class_docstr: A class for representing hyperparameters that have a discrete list of possible values.
class_docstr_tok: ["A","class","for","representing","hyperparameters","that","have","a","discrete","list","of","possible","values","."]
docstr: Initialize a ``CategoricalParameter``.
  
  Args:
      values (list or object): The possible values for the hyperparameter.
          This input will be converted into a list of strings.
docstr_tok: ["Initialize","a","``","CategoricalParameter","``",".","Args",":","values","(","list","or","object",")",":","The","possible","values","for","the","hyperparameter",".","This","input","will","be","converted","into","a","list","of","strings","."]
code: def __init__(self, values):  # pylint: disable=super-init-not-called
      """Initialize a ``CategoricalParameter``.
  
      Args:
          values (list or object): The possible values for the hyperparameter.
              This input will be converted into a list of strings.
      """
      values = values if isinstance(values, list) else [values]
      self.values = [to_string(v) for v in 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 1 to create a new CategoricalParameter object from inherited base classes: ParameterRange with example: obj = CategoricalParameter(values)