code: def test_sparse_randint_execution(setup):
      # size_executor = ExecutorForTest(sync_provider_type=ExecutorForTest.SyncProviderType.MOCK)
  
      arr = tensor.random.randint(
          1, 2, size=(30, 50), density=0.1, chunk_size=20, dtype="f4"
      )
      # size_res = size_executor.execute_tensor(arr, mock=True)
      # assert pytest.approx(arr.nbytes * 0.1) == sum(tp[0] for tp in size_res)
  
      res = arr.execute().fetch()
      assert issparse(res) is True
      assert res.shape == (30, 50)
      np.testing.assert_array_less(res.data, 2)
      np.testing.assert_array_less(0, res.data)
      assert (res >= 1).toarray().sum() == pytest.approx(
          30 * 50 * 0.1, abs=20
      )
  
file_path: mars/mars/tensor/random/tests/test_random_execution.py
imports: from collections import namedtuple
  import numpy
  import pytest
  from ....None import tensor
  from ....core import tile
  from ....lib.sparse.core import issparse
  from ...datasource import tensor
label_desc: Use image node_id 5 for calling a global function with example usage: test_sparse_randint_execution(setup) without return types