Add contiguous checking / make tensors contiguous for

SpatialUpSamplingBilinear, PReLU, SpatialSubSampling, TemporalConvolution.

4 files changed, 61 insertions, 7 deletions

diff --git a/SpatialUpSamplingBilinear.lua b/SpatialUpSamplingBilinear.lua
index 54ce5b8..8f19f91 100644
--- a/SpatialUpSamplingBilinear.lua
+++ b/SpatialUpSamplingBilinear.lua
@@ -70,12 +70,12 @@ end
 function SpatialUpSamplingBilinear:updateOutput(input)
    assert(input:dim() == 4 or input:dim()==3,
             'SpatialUpSamplingBilinear only supports 3D or 4D tensors' )
+   input = makeContiguous(self, input)
    local inputwas3D = false
    if input:dim() == 3 then
       input=input:view(-1, input:size(1), input:size(2), input:size(3))
       inputwas3D = true
    end
-   input = makeContiguous(self, input)
    local xdim = input:dim()
    local ydim = xdim - 1
    self:setSize(input)
@@ -98,6 +98,7 @@ function SpatialUpSamplingBilinear:updateGradInput(input, gradOutput)
             'SpatialUpSamplingBilinear only support 3D or 4D tensors' )
    assert(input:dim() == gradOutput:dim(),
 	  'Input and gradOutput should be of same dimension' )
+   input, gradOutput = makeContiguous(self, input, gradOutput)
    local inputwas3D = false
    if input:dim() == 3 then
       input = input:view(-1, input:size(1), input:size(2), input:size(3))
diff --git a/lib/THNN/generic/PReLU.c b/lib/THNN/generic/PReLU.c
index 75f93e2..ba03b06 100644
--- a/lib/THNN/generic/PReLU.c
+++ b/lib/THNN/generic/PReLU.c
@@ -2,6 +2,16 @@
 #define TH_GENERIC_FILE "generic/PReLU.c"
 #else
 
+static inline void THNN_(PReLU_shapeCheck)(
+                         THNNState *state,
+                         THTensor *input,
+                         THTensor *gradOutput) {
+  THArgCheck(THTensor_(isContiguous)(input), 2, "input must be contiguous");
+  if (gradOutput != NULL) {
+    THArgCheck(THTensor_(isContiguous)(gradOutput), 2, "gradOuput must be contiguous");
+  }
+}
+
 void THNN_(PReLU_updateOutput)(
           THNNState *state,
           THTensor *input,
@@ -9,6 +19,7 @@ void THNN_(PReLU_updateOutput)(
           THTensor *weight,
           THIndex_t nOutputPlane)
 {
+  THNN_(PReLU_shapeCheck)(state, input, NULL);
   THTensor_(resizeAs)(output, input);
 
   if (nOutputPlane == 0)
@@ -76,6 +87,7 @@ void THNN_(PReLU_updateGradInput)(
           THTensor *weight,
           THIndex_t nOutputPlane)
 {
+  THNN_(PReLU_shapeCheck)(state, input, gradOutput);
   THNN_CHECK_NELEMENT(input, gradOutput);
   THTensor_(resizeAs)(gradInput, input);
 
@@ -161,7 +173,8 @@ void THNN_(PReLU_accGradParameters)(
           THIndex_t nOutputPlane,
           real scale)
 {
-  THNN_CHECK_NELEMENT(input, gradOutput);  
+  THNN_(PReLU_shapeCheck)(state, input, gradOutput);
+  THNN_CHECK_NELEMENT(input, gradOutput);
   real *gradWeight_data = THTensor_(data)(gradWeight);
 
   if (nOutputPlane == 0)
diff --git a/lib/THNN/generic/SpatialSubSampling.c b/lib/THNN/generic/SpatialSubSampling.c
index abfbfce..1b2e222 100644
--- a/lib/THNN/generic/SpatialSubSampling.c
+++ b/lib/THNN/generic/SpatialSubSampling.c
@@ -2,6 +2,39 @@
 #define TH_GENERIC_FILE "generic/SpatialSubSampling.c"
 #else
 
