class_docstr: Tools for reconstructing a model from a remote LoRA model.
  (Transferring only LoRA data costs much less!)
  Usage:
      Step 1 (Sender):
          filter_state_dict_lora()
  
      Step 2 (Sender, Optional):
          extract_lora_config()
  
      Step 3 (Sender):
          send state_dict_lora and lora_config_dict
  
      Step 4 (Receiver):
          reconstruct_increase()
  
      Step 5 (Receiver):
          load_state_dict_increase()
docstr: The final reconstruction step
docstr_tok: ["The","final","reconstruction","step"]
code: def load_state_dict_increase(
      self, model: nn.Module, state_dict_increase: Dict[str, Any]
  ):
      """
      The final reconstruction step
      """
      # naive approach
      model.load_state_dict(
          {
              k: v + model.state_dict()[k]
              for k, v in state_dict_increase.items()
          },
          strict=False,
      )
  
file_path: colossalai/applications/Chat/coati/ray/lora_constructor.py
imports: from collections import OrderedDict
  from dataclasses import dataclass
  from typing import Any, Dict
  import torch.nn
  from coati.models.lora import LoraLinear
label_desc: Use image node_id 5 for calling the LoRAConstructor obj's underlying member method code with example usage: obj.load_state_dict_increase(model, state_dict_increase) without return types