INNER CODE UNIT · Python

batch_size_multiplier

NVIDIA/DeepLearningExamples · PyTorch/Classification/ConvNets/main.py:415

        batch_size_multiplier = int(args.optimizer_batch_size / tbs)
        print("BSM: {}".format(batch_size_multiplier))

    start_epoch = 0
    best_prec1 = 0
    # optionally resume from a checkpoint
    if args.resume is not None:
        if os.path.isfile(args.resume):
            print("=> loading checkpoint '{}'".format(args.resume))
            checkpoint = torch.load(
                args.resume, map_location=lambda storage, loc: storage.cuda(args.gpu)
            )
            start_epoch = checkpoint["epoch"]
            best_prec1 = checkpoint["best_prec1"]
            model_state = checkpoint["state_dict"]
            optimizer_state = checkpoint["optimizer"]
            if "state_dict_ema" in checkpoint:
                model_state_ema = checkpoint["state_dict_ema"]

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