def METHOD_NAME(self, cfg_transform):
    scale = 1.
    mean = np.array([0.485, 0.456, 0.406], dtype=np.float32)
    std = np.array([0.229, 0.224, 0.225], dtype=np.float32)
    for item in cfg_transform:
        if 'NormalizeImage' in item:
            mean = np.array(
                item['NormalizeImage']['mean'], dtype=np.float32)
            std = np.array(item['NormalizeImage']['std'], dtype=np.float32)
            if item['NormalizeImage'].get('is_scale', True):
                scale = 1. / 255.
            break
    if self.data_format == 'NHWC':
        self.scale = paddle.to_tensor(scale / std).reshape((1, 1, 1, 3))
        self.bias = paddle.to_tensor(-mean / std).reshape((1, 1, 1, 3))
    else:
        self.scale = paddle.to_tensor(scale / std).reshape((1, 3, 1, 1))
        self.bias = paddle.to_tensor(-mean / std).reshape((1, 3, 1, 1))