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rebase deconv implementation with develop branch and resolve conflicts with pull#218 commit 45c81a414f

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avx_docs
wangyang59 9 years ago
parent 5e4cc241ac
commit 3d72e94939
9 changed files with 78 additions and 80 deletions
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69
paddle/gserver/layers/ConvBaseLayer.cpp
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@ -48,8 +48,20 @@ bool ConvBaseLayer::init(const LayerMap& layerMap,
outputW_.push_back(conf.output_x());
}
CHECK(inputLayers_.size() == parameters_.size());
for (size_t i = 0; i < inputLayers_.size(); i++) {
size_t height, width;
height = filterPixels_[i] * filterChannels_[i];
width = (!isDeconv_) ? numFilters_ : channels_[i];
// create a new weight
CHECK_EQ(parameters_[i]->getSize(), width * height);
Weight* w = new Weight(height, width, parameters_[i]);
weights_.emplace_back(w);
}
/* initialize the biases_ */
if (biasParameter_.get() != NULL) {
if (biasParameter_.get()) {
if (sharedBiases_) {
CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
biases_ =
@ -76,25 +88,46 @@ size_t ConvBaseLayer::calOutputSize() {
clearAndReserve(&outputH_);
clearAndReserve(&outputW_);
size_t layerSize = 0;
for (size_t i = 0; i < inputLayers_.size(); i++) {
imgSizeH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
imgSizeW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
if (imgSizeH_[i] == 0)
imgSizeH_[i] = config_.inputs(i).conv_conf().img_size();
if (imgSizeW_[i] == 0)
imgSizeW_[i] = config_.inputs(i).conv_conf().img_size();
outputH_.push_back(outputSize(imgSizeH_[i], filterSizeY_[i], paddingY_[i],
strideY_[i], caffeMode_));
outputW_.push_back(outputSize(imgSizeW_[i], filterSize_[i], padding_[i],
stride_[i], caffeMode_));
CHECK_EQ(outputH_[i], outputH_[0]);
CHECK_EQ(outputW_[i], outputW_[0]);
if (!isDeconv_) {
for (size_t i = 0; i < inputLayers_.size(); i++) {
imgSizeH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
imgSizeW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
if (imgSizeH_[i] == 0)
imgSizeH_[i] = config_.inputs(i).conv_conf().img_size();
if (imgSizeW_[i] == 0)
imgSizeW_[i] = config_.inputs(i).conv_conf().img_size();
outputH_.push_back(
outputSize(imgSizeH_[i], filterSizeY_[i], paddingY_[i], strideY_[i]));
outputW_.push_back(
outputSize(imgSizeW_[i], filterSize_[i], padding_[i], stride_[i]));
CHECK_EQ(outputH_[i], outputH_[0]);
CHECK_EQ(outputW_[i], outputW_[0]);
}
getOutput().setFrameHeight(outputH_[0]);
getOutput().setFrameWidth(outputW_[0]);
layerSize = outputH_[0] * outputW_[0] * size_t(numFilters_);
} else {
for (size_t i = 0; i < inputLayers_.size(); i++) {
outputH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
outputW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
if (outputH_[i] == 0)
outputH_[i] = config_.inputs(i).conv_conf().output_x();
if (outputW_[i] == 0)
outputW_[i] = config_.inputs(i).conv_conf().output_x();
imgSizeH_.push_back(
imageSize(outputH_[i], filterSizeY_[i], paddingY_[i], strideY_[i]));
imgSizeW_.push_back(
imageSize(outputW_[i], filterSize_[i], padding_[i], stride_[i]));
CHECK_EQ(imgSizeH_[i], imgSizeH_[0]);
CHECK_EQ(imgSizeW_[i], imgSizeW_[0]);
}
getOutput().setFrameHeight(imgSizeH_[0]);
getOutput().setFrameWidth(imgSizeW_[0]);
layerSize = imgSizeH_[0] * imgSizeW_[0] * size_t(numFilters_);
}
getOutput().setFrameHeight(outputH_[0]);
getOutput().setFrameWidth(outputW_[0]);
layerSize = outputH_[0] * outputW_[0] * size_t(numFilters_);
return layerSize;
return layerSize;
}
} // namespace paddle

