def generate_secure_vgg(num_class):
input_img_hw = 32
input_channel = 3
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(3, 64, 3, "conv1", padding=1)
pool1 = Maxpool2x2SecureLayer("pool1")
relu1 = ReluSecureLayer("relu1")
trun1 = TruncSecureLayer("trun1")
conv2 = Conv2dSecureLayer(64, 128, 3, "conv2", padding=1)
pool2 = Maxpool2x2SecureLayer("pool2")
relu2 = ReluSecureLayer("relu2")
trun2 = TruncSecureLayer("trun2")
conv3 = Conv2dSecureLayer(128, 256, 3, "conv3", padding=1)
relu3 = ReluSecureLayer("relu3")
trun3 = TruncSecureLayer("trun3")
conv4 = Conv2dSecureLayer(256, 256, 3, "conv4", padding=1)
pool3 = Maxpool2x2SecureLayer("pool3")
relu4 = ReluSecureLayer("relu4")
trun4 = TruncSecureLayer("trun4")
conv5 = Conv2dSecureLayer(256, 512, 3, "conv5", padding=1)
relu5 = ReluSecureLayer("relu5")
trun5 = TruncSecureLayer("trun5")
conv6 = Conv2dSecureLayer(512, 512, 3, "conv6", padding=1)
pool4 = Maxpool2x2SecureLayer("pool4")
relu6 = ReluSecureLayer("relu6")
trun6 = TruncSecureLayer("trun6")
conv7 = Conv2dSecureLayer(512, 512, 3, "conv7", padding=1)
relu7 = ReluSecureLayer("relu7")
trun7 = TruncSecureLayer("trun7")
conv8 = Conv2dSecureLayer(512, 512, 3, "conv8", padding=1)
relu8 = ReluSecureLayer("relu8")
trun8 = TruncSecureLayer("trun8")
pool5 = Maxpool2x2SecureLayer("pool5")
flatten = FlattenSecureLayer("flatten")
fc1 = FcSecureLayer(512, "fc1")
relu_fc_1 = ReluSecureLayer("relu_fc_1")
trun_fc_1 = TruncSecureLayer("trun_fc_1")
fc2 = FcSecureLayer(512, "fc2")
relu_fc_2 = ReluSecureLayer("relu_fc_2")
trun_fc_2 = TruncSecureLayer("trun_fc_2")
fc3 = FcSecureLayer(num_class, "fc3")
output_layer = OutputSecureLayer("output_layer")
layers = [
input_layer, conv1, pool1, relu1, trun1, conv2, pool2, relu2, trun2,
conv3, relu3, trun3, conv4, pool3, relu4, trun4, conv5, relu5, trun5,
conv6, relu6, pool4, trun6, conv7, relu7, trun7, conv8, relu8, pool5,
trun8, flatten, fc1, relu_fc_1, trun_fc_1, fc2, relu_fc_2, trun_fc_2,
fc3, output_layer
]
secure_nn = SecureNnFramework("vgg")
secure_nn.load_layers(layers)
return secure_nn
def generate_fc():
num_input_unit = 1024
num_output_unit = 128
input_shape = [num_input_unit]
input_layer = InputSecureLayer(input_shape, "input_layer")
fc1 = FcSecureLayer(num_output_unit, "fc1")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, fc1, output_layer]
secure_nn = SecureNnFramework("fc")
secure_nn.load_layers(layers)
return secure_nn
def generate_conv2d():
input_img_hw = 16
input_channel = 128
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(128, 128, 3, "conv1", padding=1)
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, conv1, output_layer]
secure_nn = SecureNnFramework("conv2d")
secure_nn.load_layers(layers)
return secure_nn
def generate_secure_minionn(pooling_type_name):
input_img_hw = 32
input_channel = 3
input_shape = [input_channel, input_img_hw, input_img_hw]
if pooling_type_name == "maxpool":
pool = Maxpool2x2SecureLayer
elif pooling_type_name == "avgpool":
pool = Avgpool2x2SecureLayer
else:
raise Exception(f"Unknown Pooling Type Name: {pooling_type_name}")
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(3, 64, 3, "conv1", padding=1)
relu1 = ReluSecureLayer("relu1")
trun1 = TruncSecureLayer("trun1")
conv2 = Conv2dSecureLayer(64, 64, 3, "conv2", padding=1)
relu2 = ReluSecureLayer("relu2")
pool1 = pool("pool1")
trun2 = TruncSecureLayer("trun2")
conv3 = Conv2dSecureLayer(64, 64, 3, "conv3", padding=1)
relu3 = ReluSecureLayer("relu3")
trun3 = TruncSecureLayer("trun3")
conv4 = Conv2dSecureLayer(64, 64, 3, "conv4", padding=1)
pool2 = pool("pool2")
relu4 = ReluSecureLayer("relu4")
trun4 = TruncSecureLayer("trun4")
conv5 = Conv2dSecureLayer(64, 64, 3, "conv5", padding=1)
relu5 = ReluSecureLayer("relu5")
trun5 = TruncSecureLayer("trun5")
conv6 = Conv2dSecureLayer(64, 64, 3, "conv6", padding=1)
relu6 = ReluSecureLayer("relu6")
trun6 = TruncSecureLayer("trun6")
conv7 = Conv2dSecureLayer(64, 16, 3, "conv7", padding=1)
