code: def test_hyperparameters_proto():
      hps = hp_module.HyperParameters()
      hps.Int("a", 1, 10, sampling="reverse_log", default=3)
      hps.Float("b", 2, 8, sampling="linear", default=4)
      hps.Choice("c", [1, 5, 10], ordered=False, default=5)
      hps.Fixed("d", "3")
      hps.Fixed("e", 3)
      hps.Fixed("f", 3.1)
      hps.Fixed("g", True)
      hps.Boolean("h")
      with hps.name_scope("d"):
          hps.Choice("e", [2.0, 4.5, 8.5], default=2.0)
          hps.Choice("f", ["1", "2"], default="1")
          with hps.conditional_scope("f", "1"):
              hps.Int("g", -10, 10, step=2, default=-2)
  
      new_hps = hp_module.HyperParameters.from_proto(hps.to_proto())
      assert _sort_space(hps) == _sort_space(new_hps)
      assert hps.values == new_hps.values
  
imports: import pytest
  from keras_tuner import protos
  from keras_tuner.backend import keras
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 16 for calling a global function with example usage: test_hyperparameters_proto() without return types