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import numpy as np
from sklearn.linear_model import LogisticRegression

import submarine

if __name__ == "__main__":
    X = np.array([-2, -1, 0, 1, 2, 1]).reshape(-1, 1)
    y = np.array([0, 0, 1, 1, 1, 0])
    lr = LogisticRegression(solver="liblinear", max_iter=100)
    submarine.log_param("max_iter", 100)
    lr.fit(X, y)
    score = lr.score(X, y)
    print(f"Score: {score}")
    submarine.log_metric("score", score)
