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comply to PEP 8

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Connor Olding 2018-03-24 06:28:00 +01:00
parent 4889740414
commit eac50b5681
2 changed files with 11 additions and 13 deletions
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2
TODO
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@ -2,8 +2,6 @@ TODO
* add prefixes and links to shape table
* abide to PEP 8
* finish writing README
* finish npz functionality

22
mnists/__init__.py
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@ -42,14 +42,14 @@ def make_emnist_meta(npz, name):
metadata = dict(
emnist_balanced = make_emnist_meta("emnist_balanced.npz", "emnist-balanced"),
emnist_byclass = make_emnist_meta("emnist_byclass.npz", "emnist-byclass"),
emnist_bymerge = make_emnist_meta("emnist_bymerge.npz", "emnist-bymerge"),
emnist_digits = make_emnist_meta("emnist_digits.npz", "emnist-digits"),
emnist_letters = make_emnist_meta("emnist_letters.npz", "emnist-letters"),
emnist_mnist = make_emnist_meta("emnist_mnist.npz", "emnist-mnist"),
fashion_mnist = make_meta("fashion_mnist.npz", prefix="fashion-mnist"),
mnist = make_meta("mnist.npz", prefix="mnist"),
emnist_balanced=make_emnist_meta("emnist_balanced.npz", "emnist-balanced"),
emnist_byclass=make_emnist_meta("emnist_byclass.npz", "emnist-byclass"),
emnist_bymerge=make_emnist_meta("emnist_bymerge.npz", "emnist-bymerge"),
emnist_digits=make_emnist_meta("emnist_digits.npz", "emnist-digits"),
emnist_letters=make_emnist_meta("emnist_letters.npz", "emnist-letters"),
emnist_mnist=make_emnist_meta("emnist_mnist.npz", "emnist-mnist"),
fashion_mnist=make_meta("fashion_mnist.npz", prefix="fashion-mnist"),
mnist=make_meta("mnist.npz", prefix="mnist"),
)
@ -77,7 +77,7 @@ def download(name):
url = webhost + url_name
try:
urlretrieve(url, path)
except:
except Exception:
lament(f"Failed to download {url} to {path}")
raise
return already_exists
@ -180,8 +180,8 @@ def prepare(dataset="mnist", return_floats=True, return_onehot=True,
# correct the orientation of emnist images.
if prefix == "emnist":
train_images_data = train_images_data.transpose(0,1,3,2)
test_images_data = test_images_data.transpose(0,1,3,2)
train_images_data = train_images_data.transpose(0, 1, 3, 2)
test_images_data = test_images_data.transpose(0, 1, 3, 2)
if return_floats: # TODO: better name.
train_images_data = train_images_data.astype(np.float32) / 255