class_docstr: A class for representing hyperparameters that have a discrete list of possible values.
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docstr: Represent the parameter range as a dictionary.
  
  Dictionary is suitable for a request to create an Amazon SageMaker hyperparameter tuning job
  using one of the deep learning frameworks.
  
  The deep learning framework images require that hyperparameters be
  serialized as JSON.
  
  Args:
      name (str): The name of the hyperparameter.
  
  Returns:
      dict[str, list[str]]: A dictionary that contains the name and values of the
      hyperparameter, where the values are serialized as JSON.
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code: def as_json_range(self, name):
      """Represent the parameter range as a dictionary.
  
      Dictionary is suitable for a request to create an Amazon SageMaker hyperparameter tuning job
      using one of the deep learning frameworks.
  
      The deep learning framework images require that hyperparameters be
      serialized as JSON.
  
      Args:
          name (str): The name of the hyperparameter.
  
      Returns:
          dict[str, list[str]]: A dictionary that contains the name and values of the
          hyperparameter, where the values are serialized as JSON.
      """
      return {
          "Name": name,
          "Values": [json.dumps(v) for v in self.values],
      }
  
imports: from __future__ import absolute_import
  import json
  from typing import Union
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.utils import to_string
label_desc: Use image node_id 3 for calling the CategoricalParameter obj's underlying member method code with example usage: obj.as_json_range(name) and returns: dict