| import torch |
| from abc import ABC, abstractmethod |
|
|
|
|
| class AbstractProcessor(ABC): |
| """ |
| Abstract class for processors to show what methods they need to implement. |
| Processors handle text encoding and image preprocessing. |
| """ |
| @abstractmethod |
| def encode_text(self, prompt): |
| pass |
|
|
| @abstractmethod |
| def preprocess_images(self, images: list): |
| pass |
|
|
|
|
| class FlamingoProcessor(AbstractProcessor): |
| """ |
| Processor class for Flamingo. |
| """ |
| def __init__(self, tokenizer, vision_processor): |
| """ |
| OF does not use same vision processor, image_processor only transforms single image |
| """ |
| self.tokenizer = tokenizer |
| self.vision_processor = vision_processor |
| |
| def encode_text(self, prompt): |
| self.tokenizer.padding_side = "left" |
| |
| return self.tokenizer([prompt], |
| return_tensors="pt", |
| ) |
| |
| def preprocess_images(self, images: list): |
| vision_x = [self.vision_processor(im).unsqueeze(0) for im in images] |
| vision_x = torch.cat(vision_x, dim=0) |
| return vision_x |
|
|
| def clean_generation(response): |
| """ |
| for some reason, the open-flamingo based model slightly changes the input prompt (e.g. prepends <unk>, an adds some spaces) |
| """ |
| return response.replace('<unk> ', '').strip() |
