def load_test_dataset(path,
inputs_filename=TEST_INPUTS,
labels_filename=TEST_LABELS,
rescale=True):
"""
"""
inputs = load_inputs(path, inputs_filename, rescale)
labels = load_labels(path, labels_filename)
targets = data.targets_from_labels(labels, NUM_CLASSES)
test = data.dataset(inputs, targets, labels)
return test
def load_test_dataset(path,
inputs_filename=TEST_INPUTS,
labels_filename=TEST_LABELS,
rescale=True):
"""
"""
inputs = load_inputs(path, inputs_filename, rescale)
labels = load_labels(path, labels_filename)
targets = data.targets_from_labels(labels, NUM_CLASSES)
test = data.dataset(inputs, targets, labels)
return test
def load_training_dataset(path,
inputs_filename=TRAIN_INPUTS,
labels_filename=TRAIN_LABELS,
rescale=True,
training_set_size=50000):
"""
"""
inputs = load_inputs(path, inputs_filename, rescale)
labels = load_labels(path, labels_filename)
targets = data.targets_from_labels(labels, NUM_CLASSES)
n = training_set_size
train = data.dataset(inputs[0:n], targets[0:n], labels[0:n])
valid = data.dataset(inputs[n:], targets[n:], labels[n:])
return train, valid
def load_training_dataset(path,
inputs_filename=TRAIN_INPUTS,
labels_filename=TRAIN_LABELS,
rescale=True,
training_set_size=50000):
"""
"""
inputs = load_inputs(path, inputs_filename, rescale)
labels = load_labels(path, labels_filename)
targets = data.targets_from_labels(labels, NUM_CLASSES)
n = training_set_size
train = data.dataset(inputs[0:n], targets[0:n], labels[0:n])
valid = data.dataset(inputs[n:], targets[n:], labels[n:])
return train, valid
