code: def _load_from_state_dict(
      self,
      state_dict,
      prefix,
      local_metadata,
      strict,
      missing_keys,
      unexpected_keys,
      error_msgs,
  ):
      version = local_metadata.get("version", None)
      if version is None or version < 2:
          self.dtype = torch.qint8
      else:
          self.dtype = state_dict[prefix + "dtype"]
          state_dict.pop(prefix + "dtype")
  
      if version is None or version < 3:
          self.set_weight_bias(
              state_dict[prefix + "weight"], state_dict[prefix + "bias"]
          )
          state_dict.pop(prefix + "weight")
          state_dict.pop(prefix + "bias")
  
      if version == 3:
          weight, bias = state_dict[prefix + "_packed_params"]
          state_dict.pop(prefix + "_packed_params")
          self.set_weight_bias(weight, bias)
  
      super()._load_from_state_dict(
          state_dict,
          prefix,
          local_metadata,
          False,
          missing_keys,
          unexpected_keys,
          error_msgs,
      )
  
imports: from collections.abc import Iterable
  import torch
  import torch.nn
  import torch.ao.nn.intrinsic
  import torch.ao.nn.intrinsic.qat
  from torch.nn.utils.fusion import fuse_linear_bn_weights
  from torch.nn.utils.parametrize import type_before_parametrizations
  from typing import Optional
  from .utils import _quantize_weight, _hide_packed_params_repr, WeightedQuantizedModule
label_desc: Use image node_id 6 for calling the LinearPackedParams 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