code: def _operator_to_node_simp(op, inter_blobs, seen):
      """
      Convert the operators to nodes.
  
      Args:
          op: Caffe2 operator to convert to node
          inter_blobs: Set of intermediate blobs
          seen: Names that have already been used and are not unique
  
      Returns:
          nodes: Nodes representing 'op' and the outputs of 'op'
      """
      assert op
      nodes = []
      outputs = [o for o in op.output if o not in inter_blobs]
      seen.update(outputs)
      len_outputs = len(outputs)
      if len_outputs == 1:
          n = NodeDef()
          n.name = outputs[0]
          # Here we are sure the name is unique.
          n.input.extend(op.input)
          n.op = op.type
          n.device = _tf_device(op.device_option)
          for arg in op.arg:
              _set_tf_attr(n.attr, arg)
          nodes.append(n)
      elif len_outputs > 1:
          # Create a name that is likely unique
          if op.name:
              name = op.name
          else:
              name_list = list(outputs)
              scope = os.path.commonprefix(name_list)
              name = os.path.join(scope, op.type)
          assert name
          op.name = _make_unique_name(seen, name)
          device = _tf_device(op.device_option)
  
          # Create additional output nodes
          for output in outputs:
              n = NodeDef()
              n.name = output
              n.input.extend([op.name])
              n.op = "Blob"
              n.device = device
              nodes.append(n)
  
          # Node for the current op
          n = NodeDef()
          n.name = op.name
          n.input.extend(op.input)
          n.op = op.type
          n.device = device
          for arg in op.arg:
              _set_tf_attr(n.attr, arg)
          nodes.append(n)
  
      return nodes
  
imports: import copy
  import logging
  import os
  import re
  from tensorboard.compat.proto.graph_pb2 import GraphDef
  from tensorboard.compat.proto.node_def_pb2 import NodeDef
  from tensorboard.compat.proto.tensor_shape_pb2 import TensorShapeProto
  from caffe2.proto import caffe2_pb2
  from caffe2.python import core, workspace
  from typing import Set, Dict, Tuple, List
label_desc: Use image node_id 14 for calling a global function with example usage: _operator_to_node_simp(op, inter_blobs, seen) and returns: nodes