def train_transform(self) -> Callable:
        """The standard imagenet transforms.
        .. code-block:: python
            transforms.Compose([
                transforms.RandomResizedCrop(self.image_size),
                transforms.RandomHorizontalFlip(),
                transforms.ToTensor(),
                transforms.Normalize(
                    mean=[0.485, 0.456, 0.406],
                    std=[0.229, 0.224, 0.225]
                ),
            ])
        """
        preprocessing = transforms.Compose(
            [
                transforms.RandomResizedCrop(self.image_size),
                transforms.RandomHorizontalFlip(),
                transforms.ToTensor(),
                imagenet_normalization(),
            ]
        )

        return preprocessing
The standard imagenet transforms.
        .. code-block:: python
            transforms.Compose([
                transforms.RandomResizedCrop(self.image_size),
                transforms.RandomHorizontalFlip(),
                transforms.ToTensor(),
                transforms.Normalize(
                    mean=[0.485, 0.456, 0.406],
                    std=[0.229, 0.224, 0.225]
                ),
            ])
        
training/src/datamodules/imagenet.py