from src.cnn_builder import Layer DROPOUT_PROB = 0.6 NETWORK_STRUCTURE = [ Layer("conv", [3, 3, 3, 64]), Layer("conv", [3, 3, 64, 64]), Layer("pool", []), Layer("conv", [3, 3, 64, 128]), Layer("conv", [3, 3, 128, 128]), Layer("pool", []), Layer("conv", [3, 3, 128, 256]), Layer("conv", [3, 3, 256, 256]), Layer("conv", [3, 3, 256, 256]), Layer("pool", []), Layer("conv", [3, 3, 256, 512]), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("pool", []), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("dense", [2 * 2 * 512, 4096]), Layer("dense", [4096, 4096]), Layer("dense", [4096, 10]) ] NETWORK_ANCHOR = -4 NETWORK_PATH = "model/cifar/model_4.ckpt" INIT = 0.0 LEARNING_RATE = 1e-4 DISTRIBUTION_PATH = "profile/cifar/model4VGG_mdist_distribution.pkl"
from src.cnn_builder import Layer DROPOUT_PROB = 0.6 NETWORK_STRUCTURE = [ Layer("conv", [3, 3, 3, 64]), Layer("conv", [3, 3, 64, 64]), Layer("pool", []), Layer("conv", [3, 3, 64, 128]), Layer("conv", [3, 3, 128, 128]), Layer("pool", []), Layer("conv", [3, 3, 128, 256]), Layer("conv", [3, 3, 256, 256]), Layer("conv", [3, 3, 256, 256]), Layer("pool", []), Layer("conv", [3, 3, 256, 512]), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("pool", []), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("conv", [3, 3, 512, 512]), Layer("dense", [2 * 2 * 512, 4096]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [4096, 4096]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [4096, 10]) ] NETWORK_ANCHOR = -4 NETWORK_PATH = "model/cifar/model_2.ckpt" INIT = 0.0 LEARNING_RATE = 1e-4
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("conv", [5, 5, 3, 32]), Layer("pool", []), Layer("conv", [5, 5, 32, 64]), Layer("pool", []), Layer("dense", [8 * 8 * 64, 1024]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [1024, 10]) ] NETWORK_ANCHOR = -2 NETWORK_PATH = "model/cifar/model_1.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-3
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("dense", [28 * 28 * 1, 1024]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [1024, 10]) ] NETWORK_ANCHOR = -2 NETWORK_PATH = "model/mnist/model_3.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-2 DISTRIBUTION_PATH = "profile/mnist/model3_mdist_distribution.pkl"
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("conv", [5, 5, 1, 16]), Layer("pool", []), Layer("dense", [14 * 14 * 16, 1024]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [1024, 10]) ] NETWORK_ANCHOR = -4 NETWORK_PATH = "model/mnist/model_2.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-3 DISTRIBUTION_PATH = "profile/mnist/model2_mdist_distribution.pkl"
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("conv", [3, 3, 1, 32]), Layer("conv", [3, 3, 32, 32]), Layer("pool", []), Layer("conv", [3, 3, 32, 64]), Layer("conv", [3, 3, 64, 64]), Layer("pool", []), Layer("dense", [7 * 7 * 64, 200]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [200, 200]), Layer("dense", [200, 10]) ] NETWORK_ANCHOR = -2 NETWORK_PATH = "model/mnist/model_4.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-3 DISTRIBUTION_PATH = "profile/mnist/model4_mdist_distribution.pkl"
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("dense", [28 * 28 * 1, 256]), Layer("dropout", [DROPOUT_PROB]), Layer("dense", [256, 10]) ] NETWORK_ANCHOR = -2 NETWORK_PATH = "model/mnist/model_3.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-2 DISTRIBUTION_PATH = "profile/mnist/model3_mdist_distribution.pkl"
from src.cnn_builder import Layer DROPOUT_PROB = 1 NETWORK_STRUCTURE = [ Layer("conv", [3, 3, 1, 32]), Layer("conv", [3, 3, 32, 32]), Layer("pool", []), Layer("conv", [3, 3, 32, 64]), Layer("conv", [3, 3, 64, 64]), Layer("pool", []), Layer("dense", [7 * 7 * 64, 200]), Layer("dense", [200, 200]), Layer("dense", [200, 3]) ] NETWORK_ANCHOR = -2 NETWORK_PATH = "model/mnist/model_6.ckpt" INIT = 1e-1 LEARNING_RATE = 1e-3 DISTRIBUTION_PATH = "profile/mnist/model6_mdist_distribution.pkl"