from fastai.vision import *
import neptune
from neptunecontrib.monitoring.fastai import NeptuneMonitor

ctx = neptune.Context()

mnist = untar_data(URLs.MNIST_TINY)
tfms = get_transforms(do_flip=False)

data = (ImageItemList.from_folder(mnist)
        .split_by_folder()
        .label_from_folder()
        .transform(tfms, size=32)
        .databunch()
        .normalize(imagenet_stats))

neptune_monitor = NeptuneMonitor(ctx=ctx)
learn = create_cnn(data, models.resnet18, metrics=accuracy, callbacks=[neptune_monitor])
learn.fit_one_cycle(2, 1e-2)