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- class DeePredict:
- def __init__(self, model=None, bridge=None):
- if model:
- self._model = model
- if bridge:
- self._bridge = bridge
- def model(self, *args, **kwargs):
- if self.__getattribute__('_model'):
- return self._model(*args, **kwargs)
- else:
- raise ValueError('缺少模型')
- def bridge(self, *args, **kwargs):
- return self._bridge(*args, **kwargs)
- def predict(self, *args, **kwargs):
- x = self.model(*args, **kwargs)
- if self.__getattribute__('_bridge'):
- y = self.bridge(x)
- return y
- else:
- return x
- if __name__ == '__main__':
- def f1(x):
- return x
- dp = DeePredict(f1, f1)
- print(dp.predict([1]))
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