62 lines
1.4 KiB
Python
62 lines
1.4 KiB
Python
import joblib
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from keras import models
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def save_sklearn_model(model, filename):
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"""
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Saves a Scikit-learn model to disk.
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Example of usage:
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>>> reg = sklearn.linear_models.LinearRegression()
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>>> reg.fit(x_train, y_train)
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>>> save_sklearn_model(reg, 'my_model.pickle')
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:param model: the model to save;
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:param filename: string, path to the file in which to store the model.
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:return: the model.
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"""
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joblib.dump(model, filename)
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def load_sklearn_model(filename):
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"""
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Loads a Scikit-learn model saved with joblib.dump.
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:param filename: string, path to the file storing the model.
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:return: the model.
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"""
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model = joblib.load(filename)
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return model
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def save_keras_model(model, filename):
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"""
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Saves a Keras model to disk.
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Example of usage:
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>>> model = Sequential()
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>>> model.add(Dense(...))
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>>> model.compile(...)
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>>> model.fit(...)
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>>> save_keras_model(model, 'my_model')
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:param model: the model to save;
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:param filename: string, path to the file in which to store the model.
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:return: the model.
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"""
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models.save_model(model, filename)
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def load_keras_model(filename):
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"""
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Loads a compiled Keras model saved with models.save_model.
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:param filename: string, path to the file storing the model.
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:return: the model.
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"""
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model = models.load_model(filename)
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return model
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