Too many values to unpack CIFAR100 to ImageNet

Why I am facing this error only because of changing the Dataset from CIFAR100 to ImageNet

def train_epoch(models, loss_module, criterion, optimizers_backbone, optimizers_module, dataloaders, epoch, epoch_loss):
    global loss 
    loss_module.train()
    global iters
    
    for data in tqdm(dataloaders['train'], leave=False, total=len(dataloaders['train'])):
        with torch.cuda.device(CUDA_VISIBLE_DEVICES):
            inputs = data[0].cuda()
            labels = data[1].cuda()
        iters += 1
        optimizers_backbone.zero_grad()
        optimizers_module.zero_grad()

        scores, _, features = models(inputs)    
        target_loss = criterion(scores, labels)
        
        if epoch > epoch_loss:
            features[0] = features[0].detach()
            features[1] = features[1].detach()
            features[2] = features[2].detach()
            features[3] = features[3].detach()

        pred_loss = loss_module(features)
        pred_loss = pred_loss.view(pred_loss.size(0))
        
        m_module_loss   = LossPredLoss(pred_loss, target_loss, margin=MARGIN)
        m_backbone_loss = torch.sum(target_loss) / target_loss.size(0)        
        
        loss = m_backbone_loss + WEIGHT * m_module_loss 
        
        loss.backward()
        optimizers_backbone.step()
        optimizers_module.step()  
    return loss

scores, _, features = models(inputs)
ValueError: too many values to unpack (expected 3)

Hi,
could you check how many values the models is returning.

The error is on this line, models was dictionary earlier, I removed the dictionary, and now it is giving error
scores, _, features = models(inputs)