gossip_sgd.py [263:279]:
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        with open(args.out_fname, 'w') as f:
            print('BEGIN-TRAINING\n'
                  'World-Size,{ws}\n'
                  'Num-DLWorkers,{nw}\n'
                  'Batch-Size,{bs}\n'
                  'Epoch,itr,BT(s),avg:BT(s),std:BT(s),'
                  'NT(s),avg:NT(s),std:NT(s),'
                  'DT(s),avg:DT(s),std:DT(s),'
                  'Loss,avg:Loss,Prec@1,avg:Prec@1,Prec@5,avg:Prec@5,val'
                  .format(ws=args.world_size,
                          nw=args.num_dataloader_workers,
                          bs=args.batch_size), file=f)

    # create distributed data loaders
    loader, sampler = make_dataloader(args, train=True)
    if not args.train_fast:
        val_loader = make_dataloader(args, train=False)
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gossip_sgd_adpsgd.py [243:259]:
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        with open(args.out_fname, 'w') as f:
            print('BEGIN-TRAINING\n'
                  'World-Size,{ws}\n'
                  'Num-DLWorkers,{nw}\n'
                  'Batch-Size,{bs}\n'
                  'Epoch,itr,BT(s),avg:BT(s),std:BT(s),'
                  'NT(s),avg:NT(s),std:NT(s),'
                  'DT(s),avg:DT(s),std:DT(s),'
                  'Loss,avg:Loss,Prec@1,avg:Prec@1,Prec@5,avg:Prec@5,val'
                  .format(ws=args.world_size,
                          nw=args.num_dataloader_workers,
                          bs=args.batch_size), file=f)

    # create distributed data loaders
    loader, sampler = make_dataloader(args, train=True)
    if not args.train_fast:
        val_loader = make_dataloader(args, train=False)
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