I have to have two labels: coarse_label and fine_label, under there is the dataloader for a single label. How to modify the dataloader?
here I have the piece of train code for cifar 100  with only label:
if args.onlygan:
loaders = {
‘train’: trainloader
}
else:
loaders = {
‘train’: trainloader,
‘test’: testloader
} for epoch in range(args.epochs):
    #print("EPOCH: ", epoch, "/", args.epochs)
    for split in loaders:
        data_loader = loaders[split]

        for  i ,(inputs,labels) in enumerate(tqdm(data_loader, desc=f'EPOCH: {epoch+1}/{args.epochs}')):
            inputs=inputs.to(device)
            labels=labels.to(device)
            

in a separate file:
trainset = torchvision.datasets.CIFAR100(root='./data' ,train=True,
                             download=True, transform=transform)
``` trainloader = torch.utils.data.DataLoader(trainset, batch_size=batch_size,
                                              shuffle=True, num_workers=4)

My doubt is this: if there are inputs and labels for the cifar 100 in the train, the inputs, coarse labels and labels should be in the train. The dataloader for how it is implemented with 2 labels load.