relu8 = ReluSecureLayer("relu8")
flatten = FlattenSecureLayer("flatten")
trun7 = TruncSecureLayer("trun7")
fc1 = FcSecureLayer(10, "fc1")
# fc1 = FcSecureLayer(2, "fc1")
output_layer = OutputSecureLayer("output_layer")
layers = [
input_layer, conv1, relu1, trun1, conv2, pool1, relu2, trun2, conv3,
relu3, trun3, conv4, pool2, relu4, trun4, conv5, relu5, trun5, conv6,
relu6, trun6, conv7, relu8, trun7, flatten, fc1, output_layer
]
secure_nn = SecureNnFramework("minionn_avgpool")
secure_nn.load_layers(layers)
return secure_nn
def generate_maxpool2x2():
num_elem = 2 ** 17
input_img_hw = 16
input_channel = num_elem // (input_img_hw ** 2)
assert(input_img_hw * input_img_hw * input_channel == num_elem)
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
pool1 = Maxpool2x2SecureLayer("pool1")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, pool1, output_layer]
secure_nn = SecureNnFramework("maxpool2x2")
secure_nn.load_layers(layers)
return secure_nn
def generate_relu_only_nn():
num_elem = 2 ** 17
input_img_hw = 16
input_channel = num_elem // (input_img_hw ** 2)
assert(input_img_hw * input_img_hw * input_channel == num_elem)
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
relu1 = ReluSecureLayer("relu1")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, relu1, output_layer]
secure_nn = SecureNnFramework("relu_only_nn")
secure_nn.load_layers(layers)
return secure_nn
def generate_small_nn():
input_img_hw = 16
input_channel = 3
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(3, 5, 3, "conv1", padding=1)
relu1 = ReluSecureLayer("relu1")
pool1 = Maxpool2x2SecureLayer("pool1")
conv2 = Conv2dSecureLayer(5, 10, 3, "conv2", padding=1)
flatten = FlattenSecureLayer("flatten")
fc1 = FcSecureLayer(512, "fc1")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, conv1, pool1, relu1, conv2, flatten, fc1, output_layer]
secure_nn = SecureNnFramework("small_nn")
secure_nn.load_layers(layers)
return secure_nn
def generate_minionn_mnist():
input_img_hw = 28
input_channel = 1
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(input_channel, 16, 5, "conv1", padding=0)
pool1 = Maxpool2x2SecureLayer("pool1")
relu1 = ReluSecureLayer("relu1")
conv2 = Conv2dSecureLayer(16, 16, 5, "conv2", padding=0)
pool2 = Maxpool2x2SecureLayer("pool2")
relu2 = ReluSecureLayer("relu2")
flatten = FlattenSecureLayer("flatten")
fc1 = FcSecureLayer(100, "fc1")
relu3 = ReluSecureLayer("relu3")
fc2 = FcSecureLayer(10, "fc2")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer, conv1, pool1, relu1, conv2, pool2, relu2, flatten, fc1, relu3, fc2, output_layer]
secure_nn = SecureNnFramework("minionn_mnist")
secure_nn.load_layers(layers)
return secure_nn
def generate_minionn_cifar10():
input_img_hw = 32
input_channel = 3
input_shape = [input_channel, input_img_hw, input_img_hw]
input_layer = InputSecureLayer(input_shape, "input_layer")
conv1 = Conv2dSecureLayer(3, 64, 3, "conv1", padding=1)
relu1 = ReluSecureLayer("relu1")
conv2 = Conv2dSecureLayer(64, 64, 3, "conv2", padding=1)
pool1 = Maxpool2x2SecureLayer("pool1")
relu2 = ReluSecureLayer("relu2")
conv3 = Conv2dSecureLayer(64, 64, 3, "conv3", padding=1)
relu3 = ReluSecureLayer("relu3")
conv4 = Conv2dSecureLayer(64, 64, 3, "conv4", padding=1)
pool2 = Maxpool2x2SecureLayer("pool2")
relu4 = ReluSecureLayer("relu4")
conv5 = Conv2dSecureLayer(64, 64, 3, "conv5", padding=1)
relu5 = ReluSecureLayer("relu5")
conv6 = Conv2dSecureLayer(64, 64, 3, "conv6", padding=1)
relu6 = ReluSecureLayer("relu6")
conv7 = Conv2dSecureLayer(64, 16, 3, "conv7", padding=1)
relu8 = ReluSecureLayer("relu8")
flatten = FlattenSecureLayer("flatten")
fc1 = FcSecureLayer(10, "fc1")
output_layer = OutputSecureLayer("output_layer")
layers = [input_layer,
conv1, relu1,
conv2, pool1, relu2, conv3, relu3,
conv4, pool2, relu4, conv5, relu5, conv6, relu6, conv7, relu8,
flatten, fc1,
output_layer]
secure_nn = SecureNnFramework("minionn_cifar10")
secure_nn.load_layers(layers)
return secure_nn