def format_and_load_CLIP_images(images: List[Union[str, ndarray, ImageType]], media_download_headers: dict) -> List[
    ImageType]:
    """takes in a list of strings, arrays or urls and either loads and/or converts to PIL
        for the clip model

    Args:
        images (List[Union[str, np.ndarray, ImageType]]): list of file locations or arrays (can be mixed)

    Raises:
        TypeError: _description_

    Returns:
        List[ImageType]: list of PIL images
    """
    if not isinstance(images, list):
        raise TypeError(f"expected list but received {type(images)}")

    results = []
    for image in images:
        results.append(format_and_load_CLIP_image(image, media_download_headers))

    return results
takes in a list of strings, arrays or urls and either loads and/or converts to PIL
        for the clip model

    Args:
        images (List[Union[str, np.ndarray, ImageType]]): list of file locations or arrays (can be mixed)

    Raises:
        TypeError: _description_

    Returns:
        List[ImageType]: list of PIL images
    
src/marqo/s2_inference/clip_utils.py