class_docstr: Same as :class:`SaverRestore`, but has more relaxed constraints.
  
  It allows upcasting certain variables, or reshape certain
  variables when there is a mismatch that can be fixed.
  
  When variable shape and value shape do not match, it will print a
  warning but will not crash.
  
  Another advantage is that it doesn't add any new ops to the graph.
class_docstr_tok: ["Same","as",":","class",":","`","SaverRestore","`",",","but","has","more","relaxed","constraints",".","It","allows","upcasting","certain","variables",",","or","reshape","certain","variables","when","there","is","a","mismatch","that","can","be","fixed",".","When","variable","shape","and","value","shape","do","not","match",",","it","will","print","a","warning","but","will","not","crash",".","Another","advantage","is","that","it","does","n't","add","any","new","ops","to","the","graph","."]
code: def _setup_graph(self):
      # no need to setup saver like the parent class
      pass
  
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 1 for calling the SaverRestoreRelaxed obj's underlying member method code with example usage: obj._setup_graph() without return types