forked from JointCloud/JCC-DeepOD
46 lines
992 B
ReStructuredText
46 lines
992 B
ReStructuredText
Model Save & Load
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==================
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The detection model class has ``save_model`` and ``load_model`` functions.
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We take the `DeepSVDD` model for example.
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.. code-block:: python
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from deepod.models import DeepSVDD
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# training an anomaly detection model
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model = DeepSVDD() # or any other models in DeepOD
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model.fit(X_train) # training
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path = 'save_file.pkl'
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model.save_model(path) # save trained model at the assigned path
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# directly load trained model from path
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model = DeepSVDD.load_model(path)
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model.decision_function(X_test)
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# or
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model.predict(X_test)
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You can also directly use pickle for saving and loading DeepOD models.
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.. code-block:: python
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import pickle
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from deepod.models import DeepSVDD
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model = DeepSVDD()
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model.fit(X_train)
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with open('save_file.pkl', 'wb'):
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pickle.dump(model)
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with open('save_file.pkl', 'rb')
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model = pickle.load(f)
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model.decision_function(X_test)
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