class_docstr: Container for both a hyperparameter space, and current values.
  
  A `HyperParameters` instance can be pass to `HyperModel.build(hp)` as an
  argument to build a model.
  
  To prevent the users from depending on inactive hyperparameter values, only
  active hyperparameters should have values in `HyperParameters.values`.
  
  Attributes:
      space: A list of `HyperParameter` objects.
      values: A dict mapping hyperparameter names to current values.
docstr: Return the current value of this hyperparameter set.
docstr_tok: ["Return","the","current","value","of","this","hyperparameter","set","."]
code: def get(self, name):
      """Return the current value of this hyperparameter set."""
      name = self._get_name(name)  # Add name_scopes.
      if name in self.values:
          return self.values[name]  # Only active values are added here.
      elif name in self._hps:
          raise ValueError(f"{name} is currently inactive.")
      else:
          raise KeyError(f"{name} does not exist.")
  
imports: import collections
  import contextlib
  import copy
  import six
  from keras_tuner import protos
  from keras_tuner.api_export import keras_tuner_export
  from keras_tuner.engine import conditions
  from keras_tuner.engine.hyperparameters import hp_types
  from keras_tuner.engine.hyperparameters import hyperparameter
label_desc: Use image node_id 9 for calling the HyperParameters obj's underlying member method code with example usage: obj.get(name) and returns: self