Remove totem dependency (torch now has its own tester) (#124)

* Remove totem dependency (torch now has its own tester), fix contiguous grad

.travis.yml

@@ -44,7 +44,6 @@ before_script:
 - export CMAKE_LIBRARY_PATH=$HOME/OpenBlasInstall/include:$HOME/OpenBlasInstall/lib:$CMAKE_LIBRARY_PATH
 - cmake .. -DCMAKE_INSTALL_PREFIX="${INSTALL_PREFIX}" -DCMAKE_BUILD_TYPE=Release -DWITH_${TORCH_LUA_VERSION}=ON
 - make && make install
-- ${INSTALL_PREFIX}/bin/luarocks install totem
 - ${INSTALL_PREFIX}/bin/luarocks install trepl
 - ${INSTALL_PREFIX}/bin/luarocks install nn
 - git clone https://github.com/torch/xlua && cd xlua && ${INSTALL_PREFIX}/bin/luarocks make xlua-1.1-0.rockspec

autograd-scm-1.rockspec

@@ -13,7 +13,6 @@ description = {
 
 dependencies = {
    "torch >= 7.0",
-   "totem"
 }
 
 build = {

src/gradfuns.lua

@@ -228,15 +228,15 @@ operators.pow = {
 -- e.g. torch.view(x,3,3) and x:view(3,3)
 local viewGradients = {
    function(g, ans, x,sizes)
-      return torch.view(util.makeContiguous(g), torch.size(x))
+      return torch.view(torch.contiguous(g), torch.size(x))
    end
 }
 local viewAsGradients = {
    function(g, ans, x,template)
       return torch.clone(torch.viewAs(g,x))
    end,
    function(g, ans, x,template)
-      return nil -- g.new(template:size()):zero()
+      return nil
    end
 }
 local expandGradients = {
@@ -639,7 +639,6 @@ overload.module("util", util, function(module)
       function(g, ans, x, template, dim, index) return nil end,
       function(g, ans, x, template, dim, index) return nil end,
    })
-   module.gradient("makeContiguous", zeroGradient())
    module.gradient("cat", functions.catGradient)
    module.static("lt")
    module.static("le")

src/util.lua

@@ -227,13 +227,6 @@ function util.cat(x, y, dim)
    end
 end
 
-function util.makeContiguous(g)
-   if not g:isContiguous() then
-      g = g:contiguous()
-   end
-   return g
-end
-
 function util.defaultBool(b, db)
    if b == nil then
       return db

test/test.lua

@@ -1,10 +1,10 @@
 -- Tester:
-local totem = require 'totem'
+local torch = require 'torch'
 local autograd = require 'autograd'
 local util = require 'autograd.util'
 local gradcheck = require 'autograd.gradcheck' {randomizeInput = true}
 local gradcheckConstant = require 'autograd.gradcheck' {randomizeInput = false}
-local tester = totem.Tester()
+local tester = torch.Tester()
 local stringx = require 'pl.stringx'
 
 autograd.protected(true)
@@ -1696,25 +1696,47 @@ local tests = {
       end
       df = autograd(f)
       dparams, loss = df(params, 2)
+   end,
+
+   Contiguous = function()
+         -- Parameters:
+      local W = torch.Tensor(32,100):fill(.5)
+      local x = torch.Tensor(100):fill(.5)
+
+      -- Function:
+      local f1 = function(inputs)
+         return torch.sum(torch.contiguous(torch.contiguous(inputs.W)) * torch.contiguous(torch.contiguous(inputs.x)))
+      end
+
+      -- Tests:
+      tester:assert(gradcheck(f1,{W=torch.Tensor(32,100):fill(.5),x=torch.Tensor(100):fill(.5)}), "Incorrect gradient")
    end
 
 
 }
 
 local function prefixTests(pf, t, skip)
    local nt = { }
-   for k, v in pairs(t) do
-      if not skip[k] then
-         nt[pf .. k] = v
+   if type(t) == "table" then
+      for k, v in pairs(t) do
+         if not skip[k] then
+            nt[pf .. k] = v
+         end
       end
+   elseif type(t) == "string" then
+      nt = pf .. t
+   elseif type(t) == "nil" then
+      nt = nil
    end
    return nt
 end
 
+
 -- Run tests:
+print(prefixTests("Optimized_", tests, { }))
 autograd.optimize(true)
-tester:add(prefixTests("Optimized_", tests, { })):run()
+tester:add(prefixTests("Optimized_", tests, { })):run(prefixTests("Optimized_", arg[1]))
 autograd.optimize(false)
-tester = totem.Tester()
-tester:add(prefixTests("Direct_", tests, { GradGrad = true, AutoModule = true, DebuggerDivZero = true, StableGradients = true, ZeroGrad = true, SimpleGradGrad = true })):run()
+tester = torch.Tester()
+tester:add(prefixTests("Direct_", tests, { GradGrad = true, AutoModule = true, DebuggerDivZero = true, StableGradients = true, ZeroGrad = true, SimpleGradGrad = true })):run(arg[1])