| from abc import ABC, abstractmethod |
| from typing import Dict, Any, Union |
| import torch |
|
|
| class DNABaseModule(ABC): |
| def __init__(self): |
| super().__init__() |
| |
| @abstractmethod |
| def get_dnallm_key(self): |
| pass |
|
|
| @abstractmethod |
| def get_model_class(self, model_id: str, model_init_kwargs: dict): |
| pass |
|
|
| def post_model_init(self, model, processing_class): |
| pass |
|
|
| def is_embeds_input(self): |
| return False |
| |
| @abstractmethod |
| def get_processing_class(self): |
| pass |
|
|
| @abstractmethod |
| def get_dnallm_modules_keywords(self): |
| pass |
|
|
| @abstractmethod |
| def get_custom_multimodal_keywords(self): |
| pass |
|
|
| @abstractmethod |
| def get_non_generate_params(self): |
| pass |
|
|
| @abstractmethod |
| def get_custom_processing_keywords(self): |
| pass |
|
|
| @abstractmethod |
| def prepare_prompt(self, processing_class, inputs: dict[str, Union[torch.Tensor, Any]]): |
| pass |
| |
| @abstractmethod |
| def prepare_model_inputs(self, processing_class, prompts_text, images, return_tensors, padding, padding_side, add_special_tokens): |
| pass |
