code: def config(self):
      return self._original_model.config
  
imports: import functools
  import math
  import os
  import shutil
  import sys
  import time
  import types
  import warnings
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
  from transformers.integrations import hp_params
  from transformers.utils import is_accelerate_available
  from packaging import version
  import huggingface_hub.utils
  import torch
  import torch.distributed
  from torch import nn
  from torch.utils.data import Dataset, RandomSampler
  from transformers.data.data_collator import DataCollator
  from transformers.debug_utils import DebugOption, DebugUnderflowOverflow
  from transformers.deepspeed import deepspeed_init, deepspeed_load_checkpoint, is_deepspeed_zero3_enabled
  from transformers.modeling_utils import PreTrainedModel, unwrap_model
  from transformers.tokenization_utils_base import PreTrainedTokenizerBase
  from transformers.trainer import Trainer
  from transformers.trainer_callback import TrainerCallback, TrainerState
  from transformers.trainer_pt_utils import get_model_param_count, get_module_class_from_name, get_parameter_names
  from transformers.trainer_utils import EvalPrediction, HPSearchBackend, TrainOutput, enable_full_determinism, find_executable_batch_size, get_last_checkpoint, has_length, set_seed, speed_metrics
  from transformers.training_args import ParallelMode
  from transformers.utils import is_apex_available, is_sagemaker_dp_enabled, is_sagemaker_mp_enabled, is_torch_tpu_available
  from ..utils import logging
  from .training_args import ORTOptimizerNames, ORTTrainingArguments
  from .utils import is_onnxruntime_training_available
label_desc: Use image node_id 4 for calling the ModuleWithLoss obj's underlying member method code with example usage: obj.config() and returns: self