def test_augmentation(self):
import fast_denser.utilities.data as data
import fast_denser.utilities.data_augmentation as data_augmentation
import tensorflow as tf
cifar_10 = data.load_dataset(dataset='cifar10')
input_image = cifar_10['evo_x_train'][0]
augmented_image = data_augmentation.augmentation(input_image)
diff = input_image - augmented_image
self.assertTrue(diff.sum() != 0, "Error augmenting an image")
def __init__(self, dataset, fitness_metric):
"""
Creates the Evaluator instance and loads the dataset.
Parameters
----------
dataset : str
dataset to be loaded
"""
self.dataset = load_dataset(dataset)
self.fitness_metric = fitness_metric
def test_load_datasets(self):
import fast_denser.utilities.data as data
fashion_mnist = data.load_dataset(dataset='fashion-mnist')
mnist = data.load_dataset(dataset='mnist')
svhn = data.load_dataset(dataset='svhn')
cifar_10 = data.load_dataset(dataset='cifar10')
cifar_100_fine = data.load_dataset(dataset='cifar100-fine')
cifar_100_coarse = data.load_dataset(dataset='cifar100-coarse')
tiny_imagenet = data.load_dataset(dataset='tiny-imagenet')
self.assertTrue(fashion_mnist, "Error loading fashion-mnist")
self.assertTrue(mnist, "Error loading mnist")
self.assertTrue(svhn, "Error loading svhn")
self.assertTrue(cifar_10, "Error loading cifar-10")
self.assertTrue(cifar_100_fine, "Error loading cifar-100-fine")
self.assertTrue(cifar_100_coarse, "Error loading cifar-100-coarse")
self.assertTrue(tiny_imagenet, "Error loading cifar-100-coarse")
with self.assertRaises(SystemExit) as cm:
other = data.load_dataset(dataset='not valid')
self.assertEqual(cm.exception.code, -1,
"Error: read invalid grammar")