code: def initialize(self, context):
      self._context = context
      self.initialized = True
      self.manifest = context.manifest
  
      properties = context.system_properties
      model_dir = properties.get("model_dir")
  
      self.device = torch.device(
          "cuda:" + str(properties.get("gpu_id"))
          if torch.cuda.is_available()
          and properties.get("gpu_id") is not None
          else "cpu"
      )
  
      # read configs for the model_name, bpe etc. from setup_config.json
      setup_config_path = os.path.join(model_dir, "setup_config.json")
      if os.path.isfile(setup_config_path):
          with open(setup_config_path) as setup_config_file:
              self.setup_config = json.load(setup_config_file)
      else:
          logger.warning("Missing the setup_config.json file.")
  
      #  load the model
      self.model = TransformerModel.from_pretrained(
          model_dir,
          checkpoint_file="model.pt",
          data_name_or_path=model_dir,
          tokenizer="moses",
          bpe=self.setup_config["bpe"],
      )
      self.model.to(self.device)
      self.model.eval()
      self.initialized = True
  
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 2 for calling the LanguageTranslationHandler obj's underlying member method code with example usage: obj.initialize(context) without return types