code: def parallelize(model, distributed, local_rank):
      if distributed:
          return nn.parallel.DistributedDataParallel(
              model,
              device_ids=[local_rank],
              output_device=[local_rank],
              find_unused_parameters=True,
          )
      else:
          return nn.DataParallel(model)
  
file_path: EasyOCR/easyocr/DBNet/model/model.py
imports: import os
  import torch
  import torch.nn
  import torch.nn.functional
  from ..None import backbones
  from ..None import decoders
label_desc: Use image node_id 1 for calling a global function with example usage: parallelize(model, distributed, local_rank) and returns: nn, nn