class_docstr: It maintains the global step in the graph, making sure it's increased by one at every `hooked_sess.run`.
  This callback is used internally by the trainer, you don't need to worry about it.
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code: def _setup_graph(self):
      # ensure it exists
      gs_var = get_global_step_var()
      with tf.name_scope(None):
          self.gs_incr_op = tf.assign_add(
              gs_var, 1, name=GLOBAL_STEP_INCR_OP_NAME
          ).op
      self._fetches = tf.train.SessionRunArgs(self.gs_incr_op)
  
imports: import tqdm
  from six.moves import zip
  from ..compat import tfv1
  from ..tfutils.common import get_global_step_var, get_op_tensor_name
  from ..utils import logger
  from ..utils.naming import GLOBAL_STEP_INCR_OP_NAME
  from ..utils.utils import get_tqdm_kwargs
  from .base import Callback
label_desc: Use image node_id 1 for calling the MaintainStepCounter obj's underlying member method code with example usage: obj._setup_graph() without return types