Zhaolong Xing
7 years ago
committed by
GitHub
commit
d02a68c447
@ -0,0 +1,108 @@
|
|||||||
|
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
|
||||||
|
|
||||||
|
Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
you may not use this file except in compliance with the License.
|
||||||
|
You may obtain a copy of the License at
|
||||||
|
|
||||||
|
http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
|
||||||
|
Unless required by applicable law or agreed to in writing, software
|
||||||
|
distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License. */
|
||||||
|
|
||||||
|
#include "UpsampleLayer.h"
|
||||||
|
#include "iostream"
|
||||||
|
|
||||||
|
namespace paddle {
|
||||||
|
|
||||||
|
REGISTER_LAYER(upsample, UpsampleLayer);
|
||||||
|
|
||||||
|
size_t UpsampleLayer::getOutputSize() {
|
||||||
|
if (upsampleSize_ == 0) {
|
||||||
|
upsampleSize_ = imgSize_ * scale_ - static_cast<int>(padOutX_);
|
||||||
|
upsampleSizeY_ = imgSizeY_ * scaleY_ - static_cast<int>(padOutY_);
|
||||||
|
}
|
||||||
|
return upsampleSize_ * upsampleSizeY_ * channels_;
|
||||||
|
}
|
||||||
|
|
||||||
|
bool UpsampleLayer::init(const LayerMap& layerMap,
|
||||||
|
const ParameterMap& parameterMap) {
|
||||||
|
Layer::init(layerMap, parameterMap);
|
||||||
|
|
||||||
|
CHECK_EQ(inputLayers_.size(), 2U);
|
||||||
|
CHECK_EQ(config_.inputs_size(), 2);
|
||||||
|
const auto& conf = config_.inputs(0).upsample_conf();
|
||||||
|
const auto& img_conf = conf.image_conf();
|
||||||
|
|
||||||
|
imgSizeY_ =
|
||||||
|
img_conf.has_img_size_y() ? img_conf.img_size_y() : img_conf.img_size();
|
||||||
|
imgSize_ = img_conf.img_size();
|
||||||
|
channels_ = img_conf.channels();
|
||||||
|
|
||||||
|
CHECK((conf.has_upsample_size()) || (conf.has_scale()))
|
||||||
|
<< "scale or upsample_size is required.";
|
||||||
|
|
||||||
|
if (conf.has_upsample_size()) {
|
||||||
|
upsampleSize_ = conf.upsample_size();
|
||||||
|
upsampleSizeY_ = upsampleSize_;
|
||||||
|
if (conf.has_upsample_size_y()) {
|
||||||
|
upsampleSizeY_ = conf.upsample_size_y();
|
||||||
|
}
|
||||||
|
} else {
|
||||||
|
if (!conf.has_scale_y()) {
|
||||||
|
scale_ = scaleY_ = conf.scale_y();
|
||||||
|
CHECK_GT(static_cast<int>(scale_), 1);
|
||||||
|
} else {
|
||||||
|
scale_ = conf.scale();
|
||||||
|
scaleY_ = conf.scale_y();
|
||||||
|
}
|
||||||
|
padOutX_ = conf.pad_out_x();
|
||||||
|
padOutY_ = conf.pad_out_y();
|
||||||
|
CHECK(!padOutX_ || scale_ == 2)
|
||||||
|
<< "Output height padding compensation requires scale_ == 2";
|
||||||
|
CHECK(!padOutY_ || scaleY_ == 2)
|
||||||
|
<< "Output width padding compensation requires scaleY_ == 2";
|
||||||
|
upsampleSize_ = upsampleSizeY_ = 0;
|
||||||
|
}
|
||||||
|
return true;
|
||||||
|
}
|
||||||
|
|
||||||
|
void UpsampleLayer::forward(PassType passType) {
|
||||||
|
Layer::forward(passType);
|
||||||
|
|
||||||
|
MatrixPtr input = getInputValue(0);
|
||||||
|
MatrixPtr mask = inputLayers_[1]->getOutput("mask").value;
|
||||||
|
|
||||||
|
