cuda_test.lua

require 'cutorch'
require 'cunn'

local function build_model()
   -- a CNN
   local model = nn.Sequential() 
   model:add(nn.SpatialConvolutionMM(3, 128, 5, 5, 1, 1))
   model:add(nn.ReLU())
   model:add(nn.SpatialMaxPooling(2, 2, 2, 2))
   model:add(nn.View(10 * 10 * 128))
   model:add(nn.Linear(10 * 10 * 128, 1024))
   model:add(nn.ReLU())
   model:add(nn.Dropout(0.5))
   model:add(nn.Linear(1024, 10))
   model:add(nn.LogSoftMax()) -- use nn.LogSoftMax(), LogSoftMax() == SoftMax():log(), LogSoftMax():exp() = SoftMax()
   
   return model
end
local function cuda_test()
   local model = build_model():cuda()
   local criterion = nn.ClassNLLCriterion():cuda()
   local x = torch.Tensor(64, 3, 24, 24):uniform():cuda() -- input tensor (batch, depth, height, width)
   local y = torch.Tensor(64):random(1, 10):cuda() -- labels (array of class id)
   -- batch forward
   local z = model:forward(x)
   local err = criterion:forward(z, y)
   -- batch backward
   model:backward(x, criterion:backward(z, y))
   print("CUDA Test Successful!")
end
torch.setdefaulttensortype('torch.FloatTensor')
cuda_test()