16
paddle/gserver/layers/ExpandConvBaseLayer.cpp
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@ -45,15 +45,27 @@ bool ExpandConvBaseLayer::init(const LayerMap &layerMap,
caffeMode_ = conf.caffe_mode();
}
getOutputSize();
return true;
}
size_t ExpandConvBaseLayer::getOutputSize() {
CHECK_NE(inputLayers_.size(), 0UL);
size_t layerSize = ConvBaseLayer::calOutputSize();
subN_.clear();
for (size_t i = 0; i < inputLayers_.size(); i++) {
subN_.push_back(outputH_[i] * outputW_[i]);
}
return layerSize;
}
void ExpandConvBaseLayer::resetExpandInput(size_t height, size_t width) {
Matrix::resizeOrCreate(expandInput_, height, width, false, useGpu_);
}
void ExpandConvBaseLayer::addSharedBias() {
size_t mapW = getSize() / numFilters_;
size_t mapW = getOutputSize() / numFilters_;
size_t mapH = getOutputValue()->getElementCnt() / mapW;
MatrixPtr out =
Matrix::create(getOutputValue()->getData(), mapH, mapW, false, useGpu_);
@ -224,7 +236,7 @@ void ExpandConvBaseLayer::bpropWeights(MatrixPtr image, MatrixPtr out,
}
void ExpandConvBaseLayer::bpropSharedBias(MatrixPtr biases, MatrixPtr v) {
size_t mapW = getSize() / numFilters_;
size_t mapW = getOutputSize() / numFilters_;
size_t mapH = v->getElementCnt() / mapW;
MatrixPtr vTmp = Matrix::create(v->getData(), mapH, mapW, false, useGpu_);

9
paddle/gserver/layers/ExpandConvBaseLayer.h
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@ -34,14 +34,6 @@ protected:
IntV subN_;
/// subK_ = channels_ * filterPixels_ * groups_.
IntV subK_;
/// The spatial dimensions of height of input feature map.
IntV imgSizeH_;
/// The spatial dimensions of width of input feature map.
IntV imgSizeW_;
/// The spatial dimensions of height of output feature map.
IntV outputH_;
/// The spatial dimensions of width of output feature map.
IntV outputW_;
/*The expandInput_ and transOutValue_ are used for CPU expand conv calc
* Expand one sample at a time. shape:
@ -59,6 +51,7 @@ public:
bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
size_t getOutputSize();
/**
* Create or resize expandInput_.
*/

10
paddle/gserver/layers/ExpandConvLayer.cpp
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@ -28,16 +28,6 @@ bool ExpandConvLayer::init(const LayerMap &layerMap,
return true;
}
size_t ExpandConvLayer::getOutputSize() {
CHECK_NE(inputLayers_.size(), 0UL);
size_t layerSize = ConvBaseLayer::calOutputSize();
subN_.clear();
for (size_t i = 0; i < inputLayers_.size(); i++) {
subN_.push_back(outputH_[i] * outputW_[i]);
}
return layerSize;
}
void ExpandConvLayer::forward(PassType passType) {
Layer::forward(passType);

2
paddle/gserver/layers/ExpandConvLayer.h
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@ -38,8 +38,6 @@ public:
bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
size_t getOutputSize();
void forward(PassType passType);
void backward(const UpdateCallback& callback);
};