size_t batchSize = input->getHeight();
|
||||||
|
size_t outSize = getOutputSize();
|
||||||
|
|
||||||
|
CHECK_EQ(input->getWidth(), mask->getWidth());
|
||||||
|
CHECK_EQ(mask->getHeight(), batchSize);
|
||||||
|
resetOutput(batchSize, outSize);
|
||||||
|
|
||||||
|
MatrixPtr output = getOutputValue();
|
||||||
|
output->upsampleForward(*input,
|
||||||
|
*mask,
|
||||||
|
imgSize_,
|
||||||
|
imgSizeY_,
|
||||||
|
channels_,
|
||||||
|
upsampleSize_,
|
||||||
|
upsampleSizeY_);
|
||||||
|
}
|
||||||
|
|
||||||
|
void UpsampleLayer::backward(const UpdateCallback& callback) {
|
||||||
|
MatrixPtr mask = inputLayers_[1]->getOutput("mask").value;
|
||||||
|
MatrixPtr inputGrad = getInputGrad(0);
|
||||||
|
MatrixPtr outputGrad = getOutputGrad();
|
||||||
|
inputGrad->upsampleBackward(*outputGrad,
|
||||||
|
*mask,
|
||||||
|
imgSize_,
|
||||||
|
imgSizeY_,
|
||||||
|
channels_,
|
||||||
|
upsampleSize_,
|
||||||
|
upsampleSizeY_);
|
||||||
|
}
|
||||||
|
|
||||||
|
} // namespace paddle
|
||||||
@ -0,0 +1,53 @@
|
|||||||
|
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
|
||||||
|
|
||||||
|
Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
you may not use this file except in compliance with the License.
|
||||||
|
You may obtain a copy of the License at
|
||||||
|
|
||||||
|
http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
|
||||||
|
Unless required by applicable law or agreed to in writing, software
|
||||||
|
distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License. */
|
||||||
|
|
||||||
|
#pragma once
|
||||||
|
|
||||||
|
#include <vector>
|
||||||
|
#include "Layer.h"
|
||||||
|
#include "paddle/math/Matrix.h"
|
||||||
|
#include "paddle/utils/Logging.h"
|
||||||
|
#include "paddle/utils/Stat.h"
|
||||||
|
|
||||||
|
namespace paddle {
|
||||||
|
|
||||||
|
/**
|
||||||
|
* This layer transpose the pooling process.
|
||||||
|
* It takes two input, the first input is the input data, and
|
||||||
|
* the second is the mask data from the max-pool-with-mask layer.
|
||||||
|
*
|
||||||
|
*/
|
||||||
|
|
||||||
|
class UpsampleLayer : public Layer {
|
||||||
|
public:
|
||||||
|
explicit UpsampleLayer(const LayerConfig& config) : Layer(config) {}
|
||||||
|
~UpsampleLayer() {}
|
||||||
|
|
||||||
|
bool init(const LayerMap& layerMap,
|
||||||
|
const ParameterMap& parameterMap) override;
|
||||||
|
|
||||||
|
void forward(PassType passType) override;
|
||||||
|
void backward(const UpdateCallback& callback) override;
|
||||||
|
|
||||||
|
size_t getOutputSize();
|
||||||
|
|
||||||
|
protected:
|
||||||
|
size_t scale_, scaleY_;
|
||||||
|
size_t upsampleSize_, upsampleSizeY_;
|
||||||
|
size_t padOutX_, padOutY_;
|
||||||
|
size_t imgSize_, imgSizeY_;
|
||||||
|
size_t channels_;
|
||||||
|
};
|
||||||
|
|
||||||
|
} // namespace paddle
|
||||||
@ -0,0 +1,152 @@
|
|||||||
|
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
|
||||||
|
|
||||||
|
Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
you may not use this file except in compliance with the License.
