def METHOD_NAME(input_channel, output_channel):
    conv_candidates = [
        '5x5_MBConv2', '5x5_MBConv4', '5x5_MBConv6', '3x3_MBConv2',
        '3x3_MBConv4', '3x3_MBConv6', '13_MixConv2', '13_MixConv4',
        '13_MixConv6', '35_MixConv2', '35_MixConv4', '35_MixConv6',
        '135_MixConv2', '135_MixConv4', '135_MixConv6', '13_LinMixConv',
        '35_LinMixConv', '135_LinMixConv', '13_RepConv2', '13_RepConv4',
        '13_RepConv6', '35_RepConv2', '35_RepConv4', '35_RepConv6',
        '135_RepConv2', '135_RepConv4', '135_RepConv6', 'Zero'
    ]
    se_candidates = ['SE_2', 'SE_4', 'SE_8', 'Zero']
    stride_stages = [(2, 2), (2, 1), (2, 1), (2, 1)]
    n_cell_stages = [5, 5, 5, 5]
    width_stages = [32, 64, 96, 123]
    conv_op_ids = [
        2, 23, 24, 26, 2, 2, 11, 27, 27, 27, 27, 2, 0, 2, 16, 10, 27, 2, 2, 2,
        22, 10, 27, 3
    ]
    net = CompactRecBackboneMixSE(2, input_channel, stride_stages,
                                  n_cell_stages, width_stages, conv_op_ids,
                                  conv_candidates, se_candidates)
    return net