code: def _maybe_insert_output_observer_for_node(
      node: Node,
      model: torch.nn.Module,
      named_modules: Dict[str, torch.nn.Module],
      graph: Graph,
      obs_or_fq_map: Dict[EdgeOrNode, ObserverOrFakeQuantize],
      is_qat: bool,
  ) -> Optional[Node]:
      if node in obs_or_fq_map:
          output_act_obs_or_fq = obs_or_fq_map[node]
          return _insert_obs_or_fq(
              node, output_act_obs_or_fq, model, named_modules, graph
          )
      return None
  
imports: import torch
  from torch._subclasses import FakeTensor
  from torch.ao.quantization.fx.prepare import _insert_obs_or_fq, _save_state, _is_activation_post_process_node, _create_obs_or_fq_from_qspec
  from torch.fx import GraphModule, Graph, Node
  from torch.fx.node import Argument
  from torch.ao.quantization import QConfigMapping
  from torch.ao.quantization.qconfig import QConfigAny
  from torch.ao.quantization.fx.custom_config import PrepareCustomConfig
  from typing import Dict, Tuple, Union, Any, Optional
  from torch.ao.quantization.quantizer import EdgeOrNode, SharedQuantizationSpec, QuantizationSpecBase
  from torch.ao.quantization import ObserverOrFakeQuantize
label_desc: Use image node_id 13 for calling a global function with example usage: _maybe_insert_output_observer_for_node(node, model, named_modules, graph, obs_or_fq_map, is_qat) and returns: None, _insert_obs_or_fq