused_bias)
    return fused_conv