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: Fixed, untunable value.
  
  Args:
      name: A string. the name of parameter. Must be unique for each
          `HyperParameter` instance in the search space.
      value: The value to use (can be any JSON-serializable Python type).
      parent_name: Optional string, specifying the name of the parent
          `HyperParameter` to use as the condition to activate the
          current `HyperParameter`.
      parent_values: Optional list of the values of the parent
          `HyperParameter` to use as the condition to activate the
          current `HyperParameter`.
  
  Returns:
      The value of the hyperparameter, or None if the hyperparameter is
      not active.
docstr_tok: ["Fixed",",","untunable","value",".","Args",":","name",":","A","string",".","the","name","of","parameter",".","Must","be","unique","for","each","`","HyperParameter","`","instance","in","the","search","space",".","value",":","The","value","to","use","(","can","be","any","JSON-serializable","Python","type",")",".","parent_name",":","Optional","string",",","specifying","the","name","of","the","parent","`","HyperParameter","`","to","use","as","the","condition","to","activate","the","current","`","HyperParameter","`",".","parent_values",":","Optional","list","of","the","values","of","the","parent","`","HyperParameter","`","to","use","as","the","condition","to","activate","the","current","`","HyperParameter","`",".","Returns",":","The","value","of","the","hyperparameter",",","or","None","if","the","hyperparameter","is","not","active","."]
code: def Fixed(self, name, value, parent_name=None, parent_values=None):
      """Fixed, untunable value.
  
      Args:
          name: A string. the name of parameter. Must be unique for each
              `HyperParameter` instance in the search space.
          value: The value to use (can be any JSON-serializable Python type).
          parent_name: Optional string, specifying the name of the parent
              `HyperParameter` to use as the condition to activate the
              current `HyperParameter`.
          parent_values: Optional list of the values of the parent
              `HyperParameter` to use as the condition to activate the
              current `HyperParameter`.
  
      Returns:
          The value of the hyperparameter, or None if the hyperparameter is
          not active.
      """
      with self._maybe_conditional_scope(parent_name, parent_values):
          hp = hp_types.Fixed(
              name=self._get_name(name),  # Add name_scopes.
              value=value,
              conditions=self._conditions,
          )
          return self._retrieve(hp)
  
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 16 for calling the HyperParameters obj's underlying member method code with example usage: obj.Fixed(name, value, parent_name, parent_values) and returns: self