|
||||||
|
You may obtain a copy of the License at
|
||||||
|
|
||||||
|
http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
|
||||||
|
Unless required by applicable law or agreed to in writing, software
|
||||||
|
distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License. */
|
||||||
|
|
||||||
|
#include <gtest/gtest.h>
|
||||||
|
#include <string>
|
||||||
|
#include <vector>
|
||||||
|
|
||||||
|
#include "LayerGradUtil.h"
|
||||||
|
#include "paddle/math/MathUtils.h"
|
||||||
|
#include "paddle/testing/TestUtil.h"
|
||||||
|
|
||||||
|
using namespace paddle;
|
||||||
|
|
||||||
|
void setPoolConfig(TestConfig* config,
|
||||||
|
PoolConfig* pool,
|
||||||
|
const string& poolType) {
|
||||||
|
(*config).biasSize = 0;
|
||||||
|
(*config).layerConfig.set_type("pool");
|
||||||
|
(*config).layerConfig.set_num_filters(1);
|
||||||
|
|
||||||
|
int kw = 2, kh = 2;
|
||||||
|
int pw = 0, ph = 0;
|
||||||
|
int sw = 2, sh = 2;
|
||||||
|
pool->set_pool_type(poolType);
|
||||||
|
pool->set_channels(2);
|
||||||
|
pool->set_size_x(kw);
|
||||||
|
pool->set_size_y(kh);
|
||||||
|
pool->set_start(0);
|
||||||
|
pool->set_padding(pw);
|
||||||
|
pool->set_padding_y(ph);
|
||||||
|
pool->set_stride(sw);
|
||||||
|
pool->set_stride_y(sh);
|
||||||
|
|
||||||
|
int ow = outputSize(pool->img_size(), kw, pw, sw, /* caffeMode */ false);
|
||||||
|
int oh = outputSize(pool->img_size_y(), kh, ph, sh, /* caffeMode */ false);
|
||||||
|
pool->set_output_x(ow);
|
||||||
|
pool->set_output_y(oh);
|
||||||
|
}
|
||||||
|
|
||||||
|
LayerPtr doOneUpsampleTest(MatrixPtr& inputMat,
|
||||||
|
const string& poolType,
|
||||||
|
bool use_gpu,
|
||||||
|
real* tempGradData) {
|
||||||
|
/* prepare maxPoolWithMaskLayer */
|
||||||
|
TestConfig config;
|
||||||
|
config.inputDefs.push_back({INPUT_DATA, "layer_0", 128, 0});
|
||||||
|
LayerInputConfig* input = config.layerConfig.add_inputs();
|
||||||
|
PoolConfig* pool = input->mutable_pool_conf();
|
||||||
|
|
||||||
|
pool->set_img_size(8);
|
||||||
|
pool->set_img_size_y(8);
|
||||||
|
setPoolConfig(&config, pool, "max-pool-with-mask");
|
||||||
|
config.layerConfig.set_size(pool->output_x() * pool->output_y() *
|
||||||
|
pool->channels());
|
||||||
|
|
||||||
|
config.layerConfig.set_name("MaxPoolWithMask");
|
||||||
|
|
||||||
|
std::vector<DataLayerPtr> dataLayers;
|
||||||
|
LayerMap layerMap;
|
||||||
|
vector<Argument> datas;
|
||||||
|
|
||||||
|
initDataLayer(config,
|
||||||
|
&dataLayers,
|
||||||
|
&datas,
|
||||||
|
&layerMap,
|
||||||
|
"MaxPoolWithMask",
|
||||||
|
1,
|
||||||
|
false,
|
||||||
|
use_gpu);
|
||||||
|
|
||||||
|
dataLayers[0]->getOutputValue()->copyFrom(*inputMat);
|
||||||
|
|
||||||
|
FLAGS_use_gpu = use_gpu;
|
||||||
|
std::vector<ParameterPtr> parameters;
|
||||||
|
LayerPtr maxPoolingWithMaskOutputLayer;
|
||||||
|
