code: def raw_special_model_setup(
      model, optimizer, fp16, fp16_opt_level, n_gpu, local_rank
  ):
      """Perform setup for special modes (e.g., FP16, DataParallel, and/or DistributedDataParallel.
  
      Args:
          model (nn.Module): torch model object.
          optimizer: TODO
          fp16 (bool): True to enable FP16 mode.
          fp16_opt_level (str): Apex AMP optimization level default mode identifier.
          n_gpu: number of GPUs.
          local_rank (int): Which GPU the script should use in DistributedDataParallel mode.
  
      Notes:
          Initialization steps performed in init_cuda_from_args() set n_gpu = 1 when local_rank != -1.
  
      Returns:
          Model and optimizer with the specified special configuration.
  
      """
      if fp16:
          model, optimizer = fp16ize(
              model=model,
              optimizer=optimizer,
              fp16_opt_level=fp16_opt_level,
          )
      if n_gpu > 1:
          model = parallelize_gpu(model=model)
      if local_rank != -1:
          model = parallelize_dist(model=model, local_rank=local_rank)
      return model, optimizer
  
file_path: jiant/jiant/shared/model_setup.py
imports: import transformers
  import torch
  from jiant.ext.radam import RAdam
label_desc: Use image node_id 7 for calling a global function with example usage: raw_special_model_setup(model, optimizer, fp16, fp16_opt_level, n_gpu, local_rank) and returns: model,  optimizer