code: def test_float_proto():
      hp = hp_module.Float("a", -10, 10, sampling="linear", default=3)
      proto = hp.to_proto()
      assert proto.name == "a"
      assert proto.min_value == -10.0
      assert proto.max_value == 10.0
      assert proto.sampling == protos.get_proto().Sampling.LINEAR
      assert proto.default == 3.0
      # Zero is the default, gets converted to `None` in `from_proto`.
      assert proto.step == 0.0
  
      new_hp = hp_module.Float.from_proto(proto)
      assert new_hp.get_config() == hp.get_config()
  
file_path: keras-tuner/keras_tuner/engine/hyperparameters/hp_types/float_hp_test.py
imports: import numpy
  from keras_tuner import protos
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 9 for calling a global function with example usage: test_float_proto() without return types