from __future__ import print_function
from cifar10cnn import cifar10cnnnet
import numpy as np
import matplotlib.pyplot as plt
from utils import progress_bar
import pickle
tradeoff = 0.1
tradeoff2 = 0.1
weight_decay = 0
dropout_keep_prob = 0.75
model = cifar10cnnnet(minibatchsize=64,
learningrate=0.1,
tradeoff=tradeoff,
tradeoff2=tradeoff2,
momentum=0.1,
weight_decay=weight_decay,
dropout_keep_prob=dropout_keep_prob,
decay=1e-6)
model.buildnet()
model.loaddata()
model.init_net()
model.data_mode(1)
model.train_mode(1)
epoch = 0
from __future__ import print_function
from cifar10cnn import cifar10cnnnet
import numpy as np
import matplotlib.pyplot as plt
from utils import progress_bar
import pickle
tradeoff = 0.01
tradeoff2 = 1
model = cifar10cnnnet(minibatchsize=128,
learningrate=0.01,
tradeoff=tradeoff,
tradeoff2=tradeoff2,
momentum=0.9,
decay=0)
model.buildnet()
model.loaddata()
model.init_net()
model.data_mode(1)
model.train_mode(2)
epoch = 0
train_acc = []
train_meanloss = []
from __future__ import print_function
from cifar10cnn import cifar10cnnnet
import numpy as np
import matplotlib.pyplot as plt
from utils import progress_bar
import pickle
tradeoff = 0
tradeoff2 = 0
weight_decay = 5e-4
momentum = 0.9
model = cifar10cnnnet(minibatchsize=128,
learningrate=0.1,
tradeoff=tradeoff,
tradeoff2=tradeoff2,
weight_decay=weight_decay,
momentum=momentum,
decay=0)
model.buildnet()
model.loaddata()
model.init_net()
model.data_mode(1)
model.train_mode(2)
epoch = 0
