code: def forward(self, x):
      bert_output = self.bert_encoder(**x)
      cls_vectors = bert_output.last_hidden_state[:, 0]
      logits = self.classifier(cls_vectors)
      return logits
  
imports: from torch.utils.data import DataLoader
  import torch
  import torch.optim
  from contextlib import nullcontext
  import torch.nn.functional
  import os
  import torch.nn
  import time
  from bigdl.nano.pytorch.patching import patch_encryption
  from bigdl.nano.pytorch.encryption import EncryptedDataset
  import logging
  from bigdl.ppml.kms.ehsm.client import generate_primary_key, generate_data_key, get_data_key_plaintext
  from datasets.load import load_from_disk
  import argparse
  from transformers import BertTokenizer, BertModel, AdamW
label_desc: Use image node_id 2 for calling the NeuralNetwork obj's underlying member method code with example usage: obj.forward(x) and returns: logits