def _encode_image(self, inputs: List[Tensor], normalize: bool = True):
        """
        Args:
            inputs: A list of processed image tensors.
            normalize: Whether to normalize the output.
        """
        # Format the inputs to the required data structure for the model
        formated_input = {"image":{"pixel_values": torch.cat(inputs, dim=0)}}

        with torch.no_grad():
            outputs = self._model(formated_input)["image"]

        if normalize:
            outputs /= self.normalize(outputs)
            if outputs.shape != outputs.shape:  # Check if normalization changed the shape
                raise InternalError("Normalization changed the shape of the output tensor.")
        return self._convert_output(outputs)

        Args:
            inputs: A list of processed image tensors.
            normalize: Whether to normalize the output.
        
src/marqo/inference/native_inference/embedding_models/languagebind_model.py