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%load_ext autoreload
%autoreload 2

%matplotlib inline


    

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from exp.nb_08 import *


    

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path = datasets.untar_data(datasets.URLs.IMAGENETTE_320)


    

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tfms = [make_rgb, ResizeFixed(224), to_byte_tensor, to_float_tensor]

il = ImageList.from_files(path, tfms=tfms)
sd = SplitData.split_by_func(il, partial(grandparent_splitter, valid_name='val'))
ll = label_by_func(sd, parent_labeler, proc_y=CategoryProcessor())


    

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bs=256


    

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train_dl,valid_dl = get_dls(ll.train,ll.valid,bs, num_workers=4)


    

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%time x,y = next(iter(train_dl))


    

    




CPU times: user 12.5 ms, sys: 169 ms, total: 182 ms
Wall time: 1.99 s

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%time for x,y in train_dl: x,y = x.cuda(),y.cuda()


    

    




CPU times: user 1.31 s, sys: 1.8 s, total: 3.11 s
Wall time: 11.5 s

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