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authorClement Farabet <clement.farabet@gmail.com>2013-03-20 07:23:43 +0400
committerClement Farabet <clement.farabet@gmail.com>2013-03-20 07:23:43 +0400
commit01de69c383f08abaf867fef008294dee4c56bf2d (patch)
treeef9100ac253c1d01886ddf169b238355dd6465e1
parentedf13338e79ec336b5d5fb0b7f95fc8864f747cc (diff)
Integrated CUDA conv routines from cuda-convnet library.
-rw-r--r--SpatialConvolutionCUDA.lua50
-rw-r--r--Transpose.lua29
-rw-r--r--init.lua2
3 files changed, 81 insertions, 0 deletions
diff --git a/SpatialConvolutionCUDA.lua b/SpatialConvolutionCUDA.lua
new file mode 100644
index 0000000..ccc0284
--- /dev/null
+++ b/SpatialConvolutionCUDA.lua
@@ -0,0 +1,50 @@
+local SpatialConvolutionCUDA, parent = torch.class('nn.SpatialConvolutionCUDA', 'nn.Module')
+
+function SpatialConvolutionCUDA:__init(nInputPlane, nOutputPlane, kW, kH, dW, dH)
+ parent.__init(self)
+
+ dW = dW or 1
+ dH = dH or 1
+
+ self.nInputPlane = nInputPlane
+ self.nOutputPlane = nOutputPlane
+ self.kW = kW
+ self.kH = kH
+ self.dW = dW
+ self.dH = dH
+
+ self.weight = torch.Tensor(nInputPlane, kH, kW, nOutputPlane)
+ self.gradWeight = torch.Tensor(nInputPlane, kH, kW, nOutputPlane)
+
+ self:reset()
+end
+
+function SpatialConvolutionCUDA:reset(stdv)
+ if stdv then
+ stdv = stdv * math.sqrt(3)
+ else
+ stdv = 1/math.sqrt(self.kW*self.kH*self.nInputPlane)
+ end
+ self.weight:uniform(-stdv, stdv)
+end
+
+function SpatialConvolutionCUDA:updateOutput(input)
+ return input.nn.SpatialConvolutionCUDA_updateOutput(self, input)
+end
+
+function SpatialConvolutionCUDA:updateGradInput(input, gradOutput)
+ return input.nn.SpatialConvolutionCUDA_updateGradInput(self, input, gradOutput)
+end
+
+function SpatialConvolutionCUDA:accGradParameters(input, gradOutput, scale)
+ return input.nn.SpatialConvolutionCUDA_accGradParameters(self, input, gradOutput, scale)
+end
+
+function SpatialConvolutionCUDA:copy(sc)
+ local weight = sc.weight:clone()
+ weight:resize(sc.nOutputPlane, sc.nInputPlane * sc.kH * sc.kW)
+ weight = weight:t():contiguous()
+ weight:resize(sc.nInputPlane, sc.kH, sc.kW, sc.nOutputPlane)
+ self.weight:copy(weight)
+end
+
diff --git a/Transpose.lua b/Transpose.lua
new file mode 100644
index 0000000..a43729b
--- /dev/null
+++ b/Transpose.lua
@@ -0,0 +1,29 @@
+local Transpose, parent = torch.class('nn.Transpose', 'nn.Module')
+
+-- transpose dimensions:
+-- n = nn.Transpose({1,4},{1,3})
+-- will transpose dims 1 and 4, then 1 and 3...
+
+function Transpose:__init(...)
+ parent.__init(self)
+ self.permutations = {...}
+end
+
+function Transpose:updateOutput(input)
+ for _,perm in ipairs(self.permutations) do
+ input = input:transpose(perm[1],perm[2])
+ end
+ self.output:resizeAs(input):copy(input)
+ return self.output
+end
+
+function Transpose:updateGradInput(input, gradOutput)
+ local ndim = gradOutput:nDimension()
+ for i = #self.permutations,1,-1 do
+ local perm = self.permutations[i]
+ gradOutput = gradOutput:transpose(perm[1],perm[2])
+ end
+ self.gradInput:resizeAs(gradOutput):copy(gradOutput)
+ return self.gradInput
+end
+
diff --git a/init.lua b/init.lua
index 587412f..c6e9df9 100644
--- a/init.lua
+++ b/init.lua
@@ -13,6 +13,7 @@ include('Reshape.lua')
include('Select.lua')
include('Narrow.lua')
include('Replicate.lua')
+include('Transpose.lua')
include('Copy.lua')
include('Min.lua')
@@ -59,6 +60,7 @@ include('SpatialConvolution.lua')
include('SpatialFullConvolution.lua')
include('SpatialFullConvolutionMap.lua')
include('SpatialConvolutionMM.lua')
+include('SpatialConvolutionCUDA.lua')
include('SpatialConvolutionMap.lua')
include('SpatialSubSampling.lua')
include('SpatialMaxPooling.lua')