Function validate

validate.py:172–453

(args)

def validate(args):
    # might as well try to validate something
    args.pretrained = args.pretrained or not args.checkpoint
    args.prefetcher = not args.no_prefetcher

    if torch.cuda.is_available():
        torch.backends.cuda.matmul.allow_tf32 = True
        torch.backends.cudnn.benchmark = True

    device = torch.device(args.device)

    if args.metrics_avg and not has_sklearn:
        _logger.warning(
            f"scikit-learn not installed, disabling metrics calculation. Please install with 'pip install scikit-learn'.")
        args.metrics_avg = None

    model_dtype = None
    if args.model_dtype:
        assert args.model_dtype in ('float32', 'float16', 'bfloat16')
        model_dtype = getattr(torch, args.model_dtype)

    # resolve AMP arguments based on PyTorch availability
    amp_autocast = suppress
    if args.amp:
        assert model_dtype is None or model_dtype == torch.float32, 'float32 model dtype must be used with AMP'
        assert args.amp_dtype in ('float16', 'bfloat16')
        amp_dtype = torch.bfloat16 if args.amp_dtype == 'bfloat16' else torch.float16
        amp_autocast = partial(torch.autocast, device_type=device.type, dtype=amp_dtype)
        _logger.info('Validating in mixed precision with native PyTorch AMP.')
    else:
        _logger.info(f'Validating in {model_dtype or torch.float32}. AMP not enabled.')

    if args.fuser:
        set_jit_fuser(args.fuser)

    if args.fast_norm:
        set_fast_norm()

    # create model
    in_chans = 3
    if args.in_chans is not None:
        in_chans = args.in_chans
    elif args.input_size is not None:
        in_chans = args.input_size[0]

    model = create_model(
        args.model,
        pretrained=args.pretrained,
        num_classes=args.num_classes,
        in_chans=in_chans,
        global_pool=args.gp,
        scriptable=args.torchscript,
        **args.model_kwargs,
    )
    if args.num_classes is None:
        assert hasattr(model, 'num_classes'), 'Model must have `num_classes` attr if not set on cmd line/config.'
        args.num_classes = model.num_classes