def test_repetitions_increase_number_parameters(self):
input_shape = (32, 32, 3)
num_classes = 10
small_resnet = resnet_models.create_resnet(
input_shape, num_classes, repetitions=[1, 1])
big_resnet = resnet_models.create_resnet(
input_shape, num_classes, repetitions=[2, 2])
self.assertLess(small_resnet.count_params(), big_resnet.count_params())
def test_basic_fewer_parameters_than_bottleneck(self):
input_shape = (32, 32, 3)
num_classes = 10
basic_resnet = resnet_models.create_resnet(
input_shape, num_classes, block='basic')
bottleneck_resnet = resnet_models.create_resnet(
input_shape, num_classes, block='bottleneck')
self.assertLess(basic_resnet.count_params(),
bottleneck_resnet.count_params())
def test_group_norm_constructs(self):
group_resnet = resnet_models.create_resnet(
input_shape=(32, 32, 3), num_classes=10, norm='group')
self.assertIsInstance(group_resnet, tf.keras.Model)
def test_batch_norm_constructs(self):
batch_resnet = resnet_models.create_resnet(
input_shape=(32, 32, 3), num_classes=10, norm='batch')
self.assertIsInstance(batch_resnet, tf.keras.Model)