def METHOD_NAME():
    # test tsn from timm
    register_all_modules()
    config = get_recognizer_cfg(
        'tsn/tsn_imagenet-pretrained-r50_8xb32-1x1x3-100e_kinetics400-rgb.py')
    timm_backbone = dict(type='timm.efficientnet_b0', pretrained=False)
    config.model['backbone'] = timm_backbone
    config.model['cls_head']['in_channels'] = 1280
    input_shape = (1, 3, 3, 32, 32)
    train_test_step(config, input_shape)
    import timm
    if digit_version(timm.__version__) <= digit_version('0.6.7'):
        feature_shape = 'NLC'
    else:
        feature_shape = 'NHWC'
    timm_swin = dict(
        type='timm.swin_base_patch4_window7_224',
        pretrained=False,
        feature_shape=feature_shape)
    config.model['backbone'] = timm_swin
    config.model['cls_head']['in_channels'] = 1024
    input_shape = (1, 3, 3, 224, 224)
    train_test_step(config, input_shape)