full conv tests

3 files changed, 100 insertions, 5 deletions

diff --git a/SpatialFullConvolution.lua b/SpatialFullConvolution.lua
index d736e26..d00a8a2 100644
--- a/SpatialFullConvolution.lua
+++ b/SpatialFullConvolution.lua
@@ -8,11 +8,6 @@ autotunerCache[1] = {} -- forward
 autotunerCache[2] = {} -- backwardFilter
 autotunerCache[3] = {} -- backwardData
 
-function SpatialFullConvolution:__init(nInputPlane, nOutputPlane,
-                                       kW, kH, dW, dH, padW, padH, adjW, adjH)
-    parent.__init(self, nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH, adjW, adjH)
-end
-
 -- if you change the configuration of the module manually, call this
 function SpatialFullConvolution:resetWeightDescriptors()
     assert(torch.typename(self.weight) == 'torch.CudaTensor',
@@ -40,6 +35,7 @@ end
 function SpatialFullConvolution:fastest(mode)
     if mode == nil then mode = true end
     self.fastest_mode = mode
+    self.iSize = self.iSize or torch.LongStorage(4)
     self.iSize:fill(0)
     return self
 end
@@ -54,6 +50,7 @@ function SpatialFullConvolution:setMode(fmode, bdmode, bwmode)
     if bwmode ~= nil then
         self.bwmode = bwmode
     end
+    self.iSize = self.iSize or torch.LongStorage(4)
     self.iSize:fill(0)
     return self
 end
@@ -72,6 +69,7 @@ function SpatialFullConvolution:createIODescriptors(input)
         batch = false
     end
     assert(input:dim() == 4 and input:isContiguous());
+    self.iSize = self.iSize or torch.LongStorage(4):fill(0)
     if not self.iDesc or not self.oDesc or
         input:size(1) ~= self.iSize[1] or input:size(2) ~= self.iSize[2]
     or input:size(3) ~= self.iSize[3] or input:size(4) ~= self.iSize[4] then
diff --git a/convert.lua b/convert.lua
index 7b51ae5..aa8c65f 100644
--- a/convert.lua
+++ b/convert.lua
@@ -2,6 +2,7 @@
 local layer_list = {
   'SpatialConvolution',
   'SpatialCrossMapLRN',
+  'SpatialFullConvolution',
   'SpatialMaxPooling',
   'SpatialAveragePooling',
   'ReLU',
diff --git a/test/test.lua b/test/test.lua
index 388deb3..55171c7 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -206,6 +206,102 @@ function cudnntest.SpatialConvolution_backward_single()
   test(sconv, gconv)
 end
 
+function cudnntest.SpatialFullConvolution_forward_batch()
+   local bs = math.random(1,32)
+   local from = math.random(1,32)
+   local to = math.random(1,64)
+   local ki = math.random(1,15)
+   local kj = math.random(1,15)
+   local si = math.random(1,ki)
+   local sj = math.random(1,kj)
+   local outi = math.random(1,64)
+   local outj = math.random(1,64)
+   local ini = (outi-1)*si+ki
+   local inj = (outj-1)*sj+kj
+
+   local input = torch.randn(bs,from,inj,ini):cuda()
+   local sconv = nn.SpatialFullConvolution(from,to,ki,kj,si,sj):cuda()
+   local gconv = cudnn.SpatialFullConvolution(from,to,ki,kj,si,sj):cuda():fastest()
+   gconv.weight:copy(sconv.weight)
+   gconv.bias:copy(sconv.bias)
+
+   local function test(sconv, gconv)
+     local groundtruth = sconv:forward(input)
+     cutorch.synchronize()
+     local rescuda = gconv:forward(input)
+     cutorch.synchronize()
+     local error = rescuda:float() - groundtruth:float()
+     mytester:assertlt(error:abs():max(), precision_forward, 'error on state (forward) ')
+
+     -- IO
+     local ferr,berr = jac.testIO(gconv, input)
+     mytester:assertlt(ferr, precision_io, torch.typename(gconv) .. ' - i/o forward err ')
+     mytester:assertlt(berr, precision_io, torch.typename(gconv) .. ' - i/o backward err ')
+   end
+
+   test(sconv, gconv)
+   local gconv = cudnn.convert(sconv, cudnn)
+   mytester:asserteq(torch.typename(gconv), 'cudnn.SpatialFullConvolution', 'conversion type check')
+   test(sconv, gconv)
+end
+
+function cudnntest.SpatialFullConvolution_backward_batch()
+   local bs = math.random(1,32)
+   local from = math.random(1,32)
+   local to = math.random(1,64)
+   local ki = math.random(1,15)
+   local kj = math.random(1,15)
+   local si = math.random(1,ki)
+   local sj = math.random(1,kj)
+   local outi = math.random(1,64)
+   local outj = math.random(1,64)
+   local ini = (outi-1)*si+ki
+   local inj = (outj-1)*sj+kj
+   local scale = math.random()
+
+   local input = torch.randn(bs,from,inj,ini):cuda()
+   local gradOutput = torch.randn(bs,to,outj,outi):cuda()
+   local sconv = nn.SpatialFullConvolution(from,to,ki,kj,si,sj):cuda()
+   sconv:forward(input)
+   sconv:zeroGradParameters()
+   local groundgrad = sconv:backward(input, gradOutput, scale)
+   cutorch.synchronize()
+   local groundweight = sconv.gradWeight
+   local groundbias = sconv.gradBias
+
+   local gconv = cudnn.SpatialFullConvolution(from,to,ki,kj,si,sj):cuda():fastest()
+   gconv.weight:copy(sconv.weight)
+   gconv.bias:copy(sconv.bias)
+   gconv:forward(input)
+
+   -- serialize and deserialize
+   torch.save('modelTemp.t7', gconv)
+   gconv = torch.load('modelTemp.t7')
+
+   local function test(sconv, gconv)
+     gconv:forward(input)
+     gconv:zeroGradParameters()
+     local rescuda = gconv:backward(input, gradOutput, scale)
+     cutorch.synchronize()
+     local weightcuda = gconv.gradWeight
+     local biascuda = gconv.gradBias
+
+     local error = rescuda:float() - groundgrad:float()
+     local werror = weightcuda:float() - groundweight:float()
+     local berror = biascuda:float() - groundbias:float()
+
+     mytester:assertlt(error:abs():max(), precision_backward, 'error on state (backward) ')
+     mytester:assertlt(werror:abs():max(), precision_backward, 'error on weight (backward) ')
+     mytester:assertlt(berror:abs():max(), precision_backward, 'error on bias (backward) ')
+   end
+
+   test(sconv, gconv)
+   local gconv = cudnn.convert(sconv, cudnn)
+   mytester:asserteq(torch.typename(gconv), 'cudnn.SpatialFullConvolution', 'conversion type check')
+   test(sconv, gconv)
+end
+
+
 function cudnntest.TemporalConvolution_batch()
    local bs = math.random(1,32)
    local inputFrameSize = math.random(1,64)