base.py 1.7 KB

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  1. # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. from abc import ABC, abstractmethod
  15. from typing import Any, Dict, Optional
  16. from ...utils.subclass_register import AutoRegisterABCMetaClass
  17. from ..models import create_predictor
  18. class BasePipeline(ABC, metaclass=AutoRegisterABCMetaClass):
  19. """Base Pipeline"""
  20. __is_base = True
  21. def __init__(self, predictor_kwargs) -> None:
  22. super().__init__()
  23. self._predictor_kwargs = {} if predictor_kwargs is None else predictor_kwargs
  24. @abstractmethod
  25. def set_predictor():
  26. raise NotImplementedError(
  27. "The method `set_predictor` has not been implemented yet."
  28. )
  29. # alias the __call__() to predict()
  30. def __call__(self, *args, **kwargs):
  31. yield from self.predict(*args, **kwargs)
  32. def _create(self, model=None, pipeline=None, *args, **kwargs):
  33. if model:
  34. return create_predictor(
  35. model=model, *args, **kwargs, **self._predictor_kwargs
  36. )
  37. elif pipeline:
  38. return pipeline(*args, **kwargs, predictor_kwargs=self._predictor_kwargs)
  39. else:
  40. raise Exception()