def test_dropout_increases_num_model_layers(self):
model1 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
dropout_prob=0.5)
model2 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
dropout_prob=0.2)
model3 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
dropout_prob=None)
self.assertEqual(len(model1.layers), len(model2.layers))
self.assertGreater(len(model1.layers), len(model3.layers))
def test_num_groups_does_not_change_num_model_parameters(self):
model1 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
num_classes=1000)
model2 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
num_groups=4,
num_classes=1000)
self.assertIsInstance(model1, tf.keras.Model)
self.assertIsInstance(model2, tf.keras.Model)
self.assertEqual(model1.count_params(), model2.count_params())
def test_alpha_changes_num_model_parameters(self):
model1 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
num_classes=1000)
model2 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
alpha=0.5,
num_classes=1000)
model3 = mobilenet_v2.create_mobilenet_v2(input_shape=(224, 224, 3),
alpha=2.0,
num_classes=1000)
self.assertLess(model2.count_params(), model1.count_params())
self.assertLess(model1.count_params(), model3.count_params())
def test_constructs_keras_model(self):
model = mobilenet_v2.create_mobilenet_v2(input_shape=(100, 100, 50))
self.assertIsInstance(model, tf.keras.Model)
def test_negative_num_classes_raises(self):
with self.assertRaisesRegex(ValueError,
'num_classes must be a positive integer'):
mobilenet_v2.create_mobilenet_v2(input_shape=(32, 32, 3),
num_classes=-1)
def test_negative_dropout_prob_raises(self):
with self.assertRaisesRegex(
ValueError,
'dropout_prob must be `None` or a float between 0 and 1'):
mobilenet_v2.create_mobilenet_v2(input_shape=(32, 32, 3),
dropout_prob=-0.5)
def test_unsupported_pooling_raises(self):
with self.assertRaisesRegex(ValueError,
'pooling must be one of avg or max'):
mobilenet_v2.create_mobilenet_v2(input_shape=(32, 32, 3),
pooling='min')
def test_nonpositive_alpha_raises(self):
with self.assertRaisesRegex(ValueError, 'alpha must be positive'):
mobilenet_v2.create_mobilenet_v2(input_shape=(32, 32, 3),
alpha=-1.0)
def test_non_length_3_input_shape_raises(self):
with self.assertRaisesRegex(
ValueError,
'input_shape must be a tuple of length 3 containing '
'positive integers'):
mobilenet_v2.create_mobilenet_v2(input_shape=(10, 2))