Further clean up

tasks/facial_landmark_detection/train.py

@@ -161,21 +161,12 @@ def train(args, model: nn.Module = None):
 
     collate_fn = None
     num_classes = dataset.dataset.num_landmarks
-    mixup_transforms = []
-    if args.mixup_alpha > 0.0:
-        mixup_transforms.append(transforms.RandomMixup(num_classes, p=1.0, alpha=args.mixup_alpha))
-    if args.cutmix_alpha > 0.0:
-        mixup_transforms.append(transforms.RandomCutmix(num_classes, p=1.0, alpha=args.cutmix_alpha))
-    if mixup_transforms:
-        mixupcutmix = torchvision.transforms.RandomChoice(mixup_transforms)
-        collate_fn = lambda batch: mixupcutmix(*default_collate(batch))  # noqa: E731
     data_loader = torch.utils.data.DataLoader(
         dataset,
         batch_size=args.batch_size,
         sampler=train_sampler,
         num_workers=args.workers,
         pin_memory=True,
-        collate_fn=collate_fn,
     )
     data_loader_test = torch.utils.data.DataLoader(
         dataset_test, batch_size=args.batch_size, sampler=test_sampler, num_workers=args.workers, pin_memory=True