distributed_training/train_pytorch_single_maskrcnn.py [279:291]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    cfg.merge_from_file(args.config_file)
    cfg.merge_from_list(args.opts)
    cfg.DTYPE=args.dtype
    # grab checkpoint file to start from
    os.system(f"aws s3 cp {args.spot_ckpt} /opt/ml/checkpoints/{args.spot_ckpt.split('/')[-1]}")
    cfg.MODEL.WEIGHT = f"/opt/ml/checkpoints/{args.spot_ckpt.split('/')[-1]}"
    cfg.freeze()
    print ("CONFIG")
    print (cfg)

    output_dir = cfg.OUTPUT_DIR
    if output_dir:
        mkdir(output_dir)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



distributed_training/train_pytorch_smdataparallel_maskrcnn.py [296:308]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    cfg.merge_from_file(args.config_file)
    cfg.merge_from_list(args.opts)
    cfg.DTYPE=args.dtype
    # grab checkpoint file to start from
    os.system(f"aws s3 cp {args.spot_ckpt} /opt/ml/checkpoints/{args.spot_ckpt.split('/')[-1]}")
    cfg.MODEL.WEIGHT = f"/opt/ml/checkpoints/{args.spot_ckpt.split('/')[-1]}"
    cfg.freeze()
    print ("CONFIG")
    print (cfg)

    output_dir = cfg.OUTPUT_DIR
    if output_dir:
        mkdir(output_dir)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



