Version_2/core/augmentations.py

import torch
from torchvision.transforms import v2

def get_train_transforms(image_size=224):
    return v2.Compose([
        v2.RandomResizedCrop(size=(image_size, image_size), antialias=True),
        v2.RandomHorizontalFlip(p=0.5),
        v2.RandAugment(num_ops=2, magnitude=9), 
        v2.ToImage(),
        v2.ToDtype(torch.float32, scale=True),
        v2.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    ])

def get_eval_transforms(image_size=224):
    return v2.Compose([
        v2.Resize(size=(256, 256), antialias=True),
        v2.CenterCrop(size=(image_size, image_size)),
        v2.ToImage(),
        v2.ToDtype(torch.float32, scale=True),
        v2.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    ])

def get_batch_synthetics(num_classes):
    return v2.RandomChoice([
        v2.CutMix(num_classes=num_classes, alpha=1.0),
        v2.MixUp(num_classes=num_classes, alpha=0.8)
    ])