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			92 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			92 lines
		
	
	
		
			2.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from __future__ import annotations
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| 
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| from abc import ABC, abstractmethod
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| from pathlib import Path
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| from shutil import rmtree
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| from typing import Any
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| from zipfile import BadZipFile
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| 
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| from onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf  # type: ignore
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| 
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| from ..config import get_cache_dir
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| from ..schemas import ModelType
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| 
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| 
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| class InferenceModel(ABC):
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|     _model_type: ModelType
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| 
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|     def __init__(
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|         self, model_name: str, cache_dir: Path | str | None = None, eager: bool = True, **model_kwargs: Any
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|     ) -> None:
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|         self.model_name = model_name
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|         self._loaded = False
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|         self._cache_dir = Path(cache_dir) if cache_dir is not None else get_cache_dir(model_name, self.model_type)
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|         loader = self.load if eager else self.download
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|         try:
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|             loader(**model_kwargs)
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|         except (OSError, InvalidProtobuf, BadZipFile):
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|             self.clear_cache()
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|             loader(**model_kwargs)
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| 
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|     def download(self, **model_kwargs: Any) -> None:
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|         if not self.cached:
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|             self._download(**model_kwargs)
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| 
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|     def load(self, **model_kwargs: Any) -> None:
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|         self.download(**model_kwargs)
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|         self._load(**model_kwargs)
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|         self._loaded = True
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| 
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|     def predict(self, inputs: Any) -> Any:
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|         if not self._loaded:
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|             self.load()
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|         return self._predict(inputs)
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| 
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|     @abstractmethod
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|     def _predict(self, inputs: Any) -> Any:
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|         ...
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| 
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|     @abstractmethod
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|     def _download(self, **model_kwargs: Any) -> None:
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|         ...
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| 
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|     @abstractmethod
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|     def _load(self, **model_kwargs: Any) -> None:
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|         ...
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| 
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|     @property
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|     def model_type(self) -> ModelType:
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|         return self._model_type
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| 
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|     @property
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|     def cache_dir(self) -> Path:
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|         return self._cache_dir
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| 
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|     @cache_dir.setter
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|     def cache_dir(self, cache_dir: Path) -> None:
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|         self._cache_dir = cache_dir
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| 
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|     @property
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|     def cached(self) -> bool:
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|         return self.cache_dir.exists() and any(self.cache_dir.iterdir())
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| 
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|     @classmethod
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|     def from_model_type(cls, model_type: ModelType, model_name: str, **model_kwargs: Any) -> InferenceModel:
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|         subclasses = {subclass._model_type: subclass for subclass in cls.__subclasses__()}
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|         if model_type not in subclasses:
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|             raise ValueError(f"Unsupported model type: {model_type}")
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| 
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|         return subclasses[model_type](model_name, **model_kwargs)
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| 
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|     def clear_cache(self) -> None:
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|         if not self.cache_dir.exists():
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|             return
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|         if not rmtree.avoids_symlink_attacks:
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|             raise RuntimeError("Attempted to clear cache, but rmtree is not safe on this platform.")
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| 
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|         if self.cache_dir.is_dir():
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|             rmtree(self.cache_dir)
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|         else:
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|             self.cache_dir.unlink()
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|         self.cache_dir.mkdir(parents=True, exist_ok=True)
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