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: import torch
  import argparse
  import os
  import logging
  import time
  from torch import nn
  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
  import intel_extension_for_pytorch
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