class_docstr: Super class for all numerical type hyperparameters.
code: def values(self):
      if self.step is None:
          # Evenly select 10 samples as the values.
          return tuple(
              {self.prob_to_value(i * 0.1 + 0.05) for i in range(10)}
          )
      n_values = self._get_n_values()
      return (self._get_value_by_index(i) for i in range(n_values))
  
file_path: keras-tuner/keras_tuner/engine/hyperparameters/hp_types/numerical.py
imports: import math
  from keras_tuner.engine.hyperparameters import hp_utils
  from keras_tuner.engine.hyperparameters import hyperparameter
label_desc: Use image node_id 8 for calling the Numerical obj's underlying member method code with example usage: obj.values() and returns: unknown, tuple