code: def _load_packed_weight(
      self,
      state_dict,
      prefix,
      local_metadata,
      strict,
      missing_keys,
      unexpected_keys,
      error_msgs,
  ):
      attrs_to_pop = []
      for attr_name in state_dict:
          if attr_name.startswith("_packed_weight") and isinstance(state_dict[attr_name], torch._C.ScriptObject):  # type: ignore[attr-defined] # noqa: B950
              setattr(self, attr_name, state_dict[attr_name])
              attrs_to_pop.append(attr_name)
  
      # pop the packed param attributesn
      for attr_name in attrs_to_pop:
          state_dict.pop(attr_name)
  
imports: import torch
  from torch.fx import map_arg, Node
  from torch.fx.graph import Graph
  import torch.nn
  import torch.nn.functional
  import torch.ao.nn.intrinsic
  import torch.ao.nn.intrinsic.quantized
  import torch.ao.nn.intrinsic.quantized.dynamic
  import torch.ao.nn.quantized
  import torch.ao.nn.quantized.dynamic
  import torch.ao.nn.quantized.reference
  from torch.ao.nn.quantized.modules.utils import WeightedQuantizedModule
  from torch.fx import GraphModule
  from .utils import collect_producer_nodes, get_linear_prepack_op_for_dtype, get_new_attr_name_with_prefix, get_qconv_prepack_op, graph_module_from_producer_nodes
  from ..utils import _parent_name
  from ..qconfig import QConfigAny
  from ..quantization_mappings import get_quantized_operator
  from .utils import create_node_from_old_node_preserve_meta
  from typing import Dict, Tuple, Type, List, Callable, Any, Union, Set, Optional
  import operator
label_desc: Use image node_id 13 for calling a global function with example usage: _load_packed_weight(state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) without return types