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PaddleDetection
提交 790379f1 编写于 作者: C chengduoZH
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paddle/cuda/include/hl_cnn.h
浏览文件 @ 790379f1
......@@ -173,31 +173,6 @@ extern void hl_avgpool_backward(const int frameCnt,
real* backGrad,
const int outStride);
/**
* @brief Maximum pool forward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] channels number of channel.
* @param[in] depth image depth.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledD output image depth.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeZ depth of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] sizeX width of pooling window.
* @param[in] strideD pooling stride depth.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingD padding depth.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
*
*/
extern void hl_maxpool3D_forward(const int frameCnt,
const real* inputData,
const int channels,
......@@ -219,35 +194,6 @@ extern void hl_maxpool3D_forward(const int frameCnt,
real* tgtData,
const int tgtStride);
/**
* @brief Maximum pool backward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[out] outData output data.
* @param[out] outGrad output grad data.
* @param[in] channels number of channel.
* @param[in] depth image depth.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledD output image depth.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeZ depth of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] sizeX width of pooling window.
* @param[in] strideD pooling stride depth.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] scaleA scale.
* @param[in] scaleB scale.
* @param[in] paddingD padding depth.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] targetGrad output grad.
* @param[in] outStride stride between output data samples.
*
*/
extern void hl_maxpool3D_backward(const int frameCnt,
const real* inputData,
const real* outData,
......@@ -273,31 +219,6 @@ extern void hl_maxpool3D_backward(const int frameCnt,
real* targetGrad,
const int outStride);
/**
* @brief Averge pool forward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] channels number of channel.
* @param[in] depth image depth.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledD output image depth.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeZ depth of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] sizeX width of pooling window.
* @param[in] strideD pooling stride depth.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingD padding depth.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
*
*/
extern void hl_avgpool3D_forward(const int frameCnt,
const real* inputData,
const int channels,
......@@ -319,33 +240,6 @@ extern void hl_avgpool3D_forward(const int frameCnt,
real* tgtData,
const int tgtStride);
/**
* @brief Maximum pool backward.
*
* @param[in] frameCnt batch size of input image.
* @param[in] outGrad output grad data.
* @param[in] channels number of channel.
* @param[in] depth image depth.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledD output image depth.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeZ depth of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] sizeX width of pooling window.
* @param[in] strideD pooling stride depth.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingD padding depth.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[in] scaleA scale.
* @param[in] scaleB scale.
* @param[out] backGrad output grad.
* @param[in] outStride stride between output data samples.
*
*/
extern void hl_avgpool3D_backward(const int frameCnt,
const real* outGrad,
const int channels,
......
paddle/cuda/include/stub/hl_cnn_stub.h
浏览文件 @ 790379f1
......@@ -169,9 +169,9 @@ inline void hl_avgpool3D_backward(const int frameCnt,
const int strideD,
const int strideH,
const int strideW,
int paddingD,
int paddingH,
int paddingW,
const int paddingD,
const int paddingH,
const int paddingW,
real scaleA,
real scaleB,
real* backGrad,
......
