code: def test_dedup_finite():
      space = format_search_space(finite_space)
      dedup = Deduplicator(space)
      params = []
      exhausted = False
      try:
          for i in range(7):
              p = dedup(suggest(rng, space))
              params.append(deformat_parameters(p, space))
      except nni.NoMoreTrialError:
          exhausted = True
      params = sorted(params, key=(lambda p: (p["x"], p["y"], p["z"])))
      assert exhausted
      assert params == [
          {"x": "a", "y": 0.0, "z": 1.0},
          {"x": "a", "y": 0.6, "z": 1.0},
          {"x": "a", "y": 1.0, "z": 1.0},
          {"x": "b", "y": 0.0, "z": 1.0},
          {"x": "b", "y": 0.6, "z": 1.0},
          {"x": "b", "y": 1.0, "z": 1.0},
      ]
  
imports: import numpy
  import nni
  from nni.algorithms.hpo.random_tuner import suggest
  from nni.common.hpo_utils import Deduplicator, deformat_parameters, format_search_space
label_desc: Use image node_id 1 for calling a global function with example usage: test_dedup_finite() without return types