code: def __init__(self):
      super(NeuralNetwork, self).__init__()
      if args.local_only:
          self.bert_encoder = BertModel.from_pretrained(
              checkpoint, local_files_only=True
          )
      else:
          self.bert_encoder = BertModel.from_pretrained(checkpoint)
      self.classifier = nn.Linear(768, 2)
  
imports: import torch
  import argparse
  import os
  import logging
  import time
  from bigdl.nano.pytorch import nano
  from torch import nn
  from contextlib import nullcontext
  from datasets import load_dataset
  from torch.utils.data import DataLoader
  from torch.utils.data.distributed import DistributedSampler
  import torch.distributed
  from transformers import BertTokenizer, BertModel, AdamW
label_desc: Use image node_id 1 to create a new NeuralNetwork object from inherited base classes: nn with example: obj = NeuralNetwork()