126 lines
3.2 KiB
Python
126 lines
3.2 KiB
Python
import abc
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import gc
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from pathlib import Path
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from source.manager import ModelManager
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class BaseModel(abc.ABC):
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"""
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Represent a model.
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"""
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def __init__(self, manager: ModelManager, configuration: dict, path: Path):
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# the environment directory of the model
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self.path = path
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# the model manager
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self.manager = manager
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# the mimetype of the model responses
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self.response_mimetype: str = configuration.get("response_mimetype", "application/json")
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self._loaded = False
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def __repr__(self):
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return f"<{self.__class__.__name__}: {self.name}>"
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@property
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def name(self):
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"""
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Get the name of the model
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:return: the name of the model
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"""
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return self.path.name
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def get_information(self):
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"""
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Get information about the model
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:return: information about the model
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"""
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return {
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"name": self.name,
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"response_mimetype": self.response_mimetype,
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}
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def load(self) -> None:
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"""
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Load the model within the model manager
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"""
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# if we are already loaded, stop
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if self._loaded:
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return
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# check if we are the current loaded model
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if self.manager.current_loaded_model is not self:
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# unload the previous model
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if self.manager.current_loaded_model is not None:
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self.manager.current_loaded_model.unload()
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# model specific loading
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self._load()
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# declare ourselves as the currently loaded model
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self.manager.current_loaded_model = self
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# mark the model as loaded
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self._loaded = True
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@abc.abstractmethod
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def _load(self):
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"""
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Load the model
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Do not call manually, use `load` instead.
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"""
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def unload(self) -> None:
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"""
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Unload the model within the model manager
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"""
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# if we are not already loaded, stop
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if not self._loaded:
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return
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# if we were the currently loaded model of the manager, demote ourselves
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if self.manager.current_loaded_model is self:
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self.manager.current_loaded_model = None
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# model specific unloading part
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self._unload()
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# force the garbage collector to clean the memory
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gc.collect()
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# mark the model as unloaded
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self._loaded = False
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@abc.abstractmethod
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def _unload(self):
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"""
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Unload the model
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Do not call manually, use `unload` instead.
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:return:
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"""
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def infer(self, payload: dict) -> str | bytes:
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"""
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Infer our payload through the model within the model manager
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:param payload: the payload to give to the model
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:return: the response of the model
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"""
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# make sure we are loaded before an inference
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self.load()
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# model specific inference part
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return self._infer(payload)
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@abc.abstractmethod
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def _infer(self, payload: dict) -> str | bytes:
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"""
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Infer our payload through the model
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:param payload: the payload to give to the model
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:return: the response of the model
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"""
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