Revamped workspace handling in find.lua

Retired functional.lua: impossible to maintain consistently with Find.
Simplified FindEx state machine: replaced witgh warmup iterations concept, controllable by user.
FindEx still needs some work.
Improved cache handling and debug print

1 files changed, 11 insertions, 14 deletions

diff --git a/SpatialConvolution.lua b/SpatialConvolution.lua
index f2ab112..512e7c2 100644
--- a/SpatialConvolution.lua
+++ b/SpatialConvolution.lua
@@ -126,12 +126,12 @@ function SpatialConvolution:createIODescriptors(input)
         self.convDesc = cudnn.createDescriptors(1, 'struct cudnnConvolutionStruct*[?]',
                                                 'cudnnCreateConvolutionDescriptor', 'cudnnDestroyConvolutionDescriptor')
         self.padH, self.padW = self.padH or 0, self.padW or 0
-        local pad = torch.IntTensor({self.padH, self.padW})
-        local stride = torch.IntTensor({self.dH, self.dW})
+        self.pad = torch.IntTensor({self.padH, self.padW})
+        self.stride = torch.IntTensor({self.dH, self.dW})
         local upscale = torch.IntTensor({1,1})
         errcheck(self,'cudnnSetConvolutionNdDescriptor', self.convDesc[0],
-                 2, pad:data(),
-                 stride:data(), upscale:data(), 'CUDNN_CROSS_CORRELATION',
+                 2, self.pad:data(),
+                 self.stride:data(), upscale:data(), 'CUDNN_CROSS_CORRELATION',
                  cudnn.configmap(torch.type(self.weight)));
 
 
@@ -188,9 +188,8 @@ function SpatialConvolution:updateOutput(input)
     self:createIODescriptors(input)
     local finder = find.get()
     -- force recalculation
-    if not (self.fmode and finder.useCalculatedWorkspaceSize) then
-       self.fmode = finder:forwardAlgorithm(self, { self.iDesc[0], self.input_slice, self.weightDesc[0], self.weight, self.convDesc[0], self.oDesc[0], self.output_slice})
-    end
+    self.fmode = finder:forwardAlgorithm(self, { self.iDesc[0], self.input_slice, self.weightDesc[0], self.weight, self.convDesc[0], self.oDesc[0], self.output_slice})
+    finder:setCalculatedWorkspaceSize(true)
     local extraBuffer, extraBufferSize = cudnn.getSharedWorkspace()
     for g = 0, self.groups - 1 do
         errcheck(self,'cudnnConvolutionForward', cudnn.getHandle(),
@@ -221,9 +220,8 @@ function SpatialConvolution:updateGradInput(input, gradOutput)
     input, gradOutput = makeContiguous(self, input, gradOutput)
     self:createIODescriptors(input)
     local finder = find.get()
-    if not (finder.useCalculatedWorkspaceSize and self.bdmode) then
-       self.bdmode = finder:backwardDataAlgorithm(self, { self.weightDesc[0], self.weight, self.oDesc[0], self.output_slice, self.convDesc[0], self.iDesc[0], self.input_slice })
-    end
+    self.bdmode = finder:backwardDataAlgorithm(self, { self.weightDesc[0], self.weight, self.oDesc[0], self.output_slice, self.convDesc[0], self.iDesc[0], self.input_slice })
+    finder:setCalculatedWorkspaceSize(true)
     local extraBuffer, extraBufferSize = cudnn.getSharedWorkspace()
     for g = 0,self.groups - 1 do
         errcheck(self,'cudnnConvolutionBackwardData', cudnn.getHandle(),
@@ -249,10 +247,8 @@ function SpatialConvolution:accGradParameters(input, gradOutput, scale)
     input, gradOutput = makeContiguous(self, input, gradOutput)
     self:createIODescriptors(input)
     local finder = find.get()
-    if not (finder.useCalculatedWorkspaceSize and self.bmode) then
-       self.bmode=finder:backwardFilterAlgorithm(self, { self.iDesc[0], self.input_slice, self.oDesc[0], self.output_slice, self.convDesc[0], self.weightDesc[0], self.weight})
-    end
-
+    self.bmode=finder:backwardFilterAlgorithm(self, { self.iDesc[0], self.input_slice, self.oDesc[0], self.output_slice, self.convDesc[0], self.weightDesc[0], self.weight})
+    finder:setCalculatedWorkspaceSize(true)
     -- gradBias
     if self.bias then
         errcheck(self,'cudnnConvolutionBackwardBias', cudnn.getHandle(),
@@ -261,6 +257,7 @@ function SpatialConvolution:accGradParameters(input, gradOutput, scale)
                  cudnn.scalar(input, 1),
                  self.biasDesc[0], self.gradBias:data())
     end
+    finder:setCalculatedWorkspaceSize(true)
     local extraBuffer, extraBufferSize = cudnn.getSharedWorkspace()
     for g = 0, self.groups - 1 do
         -- gradWeight