def run_multi_image(
        self,
        images: List[Image.Image],
        num_samples: int = 1,
        seed: int = 42,
        sparse_structure_sampler_params: dict = {},
        slat_sampler_params: dict = {},
        formats: List[str] = ['mesh', 'gaussian', 'radiance_field'],
        preprocess_image: bool = True,
        mode: Literal['stochastic', 'multidiffusion'] = 'stochastic',
    ) -> dict:
        """
        Run the pipeline with multiple images as condition

        Args:
            images (List[Image.Image]): The multi-view images of the assets
            num_samples (int): The number of samples to generate.
            sparse_structure_sampler_params (dict): Additional parameters for the sparse structure sampler.
            slat_sampler_params (dict): Additional parameters for the structured latent sampler.
            preprocess_image (bool): Whether to preprocess the image.
        """
        if preprocess_image:
            images = [self.preprocess_image(image) for image in images]
        cond = self.get_cond(images)
        cond['neg_cond'] = cond['neg_cond'][:1]
        torch.manual_seed(seed)
        ss_steps = {**self.sparse_structure_sampler_params, **sparse_structure_sampler_params}.get('steps')
        with self.inject_sampler_multi_image('sparse_structure_sampler', len(images), ss_steps, mode=mode):
            coords = self.sample_sparse_structure(cond, num_samples, sparse_structure_sampler_params)
        slat_steps = {**self.slat_sampler_params, **slat_sampler_params}.get('steps')
        with self.inject_sampler_multi_image('slat_sampler', len(images), slat_steps, mode=mode):
            slat = self.sample_slat(cond, coords, slat_sampler_params)
        return self.decode_slat(slat, formats)

        Run the pipeline with multiple images as condition

        Args:
            images (List[Image.Image]): The multi-view images of the assets
            num_samples (int): The number of samples to generate.
            sparse_structure_sampler_params (dict): Additional parameters for the sparse structure sampler.
            slat_sampler_params (dict): Additional parameters for the structured latent sampler.
            preprocess_image (bool): Whether to preprocess the image.
        
trellis/pipelines/trellis_image_to_3d.py