code: def test_train_test_split():
      seed = np.random.randint(1000)
      mat = _get_sample_matrix()
      train, _ = train_test_split(mat, 0.8, seed)
      train2, _ = train_test_split(mat, 0.8, seed)
      assert np.all(train.todense() == train2.todense())
  
file_path: implicit/tests/evaluation_test.py
imports: import numpy
  import pytest
  from scipy.sparse import csr_matrix, random
  import implicit
  from implicit.evaluation import leave_k_out_split, precision_at_k, train_test_split
  from implicit.datasets.movielens import get_movielens
label_desc: Use image node_id 3 for calling a global function with example usage: test_train_test_split() without return types