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164 lines
4.9 KiB
164 lines
4.9 KiB
/* 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 "Layer.h"
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#include "paddle/math/Matrix.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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/**
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* @brief A layer for computing cosine similarity between a vector
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* and each row of a matrix
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* out[i] = cos_scale * cos(in1, in2(i,:));
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* @note used in NEURAL TURING MACHINE
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*
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* Input1: a vector (batchSize * dataDim)
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*
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* Input2: a matrix in vector form (batchSize * (weightDim*dataDim))
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*
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* Output: a vector (batchSize * weightDim)
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*/
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class CosSimVecMatLayer : public Layer {
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protected:
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MatrixPtr tmpMtx0;
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MatrixPtr tmpMtx1;
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MatrixPtr tmpRow0;
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MatrixPtr tmpRow1;
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MatrixPtr tmpRow2;
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MatrixPtr tmpRow3;
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public:
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explicit CosSimVecMatLayer(const LayerConfig& config) : Layer(config) {}
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~CosSimVecMatLayer() {}
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bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
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void forward(PassType passType);
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void backward(const UpdateCallback& callback = nullptr);
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};
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REGISTER_LAYER(cos_vm, CosSimVecMatLayer);
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bool CosSimVecMatLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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Layer::init(layerMap, parameterMap);
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CHECK_EQ(inputLayers_.size(), 2U);
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size_t dataDim = inputLayers_[0]->getSize();
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size_t numKeys = getSize();
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size_t memoryDim = inputLayers_[1]->getSize();
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CHECK_EQ(dataDim * numKeys, memoryDim) << "Dimension mismatch";
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tmpRow0 = Matrix::create(nullptr,
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/* height= */ 1,
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dataDim,
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/* trans= */ false,
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useGpu_);
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tmpRow1 = Matrix::create(nullptr,
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/* height= */ 1,
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dataDim,
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/* trans= */ false,
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useGpu_);
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tmpRow2 = Matrix::create(nullptr,
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/* height= */ numKeys,
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1,
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/* trans= */ false,
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useGpu_);
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tmpRow3 = Matrix::create(nullptr,
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/* height= */ numKeys,
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1,
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/* trans= */ false,
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useGpu_);
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tmpMtx0 = Matrix::create(nullptr,
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/* height= */ numKeys,
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dataDim,
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/* trans= */ false,
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useGpu_);
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tmpMtx1 = Matrix::create(nullptr,
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/* height= */ numKeys,
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dataDim,
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/* trans= */ false,
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useGpu_);
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return true;
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}
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void CosSimVecMatLayer::forward(PassType passType) {
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Layer::forward(passType);
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MatrixPtr inV0 = getInputValue(0);
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MatrixPtr inV1 = getInputValue(1);
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size_t batchSize = inV0->getHeight();
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size_t numKeys = getSize();
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CHECK_EQ(batchSize, inV1->getHeight());
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{
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REGISTER_TIMER_INFO("FwResetTimer", getName().c_str());
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reserveOutput(batchSize, numKeys);
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}
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MatrixPtr outV = getOutputValue();
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REGISTER_TIMER_INFO("FwCosVMTimer", getName().c_str());
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for (size_t i = 0; i < batchSize; i++) {
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tmpRow0->setData(inV0->rowBuf(i));
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tmpMtx0->setData(inV1->rowBuf(i));
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tmpRow2->setData(outV->rowBuf(i));
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tmpRow2->cosSim(*(tmpMtx0), *(tmpRow0), config_.cos_scale());
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}
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}
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void CosSimVecMatLayer::backward(const UpdateCallback& callback) {
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MatrixPtr inV0 = getInputValue(0);
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MatrixPtr inV1 = getInputValue(1);
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MatrixPtr inG0 = getInputGrad(0);
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MatrixPtr inG1 = getInputGrad(1);
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MatrixPtr outV = getOutputValue();
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MatrixPtr outG = getOutputGrad();
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size_t batchSize = inV0->getHeight();
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REGISTER_TIMER_INFO("BwCosVMTimer", getName().c_str());
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if (inG0 && inG1) {
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for (size_t i = 0; i < batchSize; i++) {
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tmpRow0->setData(inV0->rowBuf(i));
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tmpRow1->setData(inG0->rowBuf(i));
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tmpMtx0->setData(inV1->rowBuf(i));
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tmpMtx1->setData(inG1->rowBuf(i));
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tmpRow2->setData(outV->rowBuf(i));
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tmpRow3->setData(outG->rowBuf(i));
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tmpRow3->cosSimDerivative(*(tmpRow2),
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*(tmpMtx0),
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*(tmpRow0),
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*(tmpMtx1),
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*(tmpRow1),
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config_.cos_scale());
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}
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} else {
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CHECK(!inG0 || !inG1) << "Not supported";
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}
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}
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} // namespace paddle
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