class_docstr: This class is created to make sure PackedParams
  (e.g. LinearPackedParams, Conv2dPackedParams) to appear in state_dict
  so that we can serialize and deserialize quantized graph module with
  torch.save(m.state_dict()) and m.load_state_dict(state_dict)
class_docstr_tok: ["This","class","is","created","to","make","sure","PackedParams","(","e.g",".","LinearPackedParams",",","Conv2dPackedParams",")","to","appear","in","state_dict","so","that","we","can","serialize","and","deserialize","quantized","graph","module","with","torch.save","(","m.state_dict","(",")",")","and","m.load_state_dict","(","state_dict",")"]
code: def _load_from_state_dict(
      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)
  
      super()._load_from_state_dict(
          state_dict,
          prefix,
          local_metadata,
          strict,
          missing_keys,
          unexpected_keys,
          error_msgs,
      )
  
imports: import torch
  import copy
  from torch.fx import GraphModule
  from torch.fx.graph import Graph
  from typing import Union, Dict, Any, Set
label_desc: Use image node_id 2 for calling the QuantizedGraphModule obj's underlying member method code with example usage: obj._load_from_state_dict(state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) without return types