isolated 1x1 conv tests

1 files changed, 96 insertions, 0 deletions

diff --git a/test/test_1x1conv.lua b/test/test_1x1conv.lua
new file mode 100644
index 0000000..8400621
--- /dev/null
+++ b/test/test_1x1conv.lua
@@ -0,0 +1,96 @@
+require 'cudnn'
+require 'cunn'
+
+local cudnntest = {}
+local precision_forward = 1e-4
+local precision_backward = 1e-2
+local precision_jac = 1e-3
+local nloop = 1
+local times = {}
+local mytester
+
+
+function cudnntest.SpatialConvolution_forward_batch()
+   local bs = math.random(1,32)
+   local from = math.random(1,32)
+   local to = math.random(1,64)
+   local ki =1--  math.random(1,1)
+   local kj = 1-- math.random(1,1)
+   local si = 1 -- not supported by CPU version yet
+   local sj = si
+   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.SpatialConvolutionMM(from,to,ki,kj,si,sj):cuda()
+   local groundtruth = sconv:forward(input)
+   cutorch.synchronize()
+   local gconv = cudnn.SpatialConvolution(from,to,ki,kj,si,sj):cuda()
+   gconv.weight:copy(sconv.weight)
+   gconv.bias:copy(sconv.bias)
+   local rescuda = gconv:forward(input)
+   cutorch.synchronize()
+   local error = rescuda:float() - groundtruth:float()
+   mytester:assertlt(error:abs():max(), precision_forward, 'error on state (forward) ')
+end
+
+
+function cudnntest.SpatialConvolution_backward_batch()
+   local bs = math.random(1,32)
+   local from = math.random(1,32)
+   local to = math.random(1,64)
+   local ki = 1-- math.random(1,1)
+   local kj = 1-- math.random(1,1)
+   local si = 1 -- not supported by CPU version yet
+   local sj = si
+   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 gradOutput = torch.randn(bs,to,outj,outi):cuda()
+   local sconv = nn.SpatialConvolutionMM(from,to,ki,kj,si,sj):cuda()
+   sconv:forward(input)
+   sconv:zeroGradParameters()
+   local groundgrad = sconv:backward(input, gradOutput)
+   cutorch.synchronize()
+   local groundweight = sconv.gradWeight
+   local groundbias = sconv.gradBias
+
+   local gconv = cudnn.SpatialConvolution(from,to,ki,kj,si,sj):cuda()
+   gconv.weight:copy(sconv.weight)
+   gconv.bias:copy(sconv.bias)
+   gconv:forward(input)
+
+
+   gconv:forward(input)
+   gconv:zeroGradParameters()
+   local rescuda = gconv:backward(input, gradOutput)
+   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
+
+torch.setdefaulttensortype('torch.FloatTensor')
+math.randomseed(os.time())
+mytester = torch.Tester()
+mytester:add(cudnntest)
+
+for i=1,cutorch.getDeviceCount() do
+   print('Running test on device: ' .. i)
+   cutorch.setDevice(i)
+   mytester:run(tests)
+end
+
+os.execute('rm -f modelTemp.t7')