initTestLayer(config, &layerMap, ¶meters, &maxPoolingWithMaskOutputLayer);
|
||||||
|
maxPoolingWithMaskOutputLayer->forward(PASS_GC);
|
||||||
|
|
||||||
|
/* prepare the upsample layer */
|
||||||
|
LayerConfig upsampleLayerConfig;
|
||||||
|
upsampleLayerConfig.set_type("upsample");
|
||||||
|
LayerInputConfig* input1 = upsampleLayerConfig.add_inputs();
|
||||||
|
upsampleLayerConfig.add_inputs();
|
||||||
|
|
||||||
|
UpsampleConfig* upsampleConfig = input1->mutable_upsample_conf();
|
||||||
|
upsampleConfig->set_scale(2);
|
||||||
|
ImageConfig* imageConfig = upsampleConfig->mutable_image_conf();
|
||||||
|
imageConfig->set_channels(2);
|
||||||
|
imageConfig->set_img_size(4);
|
||||||
|
imageConfig->set_img_size_y(4);
|
||||||
|
upsampleLayerConfig.set_size(2 * 8 * 8);
|
||||||
|
upsampleLayerConfig.set_name("upsample");
|
||||||
|
|
||||||
|
for (size_t i = 0; i < 2; i++) {
|
||||||
|
LayerInputConfig& inputTemp = *(upsampleLayerConfig.mutable_inputs(i));
|
||||||
|
inputTemp.set_input_layer_name("MaxPoolWithMask");
|
||||||
|
}
|
||||||
|
|
||||||
|
LayerPtr upsampleLayer;
|
||||||
|
ParameterMap parameterMap;
|
||||||
|
upsampleLayer = Layer::create(upsampleLayerConfig);
|
||||||
|
layerMap[upsampleLayerConfig.name()] = upsampleLayer;
|
||||||
|
upsampleLayer->init(layerMap, parameterMap);
|
||||||
|
upsampleLayer->setNeedGradient(true);
|
||||||
|
upsampleLayer->forward(PASS_GC);
|
||||||
|
upsampleLayer->getOutputGrad()->copyFrom(tempGradData, 128);
|
||||||
|
upsampleLayer->backward();
|
||||||
|
|
||||||
|
return upsampleLayer;
|
||||||
|
}
|
||||||
|
|
||||||
|
TEST(Layer, maxPoolingWithMaskOutputLayerFwd) {
|
||||||
|
bool useGpu = false;
|
||||||
|
MatrixPtr inputMat;
|
||||||
|
MatrixPtr inputGPUMat;
|
||||||
|
MatrixPtr tempGradMat;
|
||||||
|
|
||||||
|
inputMat = Matrix::create(1, 128, false, useGpu);
|
||||||
|
inputMat->randomizeUniform();
|
||||||
|
|
||||||
|
tempGradMat = Matrix::create(1, 128, false, useGpu);
|
||||||
|
tempGradMat->randomizeUniform();
|
||||||
|
real* data = inputMat->getData();
|
||||||
|
real* tempGradData = tempGradMat->getData();
|
||||||
|
|
||||||
|
LayerPtr upsampleLayerCPU =
|
||||||
|
doOneUpsampleTest(inputMat, "max-pool-with-mask", useGpu, tempGradData);
|
||||||
|
|
||||||
|
#ifdef PADDLE_WITH_CUDA
|
||||||
|
useGpu = true;
|
||||||
|
inputGPUMat = Matrix::create(1, 128, false, useGpu);
|
||||||
|
inputGPUMat->copyFrom(data, 128);
|
||||||
|
LayerPtr upsampleLayerGPU = doOneUpsampleTest(
|
||||||
|
inputGPUMat, "max-pool-with-mask", useGpu, tempGradData);
|
||||||
|
checkMatrixEqual(upsampleLayerCPU->getOutput("").value,
|
||||||
|
upsampleLayerGPU->getOutput("").value);
|
||||||
|
|
||||||
|
checkMatrixEqual(upsampleLayerCPU->getPrev(0)->getOutputGrad(),
|
||||||
|
upsampleLayerGPU->getPrev(0)->getOutputGrad());
|
||||||
|
#endif
|
||||||
|
}
|
||||||
Loading…
Reference in new issue