mirror of
https://github.com/immich-app/immich.git
synced 2025-11-04 04:12:36 +09:00
c73832bd9c
* download facial recognition models * download hf models * simplified logic * updated `predict` for facial recognition * ensure download method is called * fixed repo_id for clip * fixed download destination * use st's own `snapshot_download` * conditional download * fixed predict method * check if loaded * minor fixes * updated mypy overrides * added pytest-mock * updated tests * updated lock
91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
from __future__ import annotations
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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 onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf # type: ignore
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from ..config import get_cache_dir
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from ..schemas import ModelType
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class InferenceModel(ABC):
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_model_type: ModelType
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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):
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self.clear_cache()
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loader(**model_kwargs)
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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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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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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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@abstractmethod
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def _predict(self, inputs: Any) -> Any:
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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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@abstractmethod
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def _load(self, **model_kwargs: Any) -> None:
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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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@property
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def cache_dir(self) -> Path:
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return self._cache_dir
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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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@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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@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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return subclasses[model_type](model_name, **model_kwargs)
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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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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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