input: Write a python function to split datasets into training and test sets using train_test_split.
  assert len(train_test_split([1, 2, 3, 4, 5], [0, 1, 0, 1, 0], test_size=0.2)) == 4
  assert all(isinstance(x, np.ndarray) for x in train_test_split(np.array([1, 2, 3]), np.array([0, 1, 0]), test_size=0.5))
output: from sklearn.model_selection import train_test_split
  import numpy as np
  
  def split_datasets(X, y, test_size=0.2, random_state=None):
      return train_test_split(X, y, test_size=test_size, random_state=random_state)