input: Write a python function to train a linear regression model using sklearn and return its coefficients and intercept.
  assert train_linear_regression(np.array([[2.0, 5.0]]), np.array([7.5])) == (np.array([0., 0.]), 7.5)
  assert train_linear_regression(np.array([[1.0, 2.0], [2.0, 3.0]]), np.array([1.0, 1.5])) == (np.array([0.5, 0.]), 0.0)
  assert train_linear_regression(np.array([[1.0, 1.0], [2.0, 2.0], [3.0, 3.0]]), np.array([2.0, 4.0, 6.0])) == (np.array([1., 1.]), 0.0)
output: from sklearn.linear_model import LinearRegression
  import numpy as np
  
  def train_linear_regression(X, y):
      model = LinearRegression()
      model.fit(X, y)
      return (model.coef_, model.intercept_)