input: Write a python function to create a univariate linear regression model and fit it to the given data using sklearn.
  assert isinstance(linreg_univariate_model(np.array([1, 2, 3]), np.array([1, 2, 3])), LinearRegression)
  assert np.isclose(linreg_univariate_model(np.array([1, 2, 3]), np.array([1, 2, 3])).coef_[0], 1.0)
  assert np.isclose(linreg_univariate_model(np.array([1, 2, 3]), np.array([2, 4, 6])).coef_[0], 2.0)
output: def linreg_univariate_model(X, y):
      from sklearn.linear_model import LinearRegression
      X = X.reshape(-1, 1)
      model = LinearRegression()
      model.fit(X, y)
      return model