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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SpatialConvolutionMM.c"
#else
static int nn_(SpatialConvolutionMM_updateOutput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
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");
long i;
THTensor *finput = luaT_getfieldcheckudata(L, 1, "finput", torch_Tensor);
THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
luaL_argcheck(L, input->nDimension == 3 || input->nDimension == 4, 2, "3D or 4D(batch mode) tensor expected");
int dimw = 2;
int dimh = 1;
if (input->nDimension == 4) {
THError("batch not yet supported");
}
long nInputPlane = input->size[0];
long inputWidth = input->size[dimw];
long inputHeight = input->size[dimh];
long nOutputPlane = weight->size[0];
long outputWidth = (inputWidth - kW) / dW + 1;
long outputHeight = (inputHeight - kH) / dH + 1;
THTensor *unfoldedInput = THTensor_(new)();
THTensor_(unfold)(unfoldedInput, input, 1, kH, dH);
THTensor_(unfold)(unfoldedInput, unfoldedInput, 2, kW, dW);
THTensor_(transpose)(unfoldedInput, unfoldedInput, 1, 3);
THTensor_(transpose)(unfoldedInput, unfoldedInput, 2, 4);
THTensor_(resize2d)(finput, kW*kH*nInputPlane, outputHeight*outputWidth);
THTensor_(copy)(finput, unfoldedInput);
THTensor_(resize3d)(output, nOutputPlane, outputHeight, outputWidth);
THTensor *output2d = THTensor_(newWithStorage2d)(output->storage, 0,
nOutputPlane, -1,
outputHeight*outputWidth, -1);
for(i = 0; i < nOutputPlane; i++)
THVector_(fill)(output->storage->data+output->storageOffset+output->stride[0]*i, THTensor_(get1d)(bias, i), outputHeight*outputWidth);
THTensor_(addmm)(output2d, 1, output2d, 1, weight, finput);
THTensor_(free)(output2d);
THTensor_(free)(unfoldedInput);
return 1;
}
static int nn_(SpatialConvolutionMM_updateGradInput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
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 nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
THTensor *finput = luaT_getfieldcheckudata(L, 1, "finput", torch_Tensor);
THTensor *fgradInput = luaT_getfieldcheckudata(L, 1, "fgradInput", torch_Tensor);
THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
THArgCheck( nOutputPlane == gradOutput->size[input->nDimension == 4 ? 1 : 0], 1, "Number of output features is not equal to nOutputPlane" );
THTensor *gradOutput2d = THTensor_(newWithStorage2d)(gradOutput->storage, 0,
gradOutput->size[0], -1,
gradOutput->size[1]*gradOutput->size[2], -1);
THTensor_(resizeAs)(fgradInput, finput);
THTensor_(zero)(fgradInput);
THTensor_(transpose)(weight, weight, 0, 1);
THTensor_(addmm)(fgradInput, 1, fgradInput, 1, weight, gradOutput2d);
THTensor_(transpose)(weight, weight, 0, 1);
THTensor_(resizeAs)(gradInput, input);
THTensor_(zero)(gradInput);
THTensor *unfoldedGradInput = THTensor_(new)();
THTensor_(unfold)(unfoldedGradInput, gradInput, 1, kH, dH);
THTensor_(unfold)(unfoldedGradInput, unfoldedGradInput, 2, kW, dW);
THTensor_(transpose)(unfoldedGradInput, unfoldedGradInput, 1, 3);
THTensor_(transpose)(unfoldedGradInput, unfoldedGradInput, 2, 4);
THTensor_(cadd)(unfoldedGradInput, unfoldedGradInput, 1, fgradInput);
THTensor_(free)(unfoldedGradInput);
THTensor_(free)(gradOutput2d);
return 1;
}
static int nn_(SpatialConvolutionMM_accGradParameters)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
real scale = luaL_optnumber(L, 4, 1);
int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
long i;
THTensor *finput = luaT_getfieldcheckudata(L, 1, "finput", torch_Tensor);
THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
THArgCheck( nOutputPlane == gradOutput->size[input->nDimension == 4 ? 1 : 0], 1, "Number of output features is not equal to nOutputPlane" );
THTensor *gradOutput2d = THTensor_(newWithStorage2d)(gradOutput->storage, 0,
gradOutput->size[0], -1,
gradOutput->size[1]*gradOutput->size[2], -1);
THTensor_(transpose)(finput, finput, 0, 1);
THTensor_(addmm)(gradWeight, 1, gradWeight, scale, gradOutput2d, finput);
THTensor_(transpose)(finput, finput, 0, 1);
THTensor *gradOutputPlane = THTensor_(new)();
for(i = 0; i < gradBias->size[0]; i++)
{
THTensor_(select)(gradOutputPlane, gradOutput2d, 0, i);
gradBias->storage->data[i] += scale*THTensor_(sumall)(gradOutputPlane);
}
THTensor_(free)(gradOutputPlane);
THTensor_(free)(gradOutput2d);
return 0;
}
static const struct luaL_Reg nn_(SpatialConvolutionMM__) [] = {
{"SpatialConvolutionMM_updateOutput", nn_(SpatialConvolutionMM_updateOutput)},
{"SpatialConvolutionMM_updateGradInput", nn_(SpatialConvolutionMM_updateGradInput)},
{"SpatialConvolutionMM_accGradParameters", nn_(SpatialConvolutionMM_accGradParameters)},
{NULL, NULL}
};
static void nn_(SpatialConvolutionMM_init)(lua_State *L)
{
luaT_pushmetatable(L, torch_Tensor);
luaT_registeratname(L, nn_(SpatialConvolutionMM__), "nn");
lua_pop(L,1);
}
#endif
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