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Remove the 'cifar_unnormalized' dataset #23

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Remove the 'cifar_unnormalized' dataset #23

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4 changes: 2 additions & 2 deletions build_label_map.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@ def build_single_label_map(
We may want many label_maps w/ same value of n_labeled.
This allows us to disambiguate.
dataset_name: A string representing the name of the dataset.
One of 'cifar10', 'svhn', 'imagenet', or 'cifar_unnormalized'.
One of 'cifar10', 'svhn', 'imagenet'.
imagenet_path: A string that encodes the location of the raw imagenet
data.
fkeys_path: A string that encodes where to read fkeys from and write
Expand Down Expand Up @@ -143,7 +143,7 @@ def build_single_label_map(
result_dict["values"] += random.sample(
unique_ids, n_labeled_per_class
)
elif dataset_name in {"cifar10", "svhn", "cifar_unnormalized"}:
elif dataset_name in {"cifar10", "svhn"}:
path = os.path.join(fkeys_path, dataset_name, "label_to_fkeys_train")
with gfile.GFile(path, "r") as f:
label_to_fkeys = json.load(f)
Expand Down
8 changes: 0 additions & 8 deletions build_tfrecords.py
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Expand Up @@ -67,12 +67,6 @@
"valid": 50050,
"extra": 0,
},
"cifar_unnormalized": {
"train": 50000,
"test": 10000,
"valid": 5000,
"extra": 0,
},
}

URLS = {
Expand Down Expand Up @@ -192,8 +186,6 @@ def main(_):
train_set, test_set, extra_set = _load_svhn()
elif FLAGS.dataset_name == "cifar10":
train_set, test_set = _load_cifar10(normalize=True)
elif FLAGS.dataset_name == "cifar_unnormalized":
train_set, test_set = _load_cifar10(normalize=False)
elif FLAGS.dataset_name == "imagenet_32":
train_set, test_set = _load_imagenet_32()
else:
Expand Down
9 changes: 0 additions & 9 deletions lib/dataset_utils.py
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Expand Up @@ -39,42 +39,36 @@

DATASET_SHAPE = {
"cifar10": (None, 32, 32, 3),
"cifar_unnormalized": (None, 32, 32, 3),
"svhn": (None, 32, 32, 3),
"svhn_extra": (None, 32, 32, 3),
"imagenet_32": (None, 32, 32, 3),
}
DATASET_DTYPE = {
"cifar10": tf.float32,
"cifar_unnormalized": tf.uint8,
"svhn": tf.uint8,
"svhn_extra": tf.uint8,
"imagenet_32": tf.uint8,
}
DATASET_CLASS_COUNT = {
"cifar10": 10,
"cifar_unnormalized": 10,
"svhn": 10,
"svhn_extra": 10,
"imagenet_32": 1000,
}
DATASET_EXAMPLE_COUNT = {
"train": {
"cifar10": 50000 - 5000,
"cifar_unnormalized": 50000 - 5000,
"svhn": 73257 - 7326,
"svhn_extra": 531131,
"imagenet_32": 1281167 - 50050,
},
"test": {
"cifar10": 10000,
"cifar_unnormalized": 10000,
"svhn": 26032,
"imagenet_32": 50000,
},
"valid": {
"cifar10": 5000,
"cifar_unnormalized": 5000,
"svhn": 7326,
"imagenet_32": 50050,
},
Expand Down Expand Up @@ -309,7 +303,6 @@ def get_filenames(dataset_name, split):
if dataset_name in [
"cifar10",
"svhn",
"cifar_unnormalized",
"imagenet_32",
]:
filenames = [os.path.join(paths.TRAIN_DIR, dataset_name, FILES[split])]
Expand All @@ -332,8 +325,6 @@ def are_datasets_compatible(labeled_dataset_name, unlabeled_dataset_name):
Boolean
"""
valid_combos = [
("cifar_unnormalized", "svhn"),
("svhn", "cifar_unnormalized"),
("svhn", "svhn_extra"),
]
return (labeled_dataset_name == unlabeled_dataset_name) or (
Expand Down
2 changes: 0 additions & 2 deletions lib/hparams.py
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Expand Up @@ -75,7 +75,6 @@ def merge_dicts(x, y):

# HParam overrides for different datasets
cifar10_overrides = dict(horizontal_flip=True)
cifar_unnormalized_overrides = cifar10_overrides

imagenet_overrides = dict(
horizontal_flip=True,
Expand All @@ -86,7 +85,6 @@ def merge_dicts(x, y):
svhn_overrides = dict(gaussian_noise=False, vat_epsilon=1.0)
dataset_overrides = dict(
cifar10=cifar10_overrides,
cifar_unnormalized=cifar_unnormalized_overrides,
imagenet=imagenet_overrides,
imagenet_32=imagenet_overrides,
imagenet_64=imagenet_overrides,
Expand Down