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- import os
- import pickle
-
- import numpy as np
-
- from learnware.model import BaseModel
-
-
- class Model(BaseModel):
- def __init__(self):
- super(Model, self).__init__(input_shape=(1,), output_shape=(1,))
- dir_path = os.path.dirname(os.path.abspath(__file__))
-
- modelv_path = os.path.join(dir_path, "modelv.pth")
- with open(modelv_path, "rb") as f:
- self.modelv = pickle.load(f)
-
- modell_path = os.path.join(dir_path, "modell.pth")
- with open(modell_path, "rb") as f:
- self.modell = pickle.load(f)
-
- def fit(self, X: np.ndarray, y: np.ndarray):
- pass
-
- def predict(self, X: np.ndarray) -> np.ndarray:
- return self.modell.predict(self.modelv.transform(X))
-
- def finetune(self, X: np.ndarray, y: np.ndarray):
- pass
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