def swin_t(**kwargs):
    from config import get_config_swin_t
    config = get_config_swin_t()
    model = SwinTransformer(img_size=config.DATA.IMG_SIZE, patch_size=config.MODEL.SWIN.PATCH_SIZE, in_chans=config.MODEL.SWIN.IN_CHANS, num_classes=config.MODEL.NUM_CLASSES, embed_dim=config.MODEL.SWIN.EMBED_DIM, depths=config.MODEL.SWIN.DEPTHS, num_heads=config.MODEL.SWIN.NUM_HEADS, window_size=config.MODEL.SWIN.WINDOW_SIZE, mlp_ratio=config.MODEL.SWIN.MLP_RATIO, qkv_bias=config.MODEL.SWIN.QKV_BIAS, qk_scale=config.MODEL.SWIN.QK_SCALE, drop_rate=config.MODEL.DROP_RATE, drop_path_rate=config.MODEL.DROP_PATH_RATE, ape=config.MODEL.SWIN.APE, patch_norm=config.MODEL.SWIN.PATCH_NORM, use_checkpoint=config.TRAIN.USE_CHECKPOINT)
    return model
def swin_t(**kwargs):
    from config import get_config_swin_t
    config = get_config_swin_t()
    model = SwinTransformer(img_size=config.DATA.IMG_SIZE, patch_size=config.MODEL.SWIN.PATCH_SIZE, in_chans=config.MODEL.SWIN.IN_CHANS, num_classes=config.MODEL.NUM_CLASSES, embed_dim=config.MODEL.SWIN.EMBED_DIM, depths=config.MODEL.SWIN.DEPTHS, num_heads=config.MODEL.SWIN.NUM_HEADS, window_size=config.MODEL.SWIN.WINDOW_SIZE, mlp_ratio=config.MODEL.SWIN.MLP_RATIO, qkv_bias=config.MODEL.SWIN.QKV_BIAS, qk_scale=config.MODEL.SWIN.QK_SCALE, drop_rate=config.MODEL.DROP_RATE, drop_path_rate=config.MODEL.DROP_PATH_RATE, ape=config.MODEL.SWIN.APE, patch_norm=config.MODEL.SWIN.PATCH_NORM, use_checkpoint=config.TRAIN.USE_CHECKPOINT)
    return model