docstr: Load tensors from a checkpoint
  :param restore_path: full path to load checkpoint from.
docstr_tok: ["Load","tensors","from","a","checkpoint",":","param","restore_path",":","full","path","to","load","checkpoint","from","."]
code: def _read_tensors(self, restore_path: str):
      """
      Load tensors from a checkpoint
      :param restore_path: full path to load checkpoint from.
      """
      # We don't use saver.restore() because checkpoint is loaded to online
      # network, but if the checkpoint is from the global network, a namespace
      # mismatch exists and variable name must be modified before loading.
      reader = tf.contrib.framework.load_checkpoint(restore_path)
      for var_name, _ in reader.get_variable_to_shape_map().items():
          yield var_name, reader.get_tensor(var_name)
  
file_path: coach/rl_coach/architectures/tensorflow_components/savers.py
imports: import pickle
  from typing import Any, List, Dict
  import tensorflow
  import numpy
  from rl_coach.saver import Saver
label_desc: Use image node_id 8 for calling the GlobalVariableSaver obj's underlying member method code with example usage: obj._read_tensors(restore_path) without return types