+static inline void THNN_(SpatialSubSampling_shapeCheck)(
+                         THTensor *input,
+                         THTensor *gradOutput,
+                         THTensor *weight,
+                         int kW, int kH) {
+  int ndims = input->nDimension;
+  THNN_ARGCHECK(input->nDimension == 3 || input->nDimension == 4, 2, input,
+                  "3D or 4D input tensor expected but got: %s");
+
+  int nInputPlane = THTensor_(size)(weight, 0);
+
+  int dimw = 2;
+  int dimh = 1;
+
+  long inputWidth;
+  long inputHeight;
+
+  if (input->nDimension == 4) {
+    dimw++;
+    dimh++;
+  }
+
+  inputWidth = input->size[dimw];
+  inputHeight = input->size[dimh];
+
+  THArgCheck(input->size[dimh-1] == nInputPlane, 2, "invalid number of input planes");
+  THArgCheck(inputWidth >= kW && inputHeight >= kH, 2, "input image smaller than kernel size");
+
+  if (gradOutput != NULL) {
+    THArgCheck(THTensor_(isContiguous)(gradOutput), 3, "gradOutput must be contiguous");
+  }
+}
+
 void THNN_(SpatialSubSampling_updateOutput)(
     THNNState *state,
     THTensor *input,
@@ -30,7 +63,7 @@ void THNN_(SpatialSubSampling_updateOutput)(
 
   long k;
 
-  THArgCheck(input->nDimension == 3 || input->nDimension == 4, 2, "3D or 4D(batch mode) tensor expected");
+  THNN_(SpatialSubSampling_shapeCheck)(input, NULL, weight, kW, kH);
 
   if (input->nDimension == 4) {
     nbatch = input->size[0];
@@ -43,9 +76,6 @@ void THNN_(SpatialSubSampling_updateOutput)(
   outputWidth = (inputWidth - kW) / dW + 1;
   outputHeight = (inputHeight - kH) / dH + 1;
 
-  THArgCheck(input->size[dimh-1] == nInputPlane, 2, "invalid number of input planes");
-  THArgCheck(inputWidth >= kW && inputHeight >= kH, 2, "input image smaller than kernel size");
-
   if (input->nDimension == 3)
     THTensor_(resize3d)(output, nInputPlane, outputHeight, outputWidth);
   else
@@ -105,7 +135,8 @@ void THNN_(SpatialSubSampling_updateGradInput)(
     int kW, int kH,
     int dW, int dH)
 {
-  
+  THNN_(SpatialSubSampling_shapeCheck)(input, gradOutput, weight, kW, kH);
+
   int dimw = 2;
   int dimh = 1;
   long nbatch = 1;
@@ -188,6 +219,8 @@ void THNN_(SpatialSubSampling_accGradParameters)(
     int dW, int dH,
     real scale)
 {
+  THNN_(SpatialSubSampling_shapeCheck)(input, gradOutput, gradWeight, kW, kH);
+
   long nbatch = 1;
   long dimw = 2;
   long dimh = 1;
diff --git a/lib/THNN/generic/TemporalConvolution.c b/lib/THNN/generic/TemporalConvolution.c
index e7c5142..0e8e83a 100644
--- a/lib/THNN/generic/TemporalConvolution.c
+++ b/lib/THNN/generic/TemporalConvolution.c
@@ -163,6 +163,9 @@ void THNN_(TemporalConvolution_updateGradInput)(
   nInputFrame = input->size[dimS];
   nOutputFrame = gradOutput->size[dimS];
 
+  input = THTensor_(newContiguous)(input);
+  gradOutput = THTensor_(newContiguous)(gradOutput);
+
   gradOutputWindow = THTensor_(new)();
   gradInputWindow = THTensor_(new)();
 
@@ -231,6 +234,8 @@ void THNN_(TemporalConvolution_updateGradInput)(
 
   THTensor_(free)(gradOutputWindow);
   THTensor_(free)(gradInputWindow);
+  THTensor_(free)(gradOutput);
+  THTensor_(free)(input);
 
 }
 
@@ -264,6 +269,7 @@ void THNN_(TemporalConvolution_accGradParameters)(
   nOutputFrame = gradOutput->size[dimS];
 
   input = THTensor_(newContiguous)(input);
+  gradOutput = THTensor_(newContiguous)(gradOutput);
   gradOutputWindow = THTensor_(new)();
   inputWindow = THTensor_(new)();
   
@@ -347,6 +353,7 @@ void THNN_(TemporalConvolution_accGradParameters)(
 
   THTensor_(free)(gradOutputWindow);
   THTensor_(free)(inputWindow);
+  THTensor_(free)(gradOutput);
   THTensor_(free)(input);
 
 }