def to(self, device, dtype) -> Dict[str, list]:
        """
        The output is the tokenized version of the prompt
        "Question: describe what you see in this image. Answer:"
        It should be of type `transformers.image_processing_base.BatchFeature`
        with `torch.Tensor` typed values for `"input_ids"`, `"attention_mask"`,
        and `"pixel_values"` keys. However, we will fake them as lists of
        integers where values are needed (`None` elsewhere) in order
        to not require `torch` or `numpy` imports.
        """
        return {
            "input_ids": [
                [2, 45641, 35, 6190, 99, 47, 192, 11, 42, 2274, 4, 31652, 35]
            ],
            "attention_mask": [[None]],
            "pixel_values": [[[[None]]]],
        }

        The output is the tokenized version of the prompt
        "Question: describe what you see in this image. Answer:"
        It should be of type `transformers.image_processing_base.BatchFeature`
        with `torch.Tensor` typed values for `"input_ids"`, `"attention_mask"`,
        and `"pixel_values"` keys. However, we will fake them as lists of
        integers where values are needed (`None` elsewhere) in order
        to not require `torch` or `numpy` imports.
        
llama-index-integrations/readers/llama-index-readers-file/tests/test_image_vision_llm.py