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Diffstat (limited to 'generic/SpatialConvolution.c')
-rw-r--r--generic/SpatialConvolution.c180
1 files changed, 88 insertions, 92 deletions
diff --git a/generic/SpatialConvolution.c b/generic/SpatialConvolution.c
index e9f2a7b..49ccc8d 100644
--- a/generic/SpatialConvolution.c
+++ b/generic/SpatialConvolution.c
@@ -2,24 +2,9 @@
#define TH_GENERIC_FILE "generic/SpatialConvolution.c"
#else
-static void nn_(convolution_updateOutput_)(THTensor *input, THTensor *output, THTensor *weight, THTensor *bias, int dH, int dW)
-{
- /* add bias */
- long i;
- THTensor *outn = THTensor_(new)();
- for (i=0; i<bias->size[0]; i++) {
- THTensor_(select)(outn,output,0,i);
- THTensor_(fill)(outn, THTensor_(get1d)(bias, i));
- }
- THTensor_(free)(outn);
-
- /* do convolutions */
- THTensor_(conv2Dmv)(output, 1.0, 1.0, input, weight, dH, dW, "V","X");
-}
-
static int nn_(SpatialConvolution_updateOutput)(lua_State *L)
{
- THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
int dW = luaT_getfieldcheckint(L, 1, "dW");
int dH = luaT_getfieldcheckint(L, 1, "dH");
@@ -47,49 +32,59 @@ static int nn_(SpatialConvolution_updateOutput)(lua_State *L)
if (input->nDimension == 3)
{
THTensor_(resize3d)(output, nOutputPlane, outputHeight, outputWidth);
-/* printf("\n*************\nstochastic\n"); */
-/* printf("no=%d\n",output->nDimension); */
-/* printf("no=%ld,%ld,%ld\n",nOutputPlane,outputHeight,outputWidth); */
-/* printf("ni=%d\n",input->nDimension); */
- nn_(convolution_updateOutput_)(input,output,weight,bias,dH,dW);
-/* printf("stochastic\n");*/
- }
- else
- {
- THTensor_(resize4d)(output, input->size[0], nOutputPlane, outputHeight, outputWidth);
- THTensor *outn = THTensor_(new)();
- THTensor *inpn = THTensor_(new)();
+ /* add bias */
long i;
- for (i=0; i<input->size[0]; i++)
+ /*THTensor *outn = THTensor_(new)();*/
+ real* bias_data = THTensor_(data)(bias);
+ real* output_data = THTensor_(data)(output);
+#pragma omp parallel for private(i)
+ for (i=0; i<bias->size[0]; i++)
{
- THTensor_(select)(outn,output,0,i);
- THTensor_(select)(inpn,input,0,i);
- nn_(convolution_updateOutput_)(inpn,outn,weight,bias,dH,dW);
+ /*THTensor_(select)(outn,output,0,i);*/
+ /*TH_TENSOR_APPLY(real,outn, *outn_data = bias_data[i];);*/
+ real *ptr_output = output_data + i*outputWidth*outputHeight;
+ long j;
+ for(j = 0; j < outputWidth*outputHeight; j++)
+ ptr_output[j] = bias_data[i];
}
- THTensor_(free)(outn);
- THTensor_(free)(inpn);
+ /*THTensor_(free)(outn);*/
+
+ /* do convolutions */
+ THTensor_(conv2Dmv)(output, 1.0, 1.0, input, weight, dH, dW, "V","X");
}
+ else
+ {
+ THTensor_(resize4d)(output, input->size[0], nOutputPlane, outputHeight, outputWidth);
-/* /\* add bias *\/ */
-/* long i; */
-/* THTensor *outn = THTensor_(new)(); */
-/* for (i=0; i<bias->size[0]; i++) { */
-/* THTensor_(select)(outn,output,0,i); */
-/* THTensor_(fill)(outn, THTensor_(get1d)(bias, i)); */
-/* } */
-/* THTensor_(free)(outn); */
+ real* bias_data = THTensor_(data)(bias);
+ real* output_data = THTensor_(data)(output);
-/* /\* do convolutions *\/ */
-/* THTensor_(conv2Dmv)(output, 1.0, 1.0, input, weight, dH, dW, "vx"); */
+ long p;
+#pragma omp parallel for private(p)
+ for (p=0; p<input->size[0]; p++)
+ {
+ /* BIAS */
+ long i;
+ for (i=0; i<bias->size[0]; i++)
+ {
+ real *ptr_output = output_data + p*nOutputPlane*outputWidth*outputHeight + i*outputWidth*outputHeight;
+ long j;
+ for(j = 0; j < outputWidth*outputHeight; j++)
+ ptr_output[j] = bias_data[i];
+ }
+ }
+ /* do convolutions */
+ THTensor_(conv2Dmm)(output, 1.0, 1.0, input, weight, dH, dW, "V","X");
+ }
return 1;
}
static int nn_(SpatialConvolution_updateGradInput)(lua_State *L)
{
- THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
- THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+ THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
int dW = luaT_getfieldcheckint(L, 1, "dW");
int dH = luaT_getfieldcheckint(L, 1, "dH");
int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
@@ -102,48 +97,18 @@ static int nn_(SpatialConvolution_updateGradInput)(lua_State *L)
/* gradient to input */
THTensor *tweight = THTensor_(newTranspose)(weight,0,1);
- if(input->nDimension == 3)
+ if (input->nDimension == 3)
{
- THTensor_(conv2Dmv)(gradInput, 0.0, 1.0, gradOutput, tweight, dH, dW, "F", "C");
+ THTensor_(conv2Dmv)(gradInput, 0.0, 1.0, gradOutput, tweight, dH, dW, "F","C");
}
else
{
-
- THTensor_(resizeAs)(gradInput,input);
- THTensor *outn = THTensor_(new)();
- THTensor *inpn = THTensor_(new)();
- long i;
- for (i=0; i<input->size[0]; i++)
- {
- THTensor_(select)(outn,gradOutput,0,i);
- THTensor_(select)(inpn,gradInput,0,i);
- THTensor_(conv2Dmv)(inpn, 0.0, 1.0, outn, tweight, dH, dW, "F", "C");
- }
- THTensor_(free)(outn);
- THTensor_(free)(inpn);
+ THTensor_(conv2Dmm)(gradInput, 0.0, 1.0, gradOutput, tweight, dH, dW, "F","C");
}
THTensor_(free)(tweight);
-
return 1;
}
-static void nn_(convolution_accGradParameters_)(THTensor *input, THTensor *gradOutput, THTensor *gradWeight, THTensor *gradBias, real scale, int dH, int dW)
-{
- long k;
-
- /* gradient to bias */
- real *gradBias_data = THTensor_(data)(gradBias);
- THTensor* gradOutSlice = THTensor_(new)();
- for(k = 0; k < gradOutput->size[0]; k++)
- {
- THTensor_(select)(gradOutSlice, gradOutput, 0, k);
- gradBias_data[k] += scale*THTensor_(sumall)(gradOutSlice);
- }
- THTensor_(free)(gradOutSlice);
-
- /* gradient to kernels */
- THTensor_(conv2DRevger)(gradWeight, 1.0, scale, input, gradOutput, dH, dW);
-}
static int nn_(SpatialConvolution_accGradParameters)(lua_State *L)
{
@@ -156,28 +121,59 @@ static int nn_(SpatialConvolution_accGradParameters)(lua_State *L)
THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
-
+
THArgCheck( nOutputPlane == gradOutput->size[input->nDimension == 4 ? 1 : 0], 1, "Number of output features is not equal to nOutputPlane" );
- if(input->nDimension == 3)
+ int dimw = 2;
+ int dimh = 1;
+
+ if (input->nDimension == 4)
+ {
+ dimw++;
+ dimh++;
+ }
+
+ /* gradient to bias */
+ real *gradBias_data = THTensor_(data)(gradBias);
+ real *gradOutput_data = THTensor_(data)(gradOutput);
+ long noutSlice = gradOutput->size[dimh]*gradOutput->size[dimw];
+ /*THTensor* gradOutSlice = THTensor_(new)();*/
+
+ if (input->nDimension == 3)
{
- nn_(convolution_accGradParameters_)(input,gradOutput,gradWeight,gradBias,scale,dH,dW);
+ long k;
+#pragma omp parallel for private(k)
+ for(k = 0; k < nOutputPlane; k++)
+ {
+ /*THTensor_(select)(gradOutSlice, gradOutput, 0, k);*/
+ real *ptr_gradOutput = gradOutput_data + k*noutSlice;
+ long l;
+ for(l = 0; l < noutSlice; l++)
+ gradBias_data[k] += scale*ptr_gradOutput[l];
+ }
+
+ /* gradient to kernels */
+ THTensor_(conv2DRevger)(gradWeight, 1.0, scale, input, gradOutput, dH, dW);
}
else
{
- THTensor *outn = THTensor_(new)();
- THTensor *inpn = THTensor_(new)();
- long i;
- for (i=0; i<input->size[0]; i++)
+ long k;
+#pragma omp parallel for private(k)
+ for(k = 0; k < nOutputPlane; k++)
{
- THTensor_(select)(outn,gradOutput,0,i);
- THTensor_(select)(inpn,input,0,i);
- nn_(convolution_accGradParameters_)(inpn,outn,gradWeight,gradBias,scale,dH,dW);
+ long p;
+ for(p = 0; p < input->size[0]; p++)
+ {
+ /* BIAS */
+ real *ptr_gradOutput = gradOutput_data + p*nOutputPlane*noutSlice + k*noutSlice;
+ long l;
+ for(l = 0; l < noutSlice; l++)
+ gradBias_data[k] += scale*ptr_gradOutput[l];
+ }
}
- THTensor_(free)(outn);
- THTensor_(free)(inpn);
+ /* gradient to kernels */
+ THTensor_(conv2DRevgerm)(gradWeight, 1.0, scale, input, gradOutput, dH, dW);
}
-
return 0;
}
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