initial revamp of torch7 tree

1 files changed, 50 insertions, 0 deletions

diff --git a/SpatialConvolution.lua b/SpatialConvolution.lua
new file mode 100644
index 0000000..38d2737
--- /dev/null
+++ b/SpatialConvolution.lua
@@ -0,0 +1,50 @@
+local SpatialConvolution, parent = torch.class('nn.SpatialConvolution', 'nn.Module')
+
+function SpatialConvolution:__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(nOutputPlane, nInputPlane, kH, kW)
+   self.bias = torch.Tensor(nOutputPlane)
+   self.gradWeight = torch.Tensor(nOutputPlane, nInputPlane, kH, kW)
+   self.gradBias = torch.Tensor(nOutputPlane)
+   
+   self:reset()
+end
+
+function SpatialConvolution:reset(stdv)
+   if stdv then
+      stdv = stdv * math.sqrt(3)
+   else
+      stdv = 1/math.sqrt(self.kW*self.kH*self.nInputPlane)
+   end
+   self.weight:apply(function()
+                        return torch.uniform(-stdv, stdv)
+                     end)
+   self.bias:apply(function()
+                      return torch.uniform(-stdv, stdv)
+                   end)   
+end
+
+function SpatialConvolution:updateOutput(input)
+   return input.nn.SpatialConvolution_updateOutput(self, input)
+end
+
+function SpatialConvolution:updateGradInput(input, gradOutput)
+   if self.gradInput then
+      return input.nn.SpatialConvolution_updateGradInput(self, input, gradOutput)
+   end
+end
+
+function SpatialConvolution:accGradParameters(input, gradOutput, scale)
+   return input.nn.SpatialConvolution_accGradParameters(self, input, gradOutput, scale)
+end