require 'cunn';
torch.setdefaulttensortype('torch.FloatTensor')
cutorch.setDevice(2)
net = nn.Sequential()
net:add(nn.TemporalConvolution(16, 16, 17))
net = net:cuda()
input = torch.rand(120000, 16):cuda()local tic = torch.tic()
output = net:forward(input)
print( torch.toc(tic) )print( output:size() )