class_docstr: Fetch training curve data from CloudWatch Metrics for a specific training job.
docstr: Clear the object of all local caches of API methods.
  
  This is so that the next time any properties are accessed they will be
  refreshed from the service.
docstr_tok: ["Clear","the","object","of","all","local","caches","of","API","methods",".","This","is","so","that","the","next","time","any","properties","are","accessed","they","will","be","refreshed","from","the","service","."]
code: def clear_cache(self):
      """Clear the object of all local caches of API methods.
  
      This is so that the next time any properties are accessed they will be
      refreshed from the service.
      """
      super(TrainingJobAnalytics, self).clear_cache()
      self._data = defaultdict(list)
      self._time_interval = self._determine_timeinterval()
  
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 4 for calling the TrainingJobAnalytics obj's underlying member method code with example usage: obj.clear_cache() without return types