code: def _increment_global_step(increment, graph=None):
      graph = graph or ops.get_default_graph()
      global_step_tensor = get_global_step(graph)
      if global_step_tensor is None:
          raise ValueError(
              "Global step tensor should be created by "
              "tf.train.get_or_create_global_step before calling increment."
          )
      global_step_read_tensor = _get_or_create_global_step_read(graph)
      with graph.as_default() as g, g.name_scope(None):
          with g.name_scope(global_step_tensor.op.name + "/"):
              with ops.control_dependencies([global_step_read_tensor]):
                  return state_ops.assign_add(
                      global_step_tensor, increment
                  )
  
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import graph_io
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 8 for calling a global function with example usage: _increment_global_step(increment, graph) and returns: state_ops