30
paddle/gserver/layers/ExpandConvTransLayer.cpp
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@ -34,34 +34,6 @@ bool ExpandConvTransLayer::init(const LayerMap &layerMap,
return true;
}
// Why this is necessary after calling init?
size_t ExpandConvTransLayer::getSize() {
CHECK_NE(inputLayers_.size(), 0UL);
imgSizeH_.clear();
imgSizeW_.clear();
outputH_.clear();
outputW_.clear();
subN_.clear();
size_t layerSize = 0;
for (size_t i = 0; i < inputLayers_.size(); i++) {
outputH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
outputW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
if (outputH_[i] == 0) outputH_[i] = outputX_[i];
if (outputW_[i] == 0) outputW_[i] = outputX_[i];
imgSizeH_.push_back(
imageSize(outputH_[i], filterSize_[i], padding_[i], stride_[i]));
imgSizeW_.push_back(
imageSize(outputW_[i], filterSize_[i], padding_[i], stride_[i]));
subN_.push_back(outputH_[i] * outputW_[i]);
CHECK(layerSize == 0 ||
imgSizeH_[i] * imgSizeW_[i] * (size_t)numFilters_ == layerSize);
layerSize = imgSizeH_[i] * imgSizeW_[i] * numFilters_;
}
getOutput().setFrameHeight(imgSizeH_[0]);
getOutput().setFrameWidth(imgSizeW_[0]);
return layerSize;
}
void ExpandConvTransLayer::forward(PassType passType) {
Layer::forward(passType);
@ -69,7 +41,7 @@ void ExpandConvTransLayer::forward(PassType passType) {
/* note: one sample correspond to one colum, and the
* transOutValue correspond sample to one row */
int batchSize = inputLayers_[0]->getOutputValue()->getHeight();
resetOutput(batchSize, getSize());
resetOutput(batchSize, getOutputSize());
MatrixPtr output = nullptr;
for (size_t i = 0; i < inputLayers_.size(); ++i) {

2
paddle/gserver/layers/ExpandConvTransLayer.h
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@ -37,8 +37,6 @@ public:
bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
size_t getSize();
void forward(PassType passType);
void backward(const UpdateCallback& callback);
};

8
paddle/gserver/tests/test_ConvTrans.cpp
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@ -43,11 +43,11 @@ TEST(Layer, convTransLayerFwd) {
configt.layerConfig.set_partial_sum(1);
configt.layerConfig.set_shared_biases(true);
configt.inputDefs.push_back({INPUT_DATA, "layer_0", 1024, 288});
configt.inputDefs.push_back({INPUT_DATA, "layer_0", 1024, 384});
LayerInputConfig* input = configt.layerConfig.add_inputs();
ConvConfig* conv = input->mutable_conv_conf();
conv->set_filter_size(2);
conv->set_filter_size_y(3);
conv->set_filter_size_y(4);
conv->set_channels(16);
conv->set_padding(0);
conv->set_padding_y(1);
@ -86,11 +86,11 @@ TEST(Layer, convTransLayerFwd) {
config.layerConfig.set_partial_sum(1);
config.layerConfig.set_shared_biases(true);
config.inputDefs.push_back({INPUT_DATA, "layer_1", 768, 288});
config.inputDefs.push_back({INPUT_DATA, "layer_1", 768, 384});
input = config.layerConfig.add_inputs();
conv = input->mutable_conv_conf();
conv->set_filter_size(2);
conv->set_filter_size_y(3);
conv->set_filter_size_y(4);
conv->set_channels(3);
conv->set_padding(0);
conv->set_padding_y(1);

12
python/paddle/trainer/config_parser.py
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@ -1670,11 +1670,13 @@ class ConvTransLayerBase(LayerBase):
if self.layer_type == "cudnn_convt":
config_assert(use_gpu, "cudnn_convt only support GPU")
if (use_gpu == 1 and self.layer_type != "exconvt" and
(parallel_nn == 0 or self.config.device > -1)):
self.layer_type = "cudnn_convt"
else:
self.layer_type = "exconvt"
# if (use_gpu == 1 and self.layer_type != "exconvt" and
# (parallel_nn == 0 or self.config.device > -1)):
# self.layer_type = "cudnn_convt"
# else:
# self.layer_type = "exconvt"
# cudnn_convt has not been implemented so use exconvt only
self.layer_type = "exconvt"
# need to specify layer in config
self.config.type = self.layer_type

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