class_docstr: Python memory leak detection class.
class_docstr_tok: ["Python","memory","leak","detection","class","."]
code: def _get_internal_object_ids(self):
      ids = set()
      for snapshot in self._snapshots:
          ids.add(id(snapshot))
          for v in snapshot.values():
              ids.add(id(v))
      return ids
  
file_path: tensorflow-upstream/tensorflow/python/framework/python_memory_checker.py
imports: import collections
  import copy
  import gc
  from tensorflow.python.framework import _python_memory_checker_helper
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.profiler import trace
label_desc: Use image node_id 7 for calling the _PythonMemoryChecker obj's underlying member method code with example usage: obj._get_internal_object_ids() and returns: ids