class_docstr: Base class for representing parameter ranges.
  
  This is used to define what hyperparameters to tune for an Amazon SageMaker
  hyperparameter tuning job and to verify hyperparameters for Marketplace Algorithms.
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docstr: Represent the parameter range as a dictionary.
  
  It is suitable for a request to create an Amazon SageMaker hyperparameter tuning job.
  
  Args:
      name (str): The name of the hyperparameter.
  
  Returns:
      dict[str, str]: A dictionary that contains the name and values of
      the hyperparameter.
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code: def as_tuning_range(self, name):
      """Represent the parameter range as a dictionary.
  
      It is suitable for a request to create an Amazon SageMaker hyperparameter tuning job.
  
      Args:
          name (str): The name of the hyperparameter.
  
      Returns:
          dict[str, str]: A dictionary that contains the name and values of
          the hyperparameter.
      """
      return {
          "Name": name,
          "MinValue": to_string(self.min_value),
          "MaxValue": to_string(self.max_value),
          "ScalingType": self.scaling_type,
      }
  
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 4 for calling the ParameterRange obj's underlying member method code with example usage: obj.as_tuning_range(name) and returns: dict