diff options
Diffstat (limited to 'generic/SpatialConvolutionMap.c')
| -rw-r--r-- | generic/SpatialConvolutionMap.c | 166 |
1 files changed, 105 insertions, 61 deletions
diff --git a/generic/SpatialConvolutionMap.c b/generic/SpatialConvolutionMap.c index a1d20bc..eed0ca9 100644 --- a/generic/SpatialConvolutionMap.c +++ b/generic/SpatialConvolutionMap.c @@ -17,6 +17,24 @@ static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L) THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor); THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor); + real *input_data; + real *output_data; + real *weight_data; + real *bias_data; + real *connTable_data; + + long input_h; + long input_w; + long output_h; + long output_w; + long weight_h; + long weight_w; + + long p, k; + int nweight; + + + luaL_argcheck(L, input->nDimension == 3, 2, "3D tensor expected"); luaL_argcheck(L, input->size[0] >= nInputPlane, 2, "invalid number of input planes"); luaL_argcheck(L, input->size[2] >= kW && input->size[1] >= kH, 2, "input image smaller than kernel size"); @@ -25,39 +43,37 @@ static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L) (input->size[1] - kH) / dH + 1, (input->size[2] - kW) / dW + 1); - // contiguous + /* contiguous */ input = THTensor_(newContiguous)(input); output = THTensor_(newContiguous)(output); - // get raw pointers - real *input_data = THTensor_(data)(input); - real *output_data = THTensor_(data)(output); - real *weight_data = THTensor_(data)(weight); - real *bias_data = THTensor_(data)(bias); - real *connTable_data = THTensor_(data)(connTable); - - // and dims - long input_h = input->size[1]; - long input_w = input->size[2]; - long output_h = output->size[1]; - long output_w = output->size[2]; - long weight_h = weight->size[1]; - long weight_w = weight->size[2]; + /* get raw pointers */ + input_data = THTensor_(data)(input); + output_data = THTensor_(data)(output); + weight_data = THTensor_(data)(weight); + bias_data = THTensor_(data)(bias); + connTable_data = THTensor_(data)(connTable); + + /* and dims */ + input_h = input->size[1]; + input_w = input->size[2]; + output_h = output->size[1]; + output_w = output->size[2]; + weight_h = weight->size[1]; + weight_w = weight->size[2]; - long p; #pragma omp parallel for private(p) for (p = 0; p < nOutputPlane; p++) { - // add bias + /* add bias */ real *ptr_output = output_data + p*output_w*output_h; long j; for(j = 0; j < output_h*output_w; j++) ptr_output[j] = bias_data[p]; - // convolve all maps - int nweight = connTable->size[0]; - long k; + /* convolve all maps */ + nweight = connTable->size[0]; for (k = 0; k < nweight; k++) { - // get offsets for input/output + /* get offsets for input/output */ int o = (int)connTable_data[k*2+1]-1; int i = (int)connTable_data[k*2+0]-1; @@ -72,7 +88,7 @@ static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L) } } - // clean up + /* clean up */ THTensor_(free)(input); THTensor_(free)(output); @@ -91,34 +107,47 @@ static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L) THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor); THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor); - // contiguous + real *gradInput_data; + real *gradOutput_data; + real *weight_data; + real *connTable_data; + + long input_h; + long input_w; + long output_h; + long output_w; + long weight_h; + long weight_w; + + long p; + + /* contiguous */ gradInput = THTensor_(newContiguous)(gradInput); gradOutput = THTensor_(newContiguous)(gradOutput); - // Resize/Zero + /* Resize/Zero */ THTensor_(resizeAs)(gradInput, input); THTensor_(zero)(gradInput); - // get raw pointers - real *gradInput_data = THTensor_(data)(gradInput); - real *gradOutput_data = THTensor_(data)(gradOutput); - real *weight_data = THTensor_(data)(weight); - real *connTable_data = THTensor_(data)(connTable); + /* get raw pointers */ + gradInput_data = THTensor_(data)(gradInput); + gradOutput_data = THTensor_(data)(gradOutput); + weight_data = THTensor_(data)(weight); + connTable_data = THTensor_(data)(connTable); - // and dims - long input_h = input->size[1]; - long input_w = input->size[2]; - long output_h = gradOutput->size[1]; - long output_w = gradOutput->size[2]; - long weight_h = weight->size[1]; - long weight_w = weight->size[2]; + /* and dims */ + input_h = input->size[1]; + input_w = input->size[2]; + output_h = gradOutput->size[1]; + output_w = gradOutput->size[2]; + weight_h = weight->size[1]; + weight_w = weight->size[2]; - long p; #pragma omp parallel for private(p) for(p = 0; p < nInputPlane; p++) { long k; - // backward all + /* backward all */ int nkernel = connTable->size[0]; for(k = 0; k < nkernel; k++) { @@ -126,7 +155,7 @@ static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L) int i = (int)connTable_data[k*2+0]-1; if (i == p) { - // gradient to input + /* gradient to input */ THTensor_(fullConv2Dptr)(gradInput_data + i*input_w*input_h, 1.0, gradOutput_data + o*output_w*output_h, output_h, output_w, @@ -136,7 +165,7 @@ static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L) } } - // clean up + /* clean up */ THTensor_(free)(gradInput); THTensor_(free)(gradOutput); @@ -157,26 +186,41 @@ static int nn_(SpatialConvolutionMap_accGradParameters)(lua_State *L) THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor); THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor); - // contiguous + real *input_data; + real *gradOutput_data; + real *gradWeight_data; + real *gradBias_data; + + /* and dims */ + long input_h; + long input_w; + long output_h; + long output_w; + long weight_h; + long weight_w; + + long k; + int nkernel; + + /* contiguous */ input = THTensor_(newContiguous)(input); gradOutput = THTensor_(newContiguous)(gradOutput); - // get raw pointers - real *input_data = THTensor_(data)(input); - real *gradOutput_data = THTensor_(data)(gradOutput); - real *gradWeight_data = THTensor_(data)(gradWeight); - real *gradBias_data = THTensor_(data)(gradBias); - - // and dims - long input_h = input->size[1]; - long input_w = input->size[2]; - long output_h = gradOutput->size[1]; - long output_w = gradOutput->size[2]; - long weight_h = weight->size[1]; - long weight_w = weight->size[2]; - - // gradients wrt bias - long k; + /* get raw pointers */ + input_data = THTensor_(data)(input); + gradOutput_data = THTensor_(data)(gradOutput); + gradWeight_data = THTensor_(data)(gradWeight); + gradBias_data = THTensor_(data)(gradBias); + + /* and dims */ + input_h = input->size[1]; + input_w = input->size[2]; + output_h = gradOutput->size[1]; + output_w = gradOutput->size[2]; + weight_h = weight->size[1]; + weight_w = weight->size[2]; + + /* gradients wrt bias */ #pragma omp parallel for private(k) for(k = 0; k < nOutputPlane; k++) { real *ptr_gradOutput = gradOutput_data + k*output_w*output_h; @@ -185,15 +229,15 @@ static int nn_(SpatialConvolutionMap_accGradParameters)(lua_State *L) gradBias_data[k] += scale*ptr_gradOutput[l]; } - // gradients wrt weight - int nkernel = connTable->size[0]; + /* gradients wrt weight */ + nkernel = connTable->size[0]; #pragma omp parallel for private(k) for(k = 0; k < nkernel; k++) { int o = (int)THTensor_(get2d)(connTable,k,1)-1; int i = (int)THTensor_(get2d)(connTable,k,0)-1; - // gradient to kernel + /* gradient to kernel */ THTensor_(validXCorr2DRevptr)(gradWeight_data + k*weight_w*weight_h, scale, input_data + i*input_w*input_h, input_h, input_w, @@ -201,7 +245,7 @@ static int nn_(SpatialConvolutionMap_accGradParameters)(lua_State *L) dH, dW); } - // clean up + /* clean up */ THTensor_(free)(input); THTensor_(free)(gradOutput); return 0; |