input: Write a python function to train a RandomForestClassifier and return the trained model.
  assert isinstance(train_random_forest(np.array([[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6]]), np.array([1, 1, 2, 2])), RandomForestClassifier)
  assert train_random_forest(np.array([[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6]]), np.array([1, 1, 2, 2])).predict([[1, 2, 3]])[0] == 1
  assert train_random_forest(np.array([[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6]]), np.array([1, 1, 2, 2])).predict([[4, 5, 6]])[0] == 2
output: def train_random_forest(X, y):
      from sklearn.ensemble import RandomForestClassifier
  
      model = RandomForestClassifier()
      model.fit(X, y)
      
      return model