def testLargeNative(): model = Sequential([ layers.DepthwiseConv2D(5, padding='same', input_shape=(100, 100, 5)) ]) common_test_basis(model, False)
def testLargeEnclave(self): model = Sequential([ layers.DepthwiseConv2D(5, padding='same', input_shape=(100, 100, 5)) ]) common_test_basis(model, True)
def testLargeNative(): model = Sequential([ layers.Dense(100, activation='softmax', kernel_initializer='identity', input_shape=(1, 100)) ]) common_test_basis(model, False)
def testHugeEnclave(self): model = Sequential([ layers.SeparableConv1D(64, 10, input_shape=(500, 64), padding='same') ]) common_test_basis(model, True)
def testMediumEnclave(self): model = Sequential([ layers.Dense(10, activation='sigmoid', kernel_initializer='identity', input_shape=(1, 10)) ]) common_test_basis(model, True)
def testSmallNative(): model = Sequential([ layers.Dense(5, activation='sigmoid', kernel_initializer='identity', input_shape=(1, 5)) ]) common_test_basis(model, False)
def testHugeEnclave(self): model = Sequential([ layers.Dense(1000, activation='softmax', kernel_initializer='identity', input_shape=(1, 1000)) ]) common_test_basis(model, True)
def testMediumNative(): model = Sequential([ layers.Dense(10, activation='relu', kernel_initializer='identity', input_shape=(1, 10)) ]) common_test_basis(model, False)
def testSmallEnclave(self): model = Sequential([ layers.Dense(5, activation='relu', kernel_initializer='identity', input_shape=(1, 5)) ]) common_test_basis(model, True)
def testHugeNative(self): model = Sequential( [layers.MaxPooling2D(pool_size=10, input_shape=(1000, 1000, 64))]) common_test_basis(model, False)
def testLargeEnclave(self): model = Sequential( [layers.GlobalAveragePooling1D(input_shape=(500, 5))]) common_test_basis(model, True)
def testMediumNative(): model = Sequential([layers.Dense(10, input_shape=(1, 10))]) common_test_basis(model, False)
def testSmallEnclave(self): model = Sequential([layers.Dense(5, input_shape=(1, 5))]) common_test_basis(model, True)
def testLargeEnclave(self): model = Sequential( [layers.Conv2D(10, 4, input_shape=(100, 100, 5), padding='same')]) common_test_basis(model, True)
def testLargeNative(): model = Sequential( [layers.Conv2D(10, 4, input_shape=(100, 100, 5), padding='same')]) common_test_basis(model, False)
def testHugeEnclave(self): model = Sequential( [layers.GlobalAveragePooling2D(input_shape=(1000, 1000, 64))]) common_test_basis(model, True)
def testLargeNative(self): model = Sequential( [layers.GlobalAveragePooling2D(input_shape=(100, 100, 10))]) common_test_basis(model, False)
def testMediumNative(self): model = Sequential( [layers.MaxPooling2D(pool_size=3, input_shape=(10, 10, 5))]) common_test_basis(model, False)
def testSmallEnclave(self): model = Sequential( [layers.GlobalAveragePooling2D(input_shape=(5, 5, 3))]) common_test_basis(model, True)
def testSmallEnclave(self): model = Sequential( [layers.MaxPooling2D(pool_size=3, input_shape=(5, 5, 3))]) common_test_basis(model, True)
def testSmallNative(): model = Sequential( [layers.Conv2D(3, 3, input_shape=(5, 5, 3), padding='same')]) common_test_basis(model, False)
def testLargeEnclave(self): model = Sequential( [layers.MaxPooling2D(pool_size=5, input_shape=(100, 100, 10))]) common_test_basis(model, True)
def testSmallEnclave(self): model = Sequential( [layers.Conv2D(3, 3, input_shape=(5, 5, 3), padding='same')]) common_test_basis(model, True)
def testSmallNative(self): model = Sequential([layers.MaxPool1D(pool_size=3, input_shape=(5, 3))]) common_test_basis(model, False)
def testSmallNative(): model = Sequential([layers.Dense(5, input_shape=(1, 5))]) common_test_basis(model, False)
def testLargeNative(self): model = Sequential( [layers.MaxPool1D(pool_size=5, input_shape=(500, 10))]) common_test_basis(model, False)
def testHugeNative(self): model = Sequential([layers.Dense(1000, input_shape=(1, 1000))]) common_test_basis(model, False)
def testMediumEnclave(self): model = Sequential( [layers.MaxPool1D(pool_size=3, input_shape=(50, 3))]) common_test_basis(model, True)
def testHugeEnclave(self): model = Sequential([layers.Dense(1000, input_shape=(1, 1000))]) common_test_basis(model, True)
def testHugeEnclave(self): model = Sequential( [layers.MaxPool1D(pool_size=64, input_shape=(1000, 1000))]) common_test_basis(model, True)