Added basic torch import functionality. Fixes #3

WIP #3. Added import tests

WIP #3 Added more test-cases

WIP #3 Added more tests

WIP #3. Fixed concat.lua test

WIP #3 minor changes

WIP #3 Fixed concat-parallel.lua

WIP #3 Added check-model helper

WIP #3 Added more tests for model checker

WIP #3 Added extra tests

WIP #3 Changed check-model to GraphChecker

WIP #3. multiple cases fail for ImportTorch...

WIP #3 Fixed ImportTorch batch test case running

WIP #3 Changed graph checker to use gme path for id

WIP #3 Updated tests

WIP #3. Tweaked to get all examples working locally w/ 'th'

WIP #3 Fixed tests

test/test-cases/code/basic4.lua

@@ -0,0 +1,27 @@
+require 'nn'
+
+local nfeats = 500
+local nstates = {}
+local filtsize = 10
+local poolsize = 10
+
+-- a typical modern convolution network (conv+relu+pool)
+model = nn.Sequential()
+
+-- stage 1 : filter bank -> squashing -> L2 pooling -> normalization
+model:add(nn.SpatialConvolutionMM(nfeats, nstates[1], filtsize, filtsize))
+model:add(nn.ReLU())
+model:add(nn.SpatialMaxPooling(poolsize,poolsize,poolsize,poolsize))
+
+-- stage 2 : filter bank -> squashing -> L2 pooling -> normalization
+model:add(nn.SpatialConvolutionMM(nstates[1], nstates[2], filtsize, filtsize))
+model:add(nn.ReLU())
+model:add(nn.SpatialMaxPooling(poolsize,poolsize,poolsize,poolsize))
+
+-- stage 3 : standard 2-layer neural network
+model:add(nn.View(nstates[2]*filtsize*filtsize))
+model:add(nn.Dropout(0.5))
+model:add(nn.Linear(nstates[2]*filtsize*filtsize, nstates[3]))
+model:add(nn.ReLU())
+model:add(nn.Linear(nstates[3], noutputs))
+