sample run lesson1-pets.ipynb to test M1 mac

lesson1-test-m1.py

from fastai.vision.all import *
#from nbdev.showdoc import *

set_seed(2)

bs = 64
path = untar_data(URLs.PETS);

Path.BASE_PATH = path # display all paths relative to dataset root

path_anno = path/'annotations'
path_img = path/'images'

fnames = get_image_files(path_img)

dls = ImageDataLoaders.from_name_re(
    path, fnames, pat=r'(.+)_\d+.jpg$', item_tfms=Resize(460), bs=bs,
    batch_tfms=[*aug_transforms(size=224, min_scale=0.75), Normalize.from_stats(*imagenet_stats)])

print(dls.vocab)

learn = vision_learner(dls, resnet34, metrics=error_rate).to_fp16()
learn.fit_one_cycle(1)