code: def main_worker(cfg):
      # create tensorboard and logs
      if cfg.DDP_CONFIG.GPU_WORLD_RANK == 0:
          tb_logdir = build_log_dir(cfg)
          writer = SummaryWriter(log_dir=tb_logdir)
      else:
          writer = None
      cfg.freeze()
  
      # create model
      # model = get_model(cfg)
      model = directpose_resnet_lpf_fpn(cfg)
      model = deploy_model(model, cfg)
  
      # create dataset and dataloader
      # train_loader, val_loader, train_sampler, val_sampler, mg_sampler = build_pose_train_loader(cfg)
      train_loader = build_pose_train_loader(cfg)
      val_loader = build_pose_test_loader(
          cfg, cfg.CONFIG.DATA.DATASET.VAL[0]
      )
      optimizer = build_pose_optimizer(cfg, model)
      scheduler = build_lr_scheduler(cfg, optimizer)
  
      # if cfg.CONFIG.MODEL.LOAD:
      #     model, _ = load_model(model, optimizer, cfg, load_fc=True)
      # criterion = nn.CrossEntropyLoss().cuda()
  
      pipeline = DirectposePipeline(
          0,
          cfg.CONFIG.TRAIN.ITER_NUM,
          model,
          train_loader,
          optimizer,
          scheduler,
          cfg,
          writer=writer,
      )
      while pipeline.base_iter < pipeline.max_iter:
          pipeline.train_step()
  
          if (
              pipeline.base_iter % cfg.CONFIG.VAL.EVAL_PERIOD == 0
              or pipeline.base_iter == pipeline.max_iter
          ):
              pipeline.validate(val_loader)
  
          if (
              pipeline.base_iter % cfg.CONFIG.TRAIN.CHECKPOINT_PERIOD
              == 0
          ):
              if (
                  cfg.DDP_CONFIG.GPU_WORLD_RANK == 0
                  or cfg.DDP_CONFIG.DISTRIBUTED == False
              ):
                  pipeline.save_model()
  
      if writer is not None:
          writer.close()
  
file_path: gluon-cv/scripts/pose/directpose/train_ddp_directpose.py
imports: import os
  import argparse
  import torch
  import torch.nn
  import torch.distributed
  import torch.optim
  from tensorboardX import SummaryWriter
  from gluoncv.torch.model_zoo import get_model
  from gluoncv.torch.model_zoo.pose import directpose_resnet_lpf_fpn
  from gluoncv.torch.data.pose import build_pose_train_loader, build_pose_test_loader
  from gluoncv.torch.utils.model_utils import deploy_model, load_model, save_model
  from gluoncv.torch.utils.task_utils import DirectposePipeline, build_pose_optimizer
  from gluoncv.torch.engine.config import get_cfg_defaults
  from gluoncv.torch.engine.launch import spawn_workers
  from gluoncv.torch.utils.utils import build_log_dir
  from gluoncv.torch.utils.lr_policy import build_lr_scheduler
label_desc: Use image node_id 1 for calling a global function with example usage: main_worker(cfg) without return types