code: def infer(self, inputs, attn_mask):
      last_hidden_states = self.ls_bert.infer(inputs)
      last_hidden_states = torch.Tensor(last_hidden_states).float()
      pooled_output = self.pooler(last_hidden_states.to("cuda:0"))
      logits = self.classifier(pooled_output)
      return logits
  
file_path: lightseq/examples/inference/python/test/ls_bert.py
imports: import time
  import argparse
  import torch
  import lightseq.inference
  from transformers import BertTokenizer, BertForSequenceClassification
label_desc: Use image node_id 2 for calling the LightseqBertClassification obj's underlying member method code with example usage: obj.infer(inputs, attn_mask) and returns: logits