def make_labeled_data_filter_fn(label_table):
"""Make filter for certain classes of labeled data."""
class_filter = tf_utils.filter_fn_from_comma_delimited(
FLAGS.labeled_classes_filter)
if label_table:
return lambda _, label, fkey: class_filter(label) & label_table.lookup(
fkey)
else:
return lambda _, label, fkey: class_filter(label)
def make_unlabeled_data_filter_fn():
"""Make filter for certain classes and a random fraction of unlabeled
data."""
class_filter = tf_utils.filter_fn_from_comma_delimited(
FLAGS.unlabeled_classes_filter)
def random_frac_filter(fkey):
return tf_utils.hash_float(fkey) < FLAGS.unlabeled_data_random_fraction
return lambda _, label, fkey: class_filter(label) & random_frac_filter(fkey
)
def make_labeled_data_filter():
"""Make filter for certain classes of labeled data."""
if FLAGS.primary_dataset_name in {
"cifar100", "tinyimagenet_32", "cifar100_tinyimagenet"
}:
labels = FLAGS.labeled_classes_filter.split(',')
labels = range(int(labels[0]), int(labels[1]))
labeled_classes_filter = ",".join([str(x) for x in labels])
else:
labeled_classes_filter = FLAGS.labeled_classes_filter
print(labeled_classes_filter)
class_filter = tf_utils.filter_fn_from_comma_delimited(
labeled_classes_filter)
return lambda image, label, index, fkey: class_filter(label)
def make_unlabeled_data_filter_fn():
"""Make filter for certain classes and a random fraction of unlabeled
data."""
if FLAGS.secondary_dataset_name in {
"cifar100", "tinyimagenet_32", "cifar100_tinyimagenet"
}:
labels = FLAGS.unlabeled_classes_filter.split(',')
labels = range(int(labels[0]), int(labels[1]))
labeled_classes_filter = ",".join([str(x) for x in labels])
else:
labeled_classes_filter = FLAGS.unlabeled_classes_filter
print(labeled_classes_filter)
class_filter = tf_utils.filter_fn_from_comma_delimited(
labeled_classes_filter)
def random_frac_filter(fkey):
return tf_utils.hash_float(fkey) < FLAGS.unlabeled_data_random_fraction
return lambda _, label, index, fkey: class_filter(
label) & random_frac_filter(fkey)
def make_labeled_data_filter():
"""Make filter for certain classes of labeled data."""
class_filter = tf_utils.filter_fn_from_comma_delimited(
FLAGS.labeled_classes_filter)
return lambda image, label, fkey: class_filter(label)
