class_docstr: A variable in the graph (e.g. learning_rate) can be a hyperparam.
docstr: Will setup the assign operator for that variable. 
docstr_tok: ["Will","setup","the","assign","operator","for","that","variable","."]
code: def setup_graph(self):
      """Will setup the assign operator for that variable."""
      all_vars = tfv1.global_variables() + tfv1.local_variables()
      for v in all_vars:
          if v.name == self.var_name:
              self.var = v
              break
      else:
          raise ValueError(
              "{} is not a variable in the graph!".format(self.var_name)
          )
  
imports: import operator
  import os
  import numpy
  from abc import ABCMeta, abstractmethod
  from collections import deque
  import six
  from ..compat import tfv1
  from ..tfutils.common import get_op_tensor_name
  from ..utils import logger
  from .base import Callback
label_desc: Use image node_id 2 for calling the GraphVarParam obj's underlying member method code with example usage: obj.setup_graph() without return types