| from typing import Any |
|
|
| from transformers import AutoImageProcessor, AutoProcessor, AutoTokenizer, ProcessorMixin |
|
|
| from .configuration_vlm import VLMConfig |
|
|
|
|
| class VLMProcessor(ProcessorMixin): |
| attributes: list[str] = ["image_processor", "tokenizer"] |
| image_processor_class: str = "AutoImageProcessor" |
| tokenizer_class: str = "AutoTokenizer" |
|
|
| def __init__( |
| self, |
| image_processor: AutoImageProcessor = None, |
| tokenizer: AutoTokenizer = None, |
| **kwargs: Any, |
| ): |
| super().__init__(image_processor, tokenizer, **kwargs) |
|
|
| @classmethod |
| def from_names(cls, image_processor_name: str, tokenizer_name: str, **kwargs: Any): |
| image_processor_args = { |
| k: v for k, v in kwargs.items() if k in ["trust_remote_code", "use_fast"] |
| } |
| tokenizer_args = { |
| k: v |
| for k, v in kwargs.items() |
| if k in ["trust_remote_code", "use_fast", "model_max_length", "padding_side"] |
| } |
|
|
| tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, **tokenizer_args) |
| image_processor = AutoImageProcessor.from_pretrained( |
| image_processor_name, **image_processor_args |
| ) |
| return cls(image_processor=image_processor, tokenizer=tokenizer) |
|
|
|
|
| AutoProcessor.register(VLMConfig, VLMProcessor) |
