code: def _n_shadows_compare_weights(
      model: torch.nn.Module,
      example_inputs: Any,
      qconfig_mapping: QConfigMapping,
      backend_config: BackendConfig,
  ) -> NSResultsType:
      """
      Note: this API is not recommended for wide usage, it is only
      provided for customers who need to migrate from the `add_loggers`
      API.
      """
      qconfig_multi_mapping = (
          QConfigMultiMapping.from_list_qconfig_mapping(
              [qconfig_mapping]
          )
      )
      mp = prepare_n_shadows_model(
          model, example_inputs, qconfig_multi_mapping, backend_config
      )
      # passing inputs through the model is necessary to populate
      # observers which observe weights with real values
      mp(*example_inputs)
      mq = convert_n_shadows_model(mp)
      weight_comparison = extract_weight_comparison(mq)
      return weight_comparison
  
imports: import collections
  import torch
  import torch.nn
  import torch.ao.quantization.quantize_fx
  from torch.fx import GraphModule
  from torch.fx.graph import Node
  from torch.ao.ns.fx.mappings import get_base_name_to_sets_of_related_ops
  from torch.ao.ns.fx.graph_matcher import get_matching_subgraph_pairs, get_type_a_related_to_b
  from .fx.weight_utils import extract_weight_from_node
  from .fx.graph_passes import add_loggers_to_model, create_a_shadows_b
  from .fx.utils import rekey_logger_info_on_node_name_of_model, maybe_add_missing_fqns, get_target_type_str
  from .fx.ns_types import NSSingleResultValuesType, NSResultsType, NSNodeTargetType
  from torch.ao.quantization.backend_config.utils import get_fusion_pattern_to_root_node_getter
  from torch.ao.quantization.backend_config import BackendConfig
  from torch.ao.quantization.fx.match_utils import _find_matches
  from torch.ao.quantization.fx.graph_module import _get_observed_graph_module_attr
  from torch.ao.quantization.fx.qconfig_mapping_utils import _generate_node_name_to_qconfig
  from torch.ao.quantization.fx.quantize_handler import _get_pattern_to_quantize_handlers
  from torch.ao.quantization.qconfig import QConfigAny
  from torch.ao.quantization import QConfigMapping
  from torch.ao.ns.fx.n_shadows_utils import OutputProp, _get_dedup_subgraphs, SHADOW_WRAPPER_NODE_NAME_PREFIX, group_results_by_subgraph, create_results_comparison, print_n_shadows_summary, create_n_transformed_and_logged_copies_of_subgraph, create_add_loggers_graph, extract_weight_comparison
  from torch.ao.ns.fx.qconfig_multi_mapping import QConfigMultiMapping
  from typing import Dict, Tuple, Callable, List, Optional, Set, Any, Type
label_desc: Use image node_id 15 for calling a global function with example usage: _n_shadows_compare_weights(model, example_inputs, qconfig_mapping, backend_config) and returns: weight_comparison