khizirsiddiqui

def auroc(model, loader_name='val', N_classes=4):
    model.eval()
    y_test = []
    y_score = []
    with torch.no_grad():
        for i, (inputs, classes) in enumerate(dataloaders[loader_name]):
            inputs = inputs.to(device)
            y_test.append(F.one_hot(classes, N_classes).numpy())
            
            try: