INNER CODE UNIT · Python

logger

NVIDIA/DeepLearningExamples · PyTorch/Classification/ConvNets/main.py:559

        logger = log.Logger(args.print_freq, [], start_epoch=start_epoch - 1)

    logger.log_parameter(args.__dict__, verbosity=dllogger.Verbosity.DEFAULT)
    logger.log_parameter(
        {f"model.{k}": v for k, v in model_args.__dict__.items()},
        verbosity=dllogger.Verbosity.DEFAULT,
    )

    optimizer = get_optimizer(
        list(executor.model.named_parameters()),
        args.lr,
        args=args,
        state=optimizer_state,
    )

    if args.lr_schedule == "step":
        lr_policy = lr_step_policy(args.lr, [30, 60, 80], 0.1, args.warmup)
    elif args.lr_schedule == "cosine":

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