class_docstr: Restore a tensorflow checkpoint saved by :class:`tf.train.Saver` or :class:`ModelSaver`.
class_docstr_tok: ["Restore","a","tensorflow","checkpoint","saved","by",":","class",":","`","tf.train.Saver","`","or",":","class",":","`","ModelSaver","`","."]
docstr: return a set of strings 
docstr_tok: ["return","a","set","of","strings"]
code: def _read_checkpoint_vars(model_path):
      """return a set of strings"""
      reader = tf.train.NewCheckpointReader(model_path)
      reader = CheckpointReaderAdapter(
          reader
      )  # use an adapter to standardize the name
      ckpt_vars = reader.get_variable_to_shape_map().keys()
      return reader, set(ckpt_vars)
  
imports: import os
  import numpy
  import six
  from ..compat import tfv1
  from ..utils import logger
  from .common import get_op_tensor_name
  from .varmanip import SessionUpdate, get_checkpoint_path, get_savename_from_varname, is_training_name
label_desc: Use image node_id 4 for calling the SaverRestore obj's underlying member method code with example usage: obj._read_checkpoint_vars(model_path) and returns: reader,  set