8 local model = nn.Sequential()
9 model:add(nn.Linear(1000, 1000))
11 model:add(nn.Linear(1000, 100))
15 local input = torch.Tensor(1000, 1000)
16 local target = torch.Tensor(input:size(1), 100)
17 local criterion = nn.MSECriterion()
24 local t1 = sys.clock()
28 local t2 = sys.clock()
30 local output = model:forward(input)
31 local loss = criterion:forward(output, target)
32 local dloss = criterion:backward(output, target)
33 model:backward(input, dloss)
35 local t3 = sys.clock()
37 dataTime = dataTime + (t2 - t1)
38 modelTime = modelTime + (t3 - t2)
40 nbSamples = nbSamples + input:size(1)
43 profiler.print(model, nbSamples)
45 print('----------------------------------------------------------------------')
46 print(string.format('Total model time %.02fs', modelTime))
47 print(string.format('Total data time %.02fs', dataTime))