Model object abstraction and refactoring

[RemyLau]

• Model metadata, e.g., description, training info, params
• Abstract methods (standardize in/out format)
  • fit(*args, **kwargs) -> None
  • predict(*args, **kwargs) -> Union[np.ndarray, torch.Tensor, other?]
  • fit_predict shortcut function combining fit and predict
  • score(*args, **kwargs) -> float (determine the type of metric via metric: Union[str, Callable], default setting saved in class attr. Abstract class per type of tasks?)
  • __repr__ (show model metadata and info)
• Model saving and loading (checkpointing)?

TODOs

• [x] single_modality/cell_type_annotation (#163, #164)
• [x] single_modality/clustering
• [ ] single_modality/imputation
• [ ] multi_modality/joint_embedding
• [ ] multi_modality/match_modality
• [ ] multi_modality/predict_modality
• [x] spatial/cell_type_deconvo
• [x] spatial/spatial_domain