Add simple Torch network profiling script.

util/profile-network.lua

@@ -0,0 +1,49 @@
+#!/usr/bin/env th
+--
+-- Outputs the number of parameters in a network for a single image
+-- in evaluation mode.
+
+require 'torch'
+require 'nn'
+require 'dpnn'
+
+torch.setdefaulttensortype('torch.FloatTensor')
+
+local cmd = torch.CmdLine()
+cmd:text()
+cmd:text('Network Size.')
+cmd:text()
+cmd:text('Options:')
+
+cmd:option('-model', './models/openface/nn4.v1.t7', 'Path to model.')
+cmd:option('-imgDim', 96, 'Image dimension. nn1=224, nn4=96')
+cmd:option('-numIter', 50)
+cmd:option('-cuda', false)
+cmd:text()
+
+opt = cmd:parse(arg or {})
+-- print(opt)
+
+net = torch.load(opt.model):float()
+net:evaluate()
+-- print(net)
+
+local img = torch.randn(opt.numIter, 1, 3, opt.imgDim, opt.imgDim)
+
+if opt.cuda then
+   require 'cutorch'
+   require 'cunn'
+   net = net:cuda()
+   img = img:cuda()
+end
+
+times = torch.Tensor(opt.numIter)
+
+for i=1,opt.numIter do
+   timer = torch.Timer()
+   rep = net:forward(img[i])
+   times[i] = 1000.0*timer:time().real
+end
+
+print(string.format('Single image forward pass: %.2f ms +/- %.2f ms',
+                    torch.mean(times), torch.std(times)))