Welcome to mirror list, hosted at ThFree Co, Russian Federation.

github.com/torch/nn.git - Unnamed repository; edit this file 'description' to name the repository.
summaryrefslogtreecommitdiff
path: root/generic/SpatialConvolutionMap.c
diff options
context:
space:
mode:
Diffstat (limited to 'generic/SpatialConvolutionMap.c')
-rw-r--r--generic/SpatialConvolutionMap.c229
1 files changed, 229 insertions, 0 deletions
diff --git a/generic/SpatialConvolutionMap.c b/generic/SpatialConvolutionMap.c
new file mode 100644
index 0000000..ff7d8ca
--- /dev/null
+++ b/generic/SpatialConvolutionMap.c
@@ -0,0 +1,229 @@
+#ifndef TH_GENERIC_FILE
+#define TH_GENERIC_FILE "generic/SpatialConvolutionMap.c"
+#else
+
+static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L)
+{
+ THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ int kW = luaT_getfieldcheckint(L, 1, "kW");
+ int kH = luaT_getfieldcheckint(L, 1, "kH");
+ int dW = luaT_getfieldcheckint(L, 1, "dW");
+ int dH = luaT_getfieldcheckint(L, 1, "dH");
+ int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
+ int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
+
+ THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
+ THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
+ THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
+ THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+
+ 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");
+
+ THTensor_(resize3d)(output, nOutputPlane,
+ (input->size[1] - kH) / dH + 1,
+ (input->size[2] - kW) / dW + 1);
+
+ // 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);
+
+ // and dims
+ long input_n = input->size[0];
+ long input_h = input->size[1];
+ long input_w = input->size[2];
+ long output_n = output->size[0];
+ long output_h = output->size[1];
+ long output_w = output->size[2];
+ long weight_n = weight->size[0];
+ long weight_h = weight->size[1];
+ long weight_w = weight->size[2];
+
+ // add bias
+ THTensor *outputPlane = THTensor_(new)();
+ int k;
+ for (k = 0; k < nOutputPlane; k++) {
+ THTensor_(select)(outputPlane,output,0,k);
+ THTensor_(fill)(outputPlane, THTensor_(get1d)(bias, k));
+ }
+ THTensor_(free)(outputPlane);
+
+ // convolve all maps
+ int i,o;
+ int nweight = connTable->size[0];
+ for (k = 0; k < nweight; k++) {
+ // get offsets for input/output
+ o = (int)THTensor_(get2d)(connTable,k,1)-1;
+ i = (int)THTensor_(get2d)(connTable,k,0)-1;
+
+ // convolve each map
+ THTensor_(validXCorr2Dptr)(output_data + o*output_w*output_h,
+ 1.0,
+ input_data + i*input_w*input_h, input_h, input_w,
+ weight_data + k*weight_w*weight_h, weight_h, weight_w,
+ dH, dW);
+ }
+
+ // clean up
+ THTensor_(free)(input);
+ THTensor_(free)(output);
+
+ return 1;
+}
+
+static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L)
+{
+ THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+ int kW = luaT_getfieldcheckint(L, 1, "kW");
+ int kH = luaT_getfieldcheckint(L, 1, "kH");
+ int dW = luaT_getfieldcheckint(L, 1, "dW");
+ int dH = luaT_getfieldcheckint(L, 1, "dH");
+ int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
+ int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
+
+ THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
+ THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
+ THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
+ THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+ THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+
+ // contiguous
+ gradInput = THTensor_(newContiguous)(gradInput);
+ gradOutput = THTensor_(newContiguous)(gradOutput);
+
+ // 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 *gradWeight_data = THTensor_(data)(gradWeight);
+
+ // and dims
+ long input_n = input->size[0];
+ long input_h = input->size[1];
+ long input_w = input->size[2];
+ long output_n = gradOutput->size[0];
+ long output_h = gradOutput->size[1];
+ long output_w = gradOutput->size[2];
+ long weight_n = weight->size[0];
+ long weight_h = weight->size[1];
+ long weight_w = weight->size[2];
+
+ // updateGradInput all
+ int k;
+ int nkernel = connTable->size[0];
+ 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 input
+ THTensor_(fullConv2Dptr)(gradInput_data + i*input_w*input_h,
+ 1.0,
+ gradOutput_data + o*output_w*output_h, output_h, output_w,
+ weight_data + k*weight_w*weight_h, weight_h, weight_w,
+ dH, dW);
+ }
+
+ // clean up
+ THTensor_(free)(gradInput);
+ THTensor_(free)(gradOutput);
+
+ return 1;
+}
+
+static int nn_(SpatialConvolutionMap_accGradParameters)(lua_State *L)
+{
+ THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+ int kW = luaT_getfieldcheckint(L, 1, "kW");
+ int kH = luaT_getfieldcheckint(L, 1, "kH");
+ int dW = luaT_getfieldcheckint(L, 1, "dW");
+ int dH = luaT_getfieldcheckint(L, 1, "dH");
+ int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
+ int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
+ real scale = luaL_optnumber(L, 4, 1);
+
+ THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
+ THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
+ THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
+ THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+ THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+
+ // 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 *weight_data = THTensor_(data)(weight);
+ real *gradWeight_data = THTensor_(data)(gradWeight);
+
+ // and dims
+ long input_n = input->size[0];
+ long input_h = input->size[1];
+ long input_w = input->size[2];
+ long output_n = gradOutput->size[0];
+ long output_h = gradOutput->size[1];
+ long output_w = gradOutput->size[2];
+ long weight_n = weight->size[0];
+ long weight_h = weight->size[1];
+ long weight_w = weight->size[2];
+
+ // gradients wrt bias
+ int k;
+ THTensor *gradOutputPlane = THTensor_(new)();
+ real *gradBias_data = THTensor_(data)(gradBias);
+ for(k = 0; k < nOutputPlane; k++) {
+ THTensor_(select)(gradOutputPlane, gradOutput, 0, k);
+ gradBias_data[k] += scale * THTensor_(sumall)(gradOutputPlane);
+ }
+ THTensor_(free)(gradOutputPlane);
+
+ // gradients wrt weight
+ int nkernel = connTable->size[0];
+ 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
+ THTensor_(validXCorr2DRevptr)(gradWeight_data + k*weight_w*weight_h,
+ scale,
+ input_data + i*input_w*input_h, input_h, input_w,
+ gradOutput_data + o*output_w*output_h, output_h, output_w,
+ dH, dW);
+ }
+
+ // clean up
+ THTensor_(free)(input);
+ THTensor_(free)(gradOutput);
+ return 0;
+}
+
+static const struct luaL_Reg nn_(SpatialConvolutionMap__) [] = {
+ {"SpatialConvolutionMap_updateOutput", nn_(SpatialConvolutionMap_updateOutput)},
+ {"SpatialConvolutionMap_updateGradInput", nn_(SpatialConvolutionMap_updateGradInput)},
+ {"SpatialConvolutionMap_accGradParameters", nn_(SpatialConvolutionMap_accGradParameters)},
+ {NULL, NULL}
+};
+
+static void nn_(SpatialConvolutionMap_init)(lua_State *L)
+{
+ luaT_pushmetaclass(L, torch_(Tensor_id));
+ luaT_registeratname(L, nn_(SpatialConvolutionMap__), "nn");
+ lua_pop(L,1);
+}
+
+#endif
generated by cgit v1.2.3 (git 2.25.1) at 2024-07-25 16:59:04 +0300