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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SpatialFractionalMaxPooling.c"
#else
static long* THNN_(SpatialFractionalMaxPooling_generateIntervals)(
real sample,
long inputSize,
long outputSize,
int poolSize) {
real alpha = (real) (inputSize - poolSize) / (real) (outputSize - 1);
long* sequence = (long*) THAlloc(sizeof(long) * outputSize);
long i;
for (i = 0; i < outputSize - 1; ++i) {
sequence[i] =
(long) ((i + sample) * alpha) - (long) (sample * alpha);
}
sequence[outputSize - 1] = inputSize - poolSize;
return sequence;
}
static void THNN_(SpatialFractionalMaxPooling_updateOutput_frame)(
real* input,
real* output,
THIndex_t* indices,
real* randomSamples,
long numPlanes,
long inputW, long inputH,
long outputW, long outputH,
int poolSizeW, int poolSizeH) {
long plane;
#pragma omp parallel for private(plane)
for (plane = 0; plane < numPlanes; ++plane) {
/* each plane contains 2 random samples, one for W and one for H */
real* randomSamplesForPlane = randomSamples + plane * 2;
/* Generate interval sequence */
long* sequenceW =
THNN_(SpatialFractionalMaxPooling_generateIntervals)(
randomSamplesForPlane[0], inputW, outputW, poolSizeW);
long* sequenceH =
THNN_(SpatialFractionalMaxPooling_generateIntervals)(
randomSamplesForPlane[1], inputH, outputH, poolSizeH);
/* loop over output */
long h, w;
real* inputForPlane = input + plane * inputW * inputH;
real* outputForPlane = output + plane * outputW * outputH;
THIndex_t* indicesForPlane = indices + plane * outputW * outputH;
for (h = 0; h < outputH; ++h) {
long inputHStart = sequenceH[h];
for (w = 0; w < outputW; ++w) {
long inputWStart = sequenceW[w];
real maxVal = -THInf;
long maxIndex = -1;
long h2, w2;
for (h2 = inputHStart; h2 < inputHStart + poolSizeH; ++h2) {
for (w2 = inputWStart; w2 < inputWStart + poolSizeW; ++w2) {
THAssert(h2 >= 0 && h2 < inputH);
THAssert(w2 >= 0 && w2 < inputW);
long planeIndex = h2 * inputW + w2;
real val = inputForPlane[planeIndex];
if (val > maxVal) {
maxVal = val;
maxIndex = planeIndex;
}
}
}
THAssert(maxVal != -THInf);
THAssert(maxIndex != -1);
outputForPlane[h * outputW + w] = maxVal;
/* +1 to lua index */
indicesForPlane[h * outputW + w] = maxIndex + TH_INDEX_BASE;
}
}
THFree(sequenceW);
THFree(sequenceH);
}
}
void THNN_(SpatialFractionalMaxPooling_updateOutput)(
THNNState *state,
THTensor *input,
THTensor *output,
int outputW, int outputH,
int poolSizeW, int poolSizeH,
THIndexTensor *indices,
THTensor *randomSamples) {
long numBatch = 1;
int planeDim = 0;
int heightDim = 1;
int widthDim = 2;
long numInputDims = THTensor_(nDimension)(input);
THNN_ARGCHECK(numInputDims == 3 || numInputDims == 4, 2, input,
"3D or 4D (batch mode) tensor expected for input, but got: %s");
if (numInputDims == 4) {
numBatch = THTensor_(size)(input, 0);
planeDim++;
heightDim++;
widthDim++;
}
/* sizes */
long numPlanes = THTensor_(size)(input, planeDim);
long inputH = THTensor_(size)(input, heightDim);
long inputW = THTensor_(size)(input, widthDim);
THArgCheck(outputH + poolSizeH - 1 < inputH, 7,
"poolSizeH (%d) too large relative to input height (%d)",
poolSizeH, inputH);
THArgCheck(outputW + poolSizeW - 1 < inputW, 6,
"poolSizeW (%d) too large relative to input width (%d)",
poolSizeW, inputW);
/* get contiguous input */
input = THTensor_(newContiguous)(input);
if (numInputDims == 3) {
/* resize output */
THTensor_(resize3d)(output, numPlanes, outputH, outputW);
/* indices will contain the locations for each output point */