paddle/gserver/layers/Pool3DLayer.cpp
浏览文件 @ 790379f1
......@@ -58,30 +58,9 @@ size_t Pool3DLayer::getSize() {
CHECK_EQ(inputLayers_.size(), 1UL);
size_t layerSize = 0;
// imgSizeD_ = inputLayers_[0]->getOutput().getFrameDepth();
// imgSizeH_ = inputLayers_[0]->getOutput().getFrameHeight();
// imgSizeW_ = inputLayers_[0]->getOutput().getFrameWidth();
if (imgSizeH_ == 0) {
// imgSizeH_ = imgSizeY_;
}
if (imgSizeW_ == 0) {
// imgSizeW_ = imgSize_;
}
outputD_ = outputSize(imgSizeD_,
sizeZ_,
paddingD_,
strideD_,
/* caffeMode */ false);
outputH_ = outputSize(imgSizeH_,
sizeY_,
paddingH_,
strideH_,
/* caffeMode */ false);
outputW_ = outputSize(imgSizeW_,
sizeX_,
paddingW_,
strideW_,
/* caffeMode */ false);
outputD_ = outputSize(imgSizeD_, sizeZ_, paddingD_, strideD_, false);
outputH_ = outputSize(imgSizeH_, sizeY_, paddingH_, strideH_, false);
outputW_ = outputSize(imgSizeW_, sizeX_, paddingW_, strideW_, false);
layerSize = outputD_ * outputH_ * outputW_ * channels_;
getOutput().setFrameHeight(outputH_);
......@@ -100,37 +79,37 @@ void Pool3DLayer::forward(PassType passType) {
if (poolType_ == "avg") {
outMat->avgPool3DForward(*inMat,
channels_,
imgSizeD_,
imgSizeH_,
imgSizeW_,
channels_,
outputD_,
outputH_,
outputW_,
sizeZ_,
sizeY_,
sizeX_,
strideD_,
strideH_,
strideW_,
outputD_,
outputH_,
outputW_,
paddingD_,
paddingH_,
paddingW_);
} else if (poolType_ == "max") {
outMat->maxPool3DForward(*inMat,
channels_,
imgSizeD_,
imgSizeH_,
imgSizeW_,
channels_,
outputD_,
outputH_,
outputW_,
sizeZ_,
sizeY_,
sizeX_,
strideD_,
strideH_,
strideW_,
outputD_,
outputH_,
outputW_,
paddingD_,
paddingH_,
paddingW_);
......@@ -155,41 +134,41 @@ void Pool3DLayer::backward(const UpdateCallback& callback) {
imgSizeD_,
imgSizeH_,
imgSizeW_,
outputD_,
outputH_,
outputW_,
sizeZ_,
sizeY_,
sizeZ_,
strideD_,
strideH_,
strideW_,
outputD_,
outputH_,
outputW_,
1,
1,
paddingD_,
paddingH_,
paddingW_);
paddingW_,
1.0,
1.0);
} else if (poolType_ == "max") {
inGradMat->maxPool3DBackward(*inMat,
*outGradMat,
*outMat,
imgSizeD_,
imgSizeH_,
imgSizeW_,
*outGradMat,
*outMat,
outputD_,
outputH_,
outputW_,
sizeZ_,
sizeY_,
sizeZ_,
strideD_,
strideH_,
strideW_,
outputD_,
outputH_,
outputW_,
1,
1,
paddingD_,
paddingH_,
paddingW_);
paddingW_,
1.0,
1.0);
} else {
LOG(FATAL) << "Unknown pool type: " << poolType_;
}
......
paddle/gserver/layers/Pool3DLayer.h
浏览文件 @ 790379f1
......@@ -44,5 +44,6 @@ protected:
int imgSizeW_, imgSizeH_, imgSizeD_;
int outputW_, outputH_, outputD_;
std::string poolType_;
MatrixPtr maxPoolIdx_;
};
} // namespace paddle
paddle/math/Matrix.cpp
浏览文件 @ 790379f1
......@@ -1191,23 +1191,23 @@ void GpuMatrix::avgPoolBackward(Matrix& outGrad,
}
void GpuMatrix::maxPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
CHECK(inputMat.useGpu_ == true) << "Matrix type are not equal";
CHECK(inputMat.useGpu_) << "Matrix type are not correct";
real* inputData = inputMat.getData();
size_t num = inputMat.getHeight();
......@@ -1236,32 +1236,31 @@ void GpuMatrix::maxPool3DForward(Matrix& inputMat,
paddingD,
paddingH,
paddingW,
data_,
getData(),
getStride());
}
void GpuMatrix::maxPool3DBackward(Matrix& inputMat,
Matrix& outGrad,
Matrix& outV,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
Matrix& outGrad,
Matrix& outV,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
CHECK(inputMat.useGpu_ == true && outGrad.useGpu_ == true &&
outV.useGpu_ == true)
size_t paddingW,
real scaleTargets,
real scaleOutput) {
CHECK(inputMat.useGpu_ && outGrad.useGpu_ && outV.useGpu_)
<< "Matrix type are not equal";
real* inputData = inputMat.getData();
......@@ -1300,28 +1299,28 @@ void GpuMatrix::maxPool3DBackward(Matrix& inputMat,
paddingW,
scaleTargets,
scaleOutput,
data_,
getData(),
outGrad.getStride());
}
