class_docstr: Fetch results about a hyperparameter tuning job and make them accessible for analytics.
docstr: Convert parameter ranges a dictionary using the parameter range names as the keys
docstr_tok: ["Convert","parameter","ranges","a","dictionary","using","the","parameter","range","names","as","the","keys"]
code: def _prepare_parameter_ranges(self, parameter_ranges):
      """Convert parameter ranges a dictionary using the parameter range names as the keys"""
      out = {}
      for _, ranges in parameter_ranges.items():
          for param in ranges:
              out[param["Name"]] = param
      return out
  
imports: from __future__ import print_function, absolute_import
  from abc import ABCMeta, abstractmethod
  from collections import defaultdict, OrderedDict
  import datetime
  import logging
  from six import with_metaclass
  from sagemaker.session import Session
  from sagemaker.utils import DeferredError
  from sagemaker.lineage import artifact
label_desc: Use image node_id 7 for calling the HyperparameterTuningJobAnalytics obj's underlying member method code with example usage: obj._prepare_parameter_ranges(parameter_ranges) and returns: out