code: def test_attention():
      low = np.array([-1, -2, -3, -4])
      high = np.array([1, 2, 3, 4])
      action_space = AttentionActionSpace(4, low=low, high=high)
      for i in range(100):
          action = action_space.sample()
          assert len(action) == 2
          assert action[0].shape == (4,)
          assert action[1].shape == (4,)
          assert np.all(action[0] <= action[1])
          assert np.all(action[0] >= low)
          assert np.all(action[1] < high)
  
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 4 for calling a global function with example usage: test_attention() without return types