code: def infer(self, sentence: str):
      inputs = self.tokenizer.encode_plus(
          sentence,
          return_tensors="pt",
          padding="max_length",
          truncation=True,
          max_length=128,
      )
      output = self.model(
          *(inputs["input_ids"], inputs["attention_mask"])
      )
      class_id = torch.argmax(output["logits"], dim=1).item()
      return self.classmap[class_id]
  
file_path: ray/doc/source/serve/doc_code/aws_neuron_core_inference_serve.py
imports: from transformers import AutoModelForSequenceClassification, AutoTokenizer
  import torch, torch_neuronx
  from fastapi import FastAPI
  import torch
  from ray import serve
  from ray.serve.handle import DeploymentHandle
label_desc: Use image node_id 2 for calling the BertBaseModel obj's underlying member method code with example usage: obj.infer(sentence) and returns: self