--- a
+++ b/code/trainDNN.lua
@@ -0,0 +1,76 @@
+require 'torch';
+require 'nn';
+require 'optim';
+
+--cudaFlag = true
+cudaFlag = true
+
+if cudaFlag then
+	require 'cutorch';
+	require 'cunn';
+end
+
+-- parameters
+local batchSize = 200		-- batch size is approximate; actual batchSizes will vary by +/- N-1, where N is the number of classes
+local learningRate = 0.05
+local learningRateDecay = 0.0005
+local weightDecay = 0.000
+local momentum = 0.9
+local maxIteration = 20
+local augment = true
+
+local trainFolder = '/home/andrew/mitosis/data/mitosis-train-large/'
+local testFolder = '/home/andrew/mitosis/data/mitosis-test/'
+
+dofile("data.lua")
+
+local classes, trainClassList, trainImagePaths = getImagePaths(trainFolder)
+local classes, testClassList, testImagePaths = getImagePaths(testFolder)
+
+
+local classRatio = trainClassList[2]:size(1)/trainClassList[1]:size(1)
+local weights = torch.Tensor(2)
+weights[1] = classRatio
+weights[2] = 1
+
+--[
+-- first network
+-- define the model
+dofile("/home/andrew/mitosis/models/model1.lua")
+local net, criterion = model1(weights)
+if cudaFlag then
+	net = net:cuda()
+	criterion = criterion:cuda()
+end
+
+-- train the network
+dofile("train.lua")
+--net = torch.load('/home/andrew/mitosis/data/nets/dnn1_halfset_aug_20i_lr001.t7')
+--train(net, criterion, classes, trainClassList, imagePaths, batchSize, learningRate, maxIteration)
+--torch.save('/home/andrew/mitosis/data/nets/dnn1_fullset_aug_30i_lr05_mini200.t7', net)
+
+-- test the network
+dofile("test.lua")
+--test(classes, testClassList, imagePaths, batchSize, maxIteration)
+--]]
+
+
+-- second network
+-- define the model
+dofile("/home/andrew/mitosis/models/model2.lua")
+local net, criterion = model2(weights)
+if cudaFlag then
+	net = net:cuda()
+	criterion = criterion:cuda()
+end
+
+-- train the network
+dofile("train.lua")
+net = torch.load('/home/andrew/mitosis/data/nets/model2-pretrained-greedylayerwise2.t7')
+train(net, criterion, classes, trainClassList, trainImagePaths, batchSize, learningRate, learningRateDecay, weightDecay, momentum, maxIteration, classRatio, augment, netFolder)
+torch.save('/home/andrew/mitosis/data/nets/dnn2_fullset_aug_20i_lr05_lrd0005_m09_mini200_aeptgl.t7', net)
+
+-- test the network
+dofile("test.lua")
+--net = torch.load('/home/andrew/mitosis/data/nets/dnn2_fullset_aug_20i_lr05_mini200_aept.t7')
+test(net, classes, testClassList, testImagePaths, batchSize)