code: def _remove_output_observer(
      node: Node,
      model: torch.nn.Module,
      named_modules: Dict[str, torch.nn.Module],
  ):
      items = list(node.users.items())
      for output_obs_node, _ in items:
          assert _is_activation_post_process_node(
              output_obs_node, named_modules
          )
          output_obs_node.replace_all_uses_with(node)
          model.graph.erase_node(output_obs_node)
  
imports: import copy
  import torch
  import warnings
  from torch.fx import GraphModule
  from torch.fx.graph import Graph, Node
  from torch.fx.node import Argument
  from ..quantize import propagate_qconfig_
  from ..observer import _is_activation_post_process, _PartialWrapper
  from ..qconfig import _is_reuse_input_qconfig, QConfigAny
  from ..qconfig_mapping import QConfigMapping
  from .qconfig_mapping_utils import _generate_node_name_to_qconfig, _update_qconfig_for_fusion, _get_flattened_qconfig_dict, _update_qconfig_for_qat
  from .quantize_handler import _default_root_node_getter, _get_pattern_to_quantize_handlers, QuantizeHandler
  from torch.ao.quantization import ObserverBase, FixedQParamsObserver, FixedQParamsFakeQuantize, _DerivedObserverOrFakeQuantize
  from torch.ao.quantization.utils import Pattern, NodePattern
  from ._equalize import is_equalization_observer, node_supports_equalization
  from .pattern_utils import _sorted_patterns_dict
  from .match_utils import _MatchResultWithQConfig, _find_matches
  from .utils import _insert_dequant_stubs_for_custom_module_lstm_output, _is_custom_module_lstm, _maybe_get_custom_module_lstm_from_node_arg, _qconfig_satisfies_dtype_config_constraints, get_custom_module_class_keys, all_node_args_have_no_tensors, assert_and_get_unique_device, get_non_observable_arg_indexes_and_types, get_new_attr_name_with_prefix, node_arg_is_weight, node_arg_is_bias, NON_QUANTIZABLE_WEIGHT_OPS, ObservedGraphModuleAttrs
  from torch.ao.quantization import PlaceholderObserver
  from torch.ao.quantization.quantize import convert
  from ..utils import _parent_name, get_qconfig_dtypes, get_swapped_custom_module_class
  from ..backend_config.utils import get_pattern_to_dtype_configs, get_module_to_qat_module, get_fusion_pattern_to_root_node_getter
  from ..backend_config import BackendConfig, DTypeConfig, get_native_backend_config
  from .custom_config import PrepareCustomConfig, StandaloneModuleConfigEntry
  from torch.ao.quantization.quantizer import EdgeOrNode, QuantizationSpec, QuantizationSpecBase, FixedQParamsQuantizationSpec, SharedQuantizationSpec, DerivedQuantizationSpec
  from torch.ao.quantization import ObserverOrFakeQuantize
  from torch._subclasses import FakeTensor
  from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union
  from dataclasses import asdict
label_desc: Use image node_id 28 for calling a global function with example usage: _remove_output_observer(node, model, named_modules) without return types