code: def inference(self, data, *args, **kwargs):
      inference_output = []
      with torch.no_grad():
          translation = self.model.translate(data, beam=5)
      logger.info("Model translated: %s", translation)
      for i in range(0, len(data)):
          output = {
              "input": data[i],
              self.setup_config["translated_output"]: translation[i],
          }
          inference_output.append(json.dumps(output))
      return inference_output
  
file_path: serve/examples/nmt_transformer/model_handler_generalized.py
imports: from ts.torch_handler.base_handler import BaseHandler
  from fairseq.models.transformer import TransformerModel
  import torch
  import json
  import os
  import logging
label_desc: Use image node_id 4 for calling the LanguageTranslationHandler obj's underlying member method code with example usage: obj.inference(data) and returns: inference_output