You can write your own Dataset class. Basically use existing FashionMNIST with your own custom modifications
class CustomDataset(Dataset):
    def __init__(self, root_dir):
        self.train_set = FashionMNIST(root=root_dir, train=True, download=True)
        self.transforms = torchvision.transforms.Compose([                                                                                                                                                
            torchvision.transforms.Resize((32, 32)),                                                                                                                                                   
            torchvision.transforms.ToTensor(),                                                                                                                                               
 ])                                           
    def __getitem__(self, idx):
        # apply necessary transforms including resize first
        image = self.transforms(self.train_set.data[idx])
        
        # image of shape (1, 3, 32, 32)
        image = image.view((1, 1, 32, 32)).repeat(1, 3, 1, 1)
        label = self.train_set.targets[idx]
        
        # do other operations necessary
        return image, label