void GpuMatrix::avgPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
CHECK(inputMat.useGpu_ == true) << "Matrix type are not equal";
CHECK(inputMat.useGpu_) << "Matrix type are not equal";
real* inputData = inputMat.getData();
size_t frameNum = inputMat.getHeight();
......@@ -1350,7 +1349,7 @@ void GpuMatrix::avgPool3DForward(Matrix& inputMat,
paddingD,
paddingH,
paddingW,
data_,
getData(),
getStride());
}
......@@ -1358,21 +1357,21 @@ void GpuMatrix::avgPool3DBackward(Matrix& outGrad,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
CHECK(outGrad.useGpu_ == true) << "Matrix type are not equal";
size_t paddingW,
real scaleTargets,
real scaleOutput) {
CHECK(outGrad.useGpu_) << "Matrix type are not equal";
real* outDiff = outGrad.getData();
size_t frameNum = outGrad.getHeight();
......@@ -1404,7 +1403,7 @@ void GpuMatrix::avgPool3DBackward(Matrix& outGrad,
paddingW,
scaleTargets,
scaleOutput,
data_,
getData(),
outGrad.getStride());
}
......@@ -2149,24 +2148,24 @@ void CpuMatrix::avgPoolBackward(Matrix& input,
}
void CpuMatrix::maxPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
real* inputData = inputMat.getData();
real* outData = data_;
real* outData = getData();
size_t num = inputMat.getHeight();
size_t inWidth = imgSizeW;
size_t inHeight = imgSizeH;
......@@ -2186,7 +2185,7 @@ void CpuMatrix::maxPool3DForward(Matrix& inputMat,
/* pool max one by one */
for (size_t n = 0; n < num; ++n) { // frame by frame
if (!isContiguous()) {
outData = data_ + n * outStride;
outData = getData() + n * outStride;
}
for (size_t c = 0; c < channels; ++c) { // channel by channel
for (size_t pd = 0; pd < outputD; ++pd) {
......@@ -2201,15 +2200,18 @@ void CpuMatrix::maxPool3DForward(Matrix& inputMat,
dstart = std::max(dstart, 0);
hstart = std::max(hstart, 0);
wstart = std::max(wstart, 0);
real maxOutData = outData[(pd * outputH + ph) * outputW + pw];
for (int d = dstart; d < dend; ++d) {
for (int h = hstart; h < hend; ++h) {
for (int w = wstart; w < wend; ++w) {
outData[(pd * outputH + ph) * outputW + pw] =
std::max(outData[(pd * outputH + ph) * outputW + pw],
inputData[(d * inHeight + h) * inWidth + w]);
if (maxOutData <
inputData[(d * inHeight + h) * inWidth + w]) {
maxOutData = inputData[(d * inHeight + h) * inWidth + w];
}
}
}
}
outData[(pd * outputH + ph) * outputW + pw] = maxOutData;
}
}
}
......@@ -2221,25 +2223,25 @@ void CpuMatrix::maxPool3DForward(Matrix& inputMat,
}
void CpuMatrix::maxPool3DBackward(Matrix& image,
Matrix& outGrad,
Matrix& outV,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
Matrix& outGrad,
Matrix& outV,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
size_t paddingW,
real scaleTargets,
real scaleOutput) {
size_t num = image.getHeight();
size_t channels = size_t(width_ / imgSizeD / imgSizeH / imgSizeW);
CHECK(image.getWidth() == imgSizeD * imgSizeH * imgSizeW * channels);
......@@ -2247,19 +2249,18 @@ void CpuMatrix::maxPool3DBackward(Matrix& image,
CHECK(outV.getHeight() == outGrad.getHeight() &&
outV.getWidth() == outGrad.getWidth());
real* tgtGrad = data_;
real* tgtGrad = getData();
real* inData = image.getData();
real* otData = outV.getData();
real* otGrad = outGrad.getData();
size_t outStride = outV.getStride();
real* origOutData = otData;
real* origOutGrad = otGrad;
;
for (size_t n = 0; n < num; ++n) {
if (!outV.isContiguous()) {
otData = origOutData + n * outStride;
otGrad = origOutGrad + n * outStride;
otData = outV.getData() + n * outStride;
otGrad = outGrad.getData() + n * outStride;
}
for (size_t c = 0; c < channels; ++c) {
for (size_t pd = 0; pd < outputD; ++pd) {
......@@ -2274,7 +2275,7 @@ void CpuMatrix::maxPool3DBackward(Matrix& image,
dstart = std::max(dstart, 0);
hstart = std::max(hstart, 0);
wstart = std::max(wstart, 0);
for (int d = 0; d < dend; ++d) {
for (int d = dstart; d < dend; ++d) {
for (int h = hstart; h < hend; ++h) {
for (int w = wstart; w < wend; ++w) {
tgtGrad[(d * imgSizeH + h) * imgSizeW + w] =
......@@ -2299,19 +2300,19 @@ void CpuMatrix::maxPool3DBackward(Matrix& image,
}
void CpuMatrix::avgPool3DForward(Matrix& input,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
......@@ -2322,7 +2323,7 @@ void CpuMatrix::avgPool3DForward(Matrix& input,
size_t inWidth = imgSizeW;
CHECK(inDepth * inHeight * inWidth * channels == input.getWidth());
CHECK(outputD * outputH * outputW * channels * num == height_ * width_);
real* tgtData = data_;
real* tgtData = getData();
real* inData = input.getData();
for (size_t n = 0; n < num; ++n) {
......@@ -2372,20 +2373,20 @@ void CpuMatrix::avgPool3DBackward(Matrix& input,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
size_t paddingW,
real scaleTargets,
real scaleOutput) {
size_t num = input.getHeight();
size_t channels = input.getWidth() / outputD / outputH / outputW;
CHECK(imgSizeD * imgSizeH * imgSizeW * channels == getWidth());
......
paddle/math/Matrix.h
浏览文件 @ 790379f1
......@@ -933,19 +933,19 @@ public:
* in the sizeX of value
*/
virtual void maxPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
......@@ -953,42 +953,42 @@ public:
}
virtual void maxPool3DBackward(Matrix& image,
Matrix& outGrad,
Matrix& outV,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
Matrix& outGrad,
Matrix& outV,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
size_t paddingW,
real scaleTargets,
real scaleOutput) {
LOG(FATAL) << "Not implemeted";
}
virtual void avgPool3DForward(Matrix& input,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
......@@ -999,20 +999,20 @@ public:
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW) {
size_t paddingW,
real scaleTargets,
real scaleOutput) {
LOG(FATAL) << "Not implemeted";
}
......@@ -1435,60 +1435,59 @@ public:
size_t paddingH,
size_t paddingW);
/////////////////////////
void maxPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW);
void maxPool3DBackward(Matrix& image,
Matrix& outGrad,
Matrix& outV,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
Matrix& outGrad,
Matrix& outV,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW);
size_t paddingW,
real scaleTargets,
real scaleOutput);
void avgPool3DForward(Matrix& input,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW);
......@@ -1497,20 +1496,20 @@ public:
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW);
size_t paddingW,
real scaleTargets,
real scaleOutput);
void maxSequenceForward(Matrix& input,
const IVector& sequence,
......@@ -1670,60 +1669,60 @@ public:
real scaleOutput,
size_t paddingH,
size_t paddingW);
//////////////////////
void maxPool3DForward(Matrix& inputMat,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW);
void maxPool3DBackward(Matrix& image,
Matrix& outGrad,
Matrix& outV,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
Matrix& outGrad,
Matrix& outV,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW);
size_t paddingW,
real scaleTargets,
real scaleOutput);
void avgPool3DForward(Matrix& input,
size_t channels,
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t channels,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t paddingD,
size_t paddingH,
size_t paddingW);
......@@ -1732,20 +1731,20 @@ public:
size_t imgSizeD,
size_t imgSizeH,
size_t imgSizeW,
size_t outputD,
size_t outputH,
size_t outputW,
size_t sizeZ,
size_t sizeY,
size_t sizeX,
size_t strideD,
size_t strideH,
size_t strideW,
size_t outputD,
size_t outputH,
size_t outputW,
real scaleTargets,
real scaleOutput,
size_t paddingD,
size_t paddingH,
size_t paddingW);
size_t paddingW,
real scaleTargets,
real scaleOutput);
void maxSequenceForward(Matrix& input,
const IVector& sequence,
......
