Code snippet for medium article

celeba_dataloaders.py

get_x = lambda x:CELEBA_PATH/f'{x[0]}'
get_y = lambda x:[headers[index+1] for index,val in enumerate(x[1:]) if val == 1]

batch_tfms = [*aug_transforms(size=224, max_warp=0), Normalize.from_stats(*imagenet_stats)]
item_tfms = RandomResizedCrop(460, min_scale=0.75, ratio=(1.,1.))
bs=64
celleba_data = DataBlock(blocks=(ImageBlock, MultiCategoryBlock),
                   get_x=get_x,
                   splitter=RandomSplitter(),
                   get_y=get_y,
                   item_tfms=item_tfms,
                  batch_tfms=batch_tfms)
                  
dls = celleba_data.dataloaders(df, bs=bs)
dls.show_batch(max_n=9, figsize=(20,9))