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: Merges hyperparameters into this object.
  
  Args:
      hps: A `HyperParameters` object or list of `HyperParameter`
          objects.
      overwrite: Boolean, whether existing `HyperParameter`s should be
          overridden by those in `hps` with the same name and conditions.
docstr_tok: ["Merges","hyperparameters","into","this","object",".","Args",":","hps",":","A","`","HyperParameters","`","object","or","list","of","`","HyperParameter","`","objects",".","overwrite",":","Boolean",",","whether","existing","`","HyperParameter","`","s","should","be","overridden","by","those","in","`","hps","`","with","the","same","name","and","conditions","."]
code: def merge(self, hps, overwrite=True):
      """Merges hyperparameters into this object.
  
      Args:
          hps: A `HyperParameters` object or list of `HyperParameter`
              objects.
          overwrite: Boolean, whether existing `HyperParameter`s should be
              overridden by those in `hps` with the same name and conditions.
      """
      if isinstance(hps, HyperParameters):
          hps = hps.space
  
      if not overwrite:
          hps = [
              hp
              for hp in hps
              if not self._exists(hp.name, hp.conditions)
          ]
  
      for hp in hps:
          self._register(hp, overwrite)
  
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 21 for calling the HyperParameters obj's underlying member method code with example usage: obj.merge(hps, overwrite) without return types