gossip_sgd.py [302:327]:
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        start_itr = 0
        if not args.train_fast:
            # update state after each epoch
            elapsed_time = time.time() - begin_time
            update_state(state, {
                'epoch': epoch + 1, 'itr': start_itr,
                'is_best': False,
                'state_dict': model.state_dict(),
                'optimizer': optimizer.state_dict(),
                'elapsed_time': elapsed_time,
                'batch_meter': batch_meter.__dict__,
                'data_meter': data_meter.__dict__,
                'nn_meter': nn_meter.__dict__
            })
            # evaluate on validation set and save checkpoint
            prec1 = validate(val_loader, model, criterion)
            with open(args.out_fname, '+a') as f:
                print('{ep},{itr},{bt},{nt},{dt},'
                      '{filler},{filler},'
                      '{filler},{filler},'
                      '{filler},{filler},'
                      '{val}'
                      .format(ep=epoch, itr=-1,
                              bt=batch_meter,
                              dt=data_meter, nt=nn_meter,
                              filler=-1, val=prec1), file=f)
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gossip_sgd_adpsgd.py [278:303]:
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        start_itr = 0
        if not args.train_fast:
            # update state after each epoch
            elapsed_time = time.time() - begin_time
            update_state(state, {
                'epoch': epoch + 1, 'itr': start_itr,
                'is_best': False,
                'state_dict': model.state_dict(),
                'optimizer': optimizer.state_dict(),
                'elapsed_time': elapsed_time,
                'batch_meter': batch_meter.__dict__,
                'data_meter': data_meter.__dict__,
                'nn_meter': nn_meter.__dict__
            })
            # evaluate on validation set and save checkpoint
            prec1 = validate(val_loader, model, criterion)
            with open(args.out_fname, '+a') as f:
                print('{ep},{itr},{bt},{nt},{dt},'
                      '{filler},{filler},'
                      '{filler},{filler},'
                      '{filler},{filler},'
                      '{val}'
                      .format(ep=epoch, itr=-1,
                              bt=batch_meter,
                              dt=data_meter, nt=nn_meter,
                              filler=-1, val=prec1), file=f)
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