THIndexTensor_(resize3d)(indices, numPlanes, outputH, outputW);
THNN_(SpatialFractionalMaxPooling_updateOutput_frame)(
THTensor_(data)(input),
THTensor_(data)(output),
THIndexTensor_(data)(indices),
THTensor_(data)(randomSamples),
numPlanes, inputW, inputH, outputW, outputH, poolSizeW, poolSizeH);
} else {
THTensor_(resize4d)(output, numBatch, numPlanes, outputH, outputW);
/* indices will contain the locations for each output point */
THIndexTensor_(resize4d)(indices, numBatch, numPlanes, outputH, outputW);
long batch;
#pragma omp parallel for private(batch)
for (batch = 0; batch < numBatch; ++batch) {
THNN_(SpatialFractionalMaxPooling_updateOutput_frame)(
THTensor_(data)(input) + batch * numPlanes * inputH * inputW,
THTensor_(data)(output) + batch * numPlanes * outputH * outputW,
THIndexTensor_(data)(indices) + batch * numPlanes * outputH * outputW,
THTensor_(data)(randomSamples) + batch * numPlanes * 2,
numPlanes, inputW, inputH, outputW, outputH, poolSizeW, poolSizeH);
}
}
/* cleanup */
THTensor_(free)(input);
}
static void THNN_(SpatialFractionalMaxPooling_updateGradInput_frame)(
real* gradInput,
real* gradOutput,
THIndex_t* indices,
long numPlanes,
long inputW, long inputH,
long outputW, long outputH) {
long plane;
#pragma omp parallel for private(plane)
for (plane = 0; plane < numPlanes; plane++) {
real* gradInputForPlane = gradInput + plane * inputW * inputH;
real* gradOutputForPlane = gradOutput + plane * outputW * outputH;
THIndex_t* indicesForPlane = indices + plane * outputW * outputH;
long h, w;
for (h = 0; h < outputH; ++h) {
for (w = 0; w < outputW; ++w) {
long outputIndex = h * outputW + w;
long index = indicesForPlane[outputIndex] - TH_INDEX_BASE;
THAssert(index >= 0 && index < inputW * inputH);
gradInputForPlane[index] += gradOutputForPlane[outputIndex];
}
}
}
}
void THNN_(SpatialFractionalMaxPooling_updateGradInput)(
THNNState *state,
THTensor *input,
THTensor *gradOutput,
THTensor *gradInput,
int outputW, int outputH,
int poolSizeW, int poolSizeH,
THIndexTensor *indices) {
long numBatch = 1;
int planeDim = 0;
int heightDim = 1;
int widthDim = 2;
long numInputDims = THTensor_(nDimension)(input);
if (numInputDims == 4) {
numBatch = THTensor_(size)(input, 0);
planeDim = 1;
heightDim++;
widthDim++;
}
/* sizes */
long numPlanes = THTensor_(size)(input, planeDim);
long inputH = THTensor_(size)(input, heightDim);
long inputW = THTensor_(size)(input, widthDim);
THArgCheck(outputW == THTensor_(size)(gradOutput, widthDim), 3,
"gradOutput width unexpected");
THArgCheck(outputH == THTensor_(size)(gradOutput, heightDim), 3,
"gradOutput height unexpected");
/* get contiguous gradOutput */
gradOutput = THTensor_(newContiguous)(gradOutput);
/* resize */
THTensor_(resizeAs)(gradInput, input);
THTensor_(zero)(gradInput);
/* backprop */
if (numInputDims == 3) {
THNN_(SpatialFractionalMaxPooling_updateGradInput_frame)(
THTensor_(data)(gradInput),
THTensor_(data)(gradOutput),
THIndexTensor_(data)(indices),
numPlanes, inputW, inputH, outputW, outputH);
} else {
long batch;
#pragma omp parallel for private(batch)
for (batch = 0; batch < numBatch; ++batch) {
THNN_(SpatialFractionalMaxPooling_updateGradInput_frame)(
THTensor_(data)(gradInput) + batch * numPlanes * inputH * inputW,
THTensor_(data)(gradOutput) + batch * numPlanes * outputH * outputW,
THIndexTensor_(data)(indices) + batch * numPlanes * outputH * outputW,
numPlanes, inputW, inputH, outputW, outputH);
}
}
/* cleanup */
THTensor_(free)(gradOutput);
}
#endif
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