Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix_prelu
xzl
8 years ago
commit
c1b23535c0
@ -0,0 +1,109 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "MaxPoolWithMaskLayer.h"
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#include "paddle/utils/Logging.h"
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#include "paddle/utils/Stat.h"
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namespace paddle {
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bool MaxPoolWithMaskLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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PoolLayer::init(layerMap, parameterMap);
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setOutput("mask", &mask_);
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return true;
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}
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size_t MaxPoolWithMaskLayer::getSize() {
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CHECK_EQ(inputLayers_.size(), 1UL);
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size_t layerSize = 0;
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outputY_ = outputSize(imgSizeY_,
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sizeY_,
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confPaddingY_,
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strideY_,
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/* caffeMode */ false);
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outputX_ = outputSize(imgSize_,
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sizeX_,
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confPadding_,
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stride_,
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/* caffeMode */ false);
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layerSize = outputX_ * outputY_ * channels_;
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getOutput().setFrameHeight(outputY_);
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getOutput().setFrameWidth(outputX_);
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return layerSize;
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}
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void MaxPoolWithMaskLayer::forward(PassType passType) {
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size_t size = getSize();
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MatrixPtr inputV = inputLayers_[0]->getOutputValue();
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int batchSize = inputV->getHeight();
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resetOutput(batchSize, size);
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MatrixPtr outV = getOutputValue();
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CHECK_EQ(size, outV->getWidth());
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resetSpecifyOutput(mask_,
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batchSize,
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size,
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/* isValueClean */ false,
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/* isGradClean */ true);
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MatrixPtr maskV = mask_.value;
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outV->maxPoolForward(*inputV,
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imgSizeY_,
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imgSize_,
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channels_,
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sizeX_,
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sizeY_,
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strideY_,
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stride_,
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outputY_,
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outputX_,
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confPaddingY_,
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confPadding_,
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maskV);
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}
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void MaxPoolWithMaskLayer::backward(const UpdateCallback& callback) {
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(void)callback;
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if (NULL == getInputGrad(0)) {
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return;
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}
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MatrixPtr outGrad = getOutputGrad();
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MatrixPtr inputV = inputLayers_[0]->getOutputValue();
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MatrixPtr outV = getOutputValue();
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MatrixPtr inputGrad = inputLayers_[0]->getOutputGrad();
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inputGrad->maxPoolBackward(*inputV,
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imgSizeY_,
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imgSize_,
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*outGrad,
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*outV,
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sizeX_,
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sizeY_,
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strideY_,
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stride_,
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outputY_,
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outputX_,
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1,
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1,
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confPaddingY_,
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confPadding_);
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}
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} // namespace paddle
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@ -0,0 +1,40 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include <vector>
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#include "PoolLayer.h"
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#include "paddle/math/Matrix.h"
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namespace paddle {
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/**
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* @brief Basic parent layer of different kinds of pooling
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*/
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class MaxPoolWithMaskLayer : public PoolLayer {
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protected:
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Argument mask_;
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public:
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explicit MaxPoolWithMaskLayer(const LayerConfig& config)
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: PoolLayer(config) {}
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size_t getSize();
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void forward(PassType passType) override;
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void backward(const UpdateCallback& callback = nullptr) override;
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bool init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) override;
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};
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} // namespace paddle
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@ -0,0 +1,117 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <gtest/gtest.h>
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#include <string>
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#include <vector>
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#include "LayerGradUtil.h"
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#include "paddle/math/MathUtils.h"
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#include "paddle/testing/TestUtil.h"
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using namespace paddle;
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void setPoolConfig(TestConfig* config,
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PoolConfig* pool,
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const string& poolType) {
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(*config).biasSize = 0;
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(*config).layerConfig.set_type("pool");
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(*config).layerConfig.set_num_filters(1);
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int kw = 3, kh = 3;
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int pw = 0, ph = 0;
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int sw = 2, sh = 2;
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pool->set_pool_type(poolType);
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pool->set_channels(1);
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pool->set_size_x(kw);
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pool->set_size_y(kh);
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pool->set_start(0);
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pool->set_padding(pw);
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pool->set_padding_y(ph);
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pool->set_stride(sw);
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pool->set_stride_y(sh);
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int ow = outputSize(pool->img_size(), kw, pw, sw, /* caffeMode */ false);
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int oh = outputSize(pool->img_size_y(), kh, ph, sh, /* caffeMode */ false);
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pool->set_output_x(ow);
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pool->set_output_y(oh);
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}
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void doOneMaxPoolingWithMaskOutputTest(MatrixPtr& inputMat,
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const string& poolType,
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bool use_gpu,
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MatrixPtr& maskMat) {
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TestConfig config;
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config.inputDefs.push_back({INPUT_DATA, "layer_0", 25, 0});
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LayerInputConfig* input = config.layerConfig.add_inputs();
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PoolConfig* pool = input->mutable_pool_conf();
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pool->set_img_size(5);
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pool->set_img_size_y(5);
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setPoolConfig(&config, pool, poolType);
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config.layerConfig.set_size(pool->output_x() * pool->output_y() *
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pool->channels());
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config.layerConfig.set_name("MaxPoolWithMask");
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std::vector<DataLayerPtr> dataLayers;
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LayerMap layerMap;
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vector<Argument> datas;
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initDataLayer(config,
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&dataLayers,
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&datas,
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&layerMap,
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"MaxPoolWithMask",
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1,
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false,
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use_gpu);
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dataLayers[0]->getOutputValue()->copyFrom(*inputMat);
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FLAGS_use_gpu = use_gpu;
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std::vector<ParameterPtr> parameters;
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LayerPtr maxPoolingWithMaskOutputLayer;
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initTestLayer(config, &layerMap, ¶meters, &maxPoolingWithMaskOutputLayer);
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maxPoolingWithMaskOutputLayer->forward(PASS_GC);
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checkMatrixEqual(maxPoolingWithMaskOutputLayer->getOutput("mask").value,
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maskMat);
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}
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TEST(Layer, maxPoolingWithMaskOutputLayerFwd) {
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bool useGpu = false;
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MatrixPtr inputMat;
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MatrixPtr maskMat;
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real inputData[] = {0.1, 0.1, 0.5, 0.5, 1.1, 0.2, 0.2, 0.6, 0.1,
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0.1, 0.3, 0.3, 0.7, 0.1, 0.1, 0.4, 0.4, 0.8,
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0.8, 0.1, 1.0, 2.0, 3.0, 0.0, 9.0};
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real maskData[] = {12, 4, 22, 24};
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inputMat = Matrix::create(1, 25, false, useGpu);
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maskMat = Matrix::create(1, 4, false, useGpu);
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inputMat->setData(inputData);
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maskMat->setData(maskData);
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doOneMaxPoolingWithMaskOutputTest(
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inputMat, "max-pool-with-mask", useGpu, maskMat);
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#ifdef PADDLE_WITH_CUDA
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useGpu = true;
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inputMat = Matrix::create(1, 25, false, useGpu);
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maskMat = Matrix::create(1, 4, false, useGpu);
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inputMat->copyFrom(inputData, 25);
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maskMat->copyFrom(maskData, 4);
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doOneMaxPoolingWithMaskOutputTest(
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inputMat, "max-pool-with-mask", useGpu, maskMat);
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#endif
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}
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