input: Write a python function to train a logistic regression model using sklearn's LogisticRegression class.
  assert train_logistic_regression(np.array([[1,2],[2,3],[3,4]]), np.array([0,1,0])).coef_.shape == (1, 2)
  assert train_logistic_regression(np.array([[1,1],[2,2],[3,3]]), np.array([0,1,0])).intercept_.shape == (1,)
  assert isinstance(train_logistic_regression(np.array([[4,5],[5,6],[6,7]]), np.array([1,0,1])), LogisticRegression)
output: def train_logistic_regression(X, y):
      from sklearn.linear_model import LogisticRegression
      
      model = LogisticRegression()
      model.fit(X, y)
      
      return model