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authorRonan Collobert <ronan@collobert.com>2012-01-25 17:55:20 +0400
committerRonan Collobert <ronan@collobert.com>2012-01-25 17:55:20 +0400
commit4df3893abd1b9f840f1d9a8c1859799ccbf941de (patch)
treee8a1e1cc1b6ea6e47855347b157eaf419fdb357b /SpatialSubSampling.lua
initial revamp of torch7 tree
Diffstat (limited to 'SpatialSubSampling.lua')
-rw-r--r--SpatialSubSampling.lua49
1 files changed, 49 insertions, 0 deletions
diff --git a/SpatialSubSampling.lua b/SpatialSubSampling.lua
new file mode 100644
index 0000000..48b32b9
--- /dev/null
+++ b/SpatialSubSampling.lua
@@ -0,0 +1,49 @@
+local SpatialSubSampling, parent = torch.class('nn.SpatialSubSampling', 'nn.Module')
+
+function SpatialSubSampling:__init(nInputPlane, kW, kH, dW, dH)
+ parent.__init(self)
+
+ dW = dW or 1
+ dH = dH or 1
+
+ self.nInputPlane = nInputPlane
+ self.kW = kW
+ self.kH = kH
+ self.dW = dW
+ self.dH = dH
+
+ self.weight = torch.Tensor(nInputPlane)
+ self.bias = torch.Tensor(nInputPlane)
+ self.gradWeight = torch.Tensor(nInputPlane)
+ self.gradBias = torch.Tensor(nInputPlane)
+
+ self:reset()
+end
+
+function SpatialSubSampling:reset(stdv)
+ if stdv then
+ stdv = stdv * math.sqrt(3)
+ else
+ stdv = 1/math.sqrt(self.kW*self.kH)
+ end
+ self.weight:apply(function()
+ return torch.uniform(-stdv, stdv)
+ end)
+ self.bias:apply(function()
+ return torch.uniform(-stdv, stdv)
+ end)
+end
+
+function SpatialSubSampling:updateOutput(input)
+ return input.nn.SpatialSubSampling_updateOutput(self, input)
+end
+
+function SpatialSubSampling:updateGradInput(input, gradOutput)
+ if self.gradInput then
+ return input.nn.SpatialSubSampling_updateGradInput(self, input, gradOutput)
+ end
+end
+
+function SpatialSubSampling:accGradParameters(input, gradOutput, scale)
+ return input.nn.SpatialSubSampling_accGradParameters(self, input, gradOutput, scale)
+end