diff options
| author | Sergey Zagoruyko <zagoruyko2@gmail.com> | 2016-04-13 16:01:55 +0300 |
|---|---|---|
| committer | Sergey Zagoruyko <zagoruyko2@gmail.com> | 2016-04-13 19:01:48 +0300 |
| commit | 70adafcae259f67129c2de6e1048594aa0283e59 (patch) | |
| tree | 432358dc7274ec86132e2c3bb40b655b0f4a4f61 /SpatialConvolution.lua | |
| parent | 0a040cf2bb3d0f0cdf217c8e92efaddf29ed2efc (diff) | |
R5 rebase
Diffstat (limited to 'SpatialConvolution.lua')
| -rw-r--r-- | SpatialConvolution.lua | 18 |
1 files changed, 12 insertions, 6 deletions
diff --git a/SpatialConvolution.lua b/SpatialConvolution.lua index 20f31ef..b92dd57 100644 --- a/SpatialConvolution.lua +++ b/SpatialConvolution.lua @@ -43,7 +43,7 @@ function SpatialConvolution:resetWeightDescriptors() self.nInputPlane/self.groups, self.kH, self.kW}) errcheck('cudnnSetFilterNdDescriptor', self.weightDesc[0], - 'CUDNN_DATA_FLOAT', 4, + 'CUDNN_DATA_FLOAT', 'CUDNN_TENSOR_NCHW', 4, desc:data()); local function destroyWDesc(d) errcheck('cudnnDestroyFilterDescriptor', d[0]); @@ -122,7 +122,7 @@ function SpatialConvolution:createIODescriptors(input) local pad = torch.IntTensor({self.padH, self.padW}) local stride = torch.IntTensor({self.dH, self.dW}) local upscale = torch.IntTensor({1,1}) - errcheck('cudnnSetConvolutionNdDescriptor_v3', self.convDesc[0], + errcheck('cudnnSetConvolutionNdDescriptor', self.convDesc[0], 2, pad:data(), stride:data(), upscale:data(), 'CUDNN_CROSS_CORRELATION', 'CUDNN_DATA_FLOAT'); @@ -177,7 +177,7 @@ function SpatialConvolution:createIODescriptors(input) if autotunerCache[1][autotunerHash] then algType[0] = autotunerCache[1][autotunerHash] if cudnn.verbose then - print('Using cached benchmark for: ', autotunerHash) + print('Autotuning SC FW: using cached algo = ', algType[0], ' for: ', autotunerHash) end else local perfResults = ffi.new("cudnnConvolutionFwdAlgoPerf_t[?]", 1) @@ -191,7 +191,7 @@ function SpatialConvolution:createIODescriptors(input) autotunerCache[1][autotunerHash] = perfResults[0].algo if cudnn.verbose then print(string.format( - "Autotuning Forward: Time: %3.5f Memory: %8d Algorithm: %d" + "\nAutotuning SC Forward: Time: %3.5f Memory: %8d Algorithm: %d" .. " Weight: %15s Input: %15s Output: %15s", perfResults[0].time, tonumber(perfResults[0].memory), tonumber(perfResults[0].algo), @@ -228,6 +228,9 @@ function SpatialConvolution:createIODescriptors(input) if cudnn.benchmark then -- the manual auto-tuner is run if autotunerCache[2][autotunerHash] then algType[0] = autotunerCache[2][autotunerHash] + if cudnn.verbose then + print('Autotuning SC BW: using cached algo = ', algType[0], ' for: ', autotunerHash) + end else local perfResults = ffi.new("cudnnConvolutionBwdFilterAlgoPerf_t[?]", 1) local intt = torch.IntTensor(1); @@ -276,6 +279,9 @@ function SpatialConvolution:createIODescriptors(input) if cudnn.benchmark then -- the manual auto-tuner is run if autotunerCache[3][autotunerHash] then algType[0] = autotunerCache[3][autotunerHash] + if cudnn.verbose then + print('Autotuning SC BWD: using cached algo = ', algType[0], ' for: ', autotunerHash) + end else local perfResults = ffi.new("cudnnConvolutionBwdDataAlgoPerf_t[?]", 1) local intt = torch.IntTensor(1); @@ -390,7 +396,7 @@ function SpatialConvolution:updateGradInput(input, gradOutput) self:createIODescriptors(input) for g = 0,self.groups - 1 do - errcheck('cudnnConvolutionBackwardData_v3', cudnn.getHandle(), + errcheck('cudnnConvolutionBackwardData', cudnn.getHandle(), one:data(), self.weightDesc[0], self.weight:data() + g*self.weight_offset, self.oDesc[0], gradOutput:data() + g*self.output_offset, @@ -427,7 +433,7 @@ function SpatialConvolution:accGradParameters(input, gradOutput, scale) for g = 0, self.groups - 1 do -- gradWeight - errcheck('cudnnConvolutionBackwardFilter_v3', cudnn.getHandle(), + errcheck('cudnnConvolutionBackwardFilter', cudnn.getHandle(), self.scaleT:data(), self.iDesc[0], input:data() + g*self.input_offset, self.oDesc[0], gradOutput:data() + g*self.output_offset, |