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)