paddle/math/tests/test_matrixCompare.cpp
浏览文件 @ 790379f1
......@@ -1204,7 +1204,6 @@ TEST(Matrix, warpCTC) {
}
}
/////
void testMatrixPool3D(int depth, int height, int width) {
int channel = 3;
int filterX = 3, filterY = 4, filterZ = 5;
......@@ -1226,38 +1225,37 @@ void testMatrixPool3D(int depth, int height, int width) {
cpuImage->randomizeUniform();
gpuImage->copyFrom(*cpuImage);
// std::cout << "test maxPool3DForward...\n";
cpuOutput->maxPool3DForward(*cpuImage,
channel,
depth,
height,
width,
channel,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
padZ,
padY,
padX);
gpuOutput->maxPool3DForward(*gpuImage,
channel,
depth,
height,
width,
channel,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
padZ,
padY,
padX);
......@@ -1265,39 +1263,38 @@ void testMatrixPool3D(int depth, int height, int width) {
cpuImage->randomizeUniform();
gpuImage->copyFrom(*cpuImage);
// std::cout << "test avgPool3DForward...\n";
cpuOutput->avgPool3DForward(*cpuImage,
channel,
depth,
height,
width,
channel,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
padZ,
padY,
padX);
gpuOutput->avgPool3DForward(*gpuImage,
channel,
depth,
height,
width,
channel,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
padZ,
padY,
padX);
......@@ -1306,98 +1303,96 @@ void testMatrixPool3D(int depth, int height, int width) {
gpuImage->copyFrom(*cpuImage);
cpuOutput->randomizeUniform();
gpuOutput->copyFrom(*cpuOutput);
// std::cout << "test avgPool3DBackward...\n";
cpuImage->avgPool3DBackward(*cpuOutput,
depth,
height,
width,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
1,
1,
padZ,
padY,
padX);
padX,
1.0,
1.0);
gpuImage->avgPool3DBackward(*gpuOutput,
depth,
height,
width,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
1,
1,
padZ,
padY,
padX);
padX,
1.0,
1.0);
TensorCheckErr(*cpuImage, *gpuImage);
cpuImage->randomizeUniform();
gpuImage->copyFrom(*cpuImage);
cpuOutput->randomizeUniform();
gpuOutput->copyFrom(*cpuOutput);
// std::cout << "test maxPool3DBackward...\n";
cpuImage->maxPool3DBackward(*cpuImage,
*cpuOutput,
*cpuOutput,
depth,
height,
width,
*cpuOutput,
*cpuOutput,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
1,
1,
padZ,
padY,
padX);
padX,
1.0,
1.0);
gpuImage->maxPool3DBackward(*gpuImage,
*gpuOutput,
*gpuOutput,
depth,
height,
width,
*gpuOutput,
*gpuOutput,
outD,
outH,
outW,
filterZ,
filterY,
filterX,
strideZ,
strideY,
strideX,
outD,
outH,
outW,
1,
1,
padZ,
padY,
padX);
padX,
1.0,
1.0);
TensorCheckErr(*cpuImage, *gpuImage);
}
TEST(Matrix, Pool3D) {
for (auto depth : {9, 16, 64, 128}) {
for (auto height : {9, 11, 128, 256}) {
for (auto depth : {9, 16, 64}) {
for (auto height : {9, 11, 128}) {
for (auto width : {9, 32, 128}) {
VLOG(3) << "depth=" << depth << " height=" << height
<< " width=" << width;
......
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