code: def test_multiselect():
      action_space = MultiSelectActionSpace(4, 2, ["a", "b", "c", "d"])
      for i in range(100):
          action = action_space.sample()
          assert action.shape == (4,)
          assert np.sum(action) <= 2
  
      # check that descriptions of multiple actions are working
      description = action_space.get_description(np.array([1, 0, 1, 0]))
      assert description == "a + c"
  
      description = action_space.get_description(np.array([0, 0, 0, 0]))
      assert description == "no-op"
  
file_path: coach/rl_coach/tests/test_spaces.py
imports: import os
  import sys
  import pytest
  from rl_coach.spaces import DiscreteActionSpace, BoxActionSpace, MultiSelectActionSpace, ObservationSpace, AgentSelection, VectorObservationSpace, AttentionActionSpace
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: test_multiselect() without return types