code: def to_dict(self):
      model_dict = {
          "feature_num": self.models[0].in_features,
          "label_num": len(self.models),
          # convert tensor to list
          "state_dict": {
              k: v.tolist() for k, v in self.state_dict().items()
          },
      }
      return model_dict
  
imports: import torch.nn
  from fate.arch.dataframe import DataFrame
  from fate.ml.abc.module import HomoModule
  from fate.ml.utils.model_io import ModelIO
  from fate.arch import Context
  import logging
  import torch
  from fate.ml.nn.homo.fedavg import FedAVGClient, TrainingArguments, FedAVGArguments
  from transformers import default_data_collator
  import functools
  import tempfile
  from fate.ml.utils.predict_tools import array_to_predict_df
  from fate.ml.utils.predict_tools import MULTI, BINARY
  from fate.ml.nn.dataset.table import TableDataset
  from fate.ml.utils._optimizer import optimizer_factory, lr_scheduler_factory
label_desc: Use image node_id 3 for calling the HomoLRModel obj's underlying member method code with example usage: obj.to_dict() and returns: model_dict