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.
code: def _validate_name(self, name):
      for condition in self._conditions:
          if condition.name == name:
              raise ValueError(
                  "A conditional `HyperParameter` cannot have the same "
                  "name as its parent. Found: " + str(name) + " and "
                  "parent_name: " + str(condition.name)
              )
  
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 27 for calling the HyperParameters obj's underlying member method code with example usage: obj._validate_name(name) without return types