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Merge pull request #3367 from lcy-seso/add_sequence_slice_layer
Add a sequence slice layer.
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| /* 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. */ | ||
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| #include "Layer.h" | ||
| #include "paddle/math/Matrix.h" | ||
| #include "paddle/math/Vector.h" | ||
| #include "paddle/utils/Logging.h" | ||
| #include "paddle/utils/Stat.h" | ||
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| namespace paddle { | ||
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| class SequenceSliceLayer : public Layer { | ||
| public: | ||
| explicit SequenceSliceLayer(const LayerConfig& config) : Layer(config) {} | ||
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| bool init(const LayerMap& layerMap, | ||
| const ParameterMap& parameterMap) override; | ||
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| void forward(PassType passType) override; | ||
| void backward(const UpdateCallback& callback = nullptr) override; | ||
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| private: | ||
| /* | ||
| * TODO(caoying) | ||
| * In PaddePaddle, currently all matrices are real number types, | ||
| * but the second and the (optional) third input which are some | ||
| * selected indices of the give sequence to trim the sequence, are actually | ||
| * filled with int types so that storing int types information in real number | ||
| * matrices is very dangerous, since real numbers will be convered to int | ||
| * types. If a user fills this matrix himself, invalid data may occor. | ||
| */ | ||
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| MatrixPtr startIdsOnCpu_; | ||
| MatrixPtr endIdsOnCpu_; | ||
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| std::vector<int> selectedRows_; | ||
| IVectorPtr rowIndice_; | ||
| std::vector<std::vector<int>> inputSeqInfoVec_; | ||
| std::vector<int> outSubSeqStartPos_; | ||
| std::vector<int> outSeqStartPos_; | ||
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| void checkInputs(); | ||
| void copySliceIdsToCpu(); | ||
| void calSelectedRows(const MatrixPtr starts, const MatrixPtr ends); | ||
| }; | ||
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| REGISTER_LAYER(seq_slice, SequenceSliceLayer); | ||
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| bool SequenceSliceLayer::init(const LayerMap& layerMap, | ||
| const ParameterMap& parameterMap) { | ||
| /* Initialize the basic parent class */ | ||
| Layer::init(layerMap, parameterMap); | ||
| CHECK_GE(inputLayers_.size(), 2U); | ||
| CHECK_LE(inputLayers_.size(), 3U); | ||
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| setNeedSequenceInfo(false); | ||
| return true; | ||
| } | ||
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| void SequenceSliceLayer::checkInputs() { | ||
| const Argument& inputSeq = getInput(0); | ||
| CHECK(inputSeq.hasSeq()) << "The first input of sequence slice layer " | ||
| << "must be a sequence."; | ||
| const MatrixPtr indices1 = getInputValue(1); | ||
| CHECK_EQ(static_cast<size_t>(indices1->getHeight()), | ||
| inputSeq.hasSubseq() ? inputSeq.getNumSubSequences() | ||
| : inputSeq.getNumSequences()) | ||
| << "Height of the second input should be equal to number of sequence " | ||
| << "in the first input."; | ||
| if (inputLayers_.size() == 3) { | ||
| const MatrixPtr indices2 = getInputValue(2); | ||
| CHECK_EQ(indices2->getHeight(), indices1->getHeight()) | ||
| << "start indices and end indices should have the same height."; | ||
| CHECK_EQ(indices2->getWidth(), indices1->getWidth()) | ||
| << "start indices and end indices should have the same Width."; | ||
| } | ||
| } | ||
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| void SequenceSliceLayer::copySliceIdsToCpu() { | ||
| const MatrixPtr indices1 = getInputValue(1); | ||
| if (inputLayers_.size() == 2U) { | ||
| if (config_.select_first()) { | ||
| Matrix::resizeOrCreate(startIdsOnCpu_, | ||
| indices1->getHeight(), | ||
| indices1->getWidth(), | ||
| false /* trans */, | ||
| false /* useGpu */); | ||
| startIdsOnCpu_->copyFrom(*indices1); | ||
| endIdsOnCpu_ = nullptr; | ||
| } else { | ||
| Matrix::resizeOrCreate(endIdsOnCpu_, | ||
| indices1->getHeight(), | ||
| indices1->getWidth(), | ||
| false /* trans */, | ||
| false /* useGpu */); | ||
| endIdsOnCpu_->copyFrom(*indices1); | ||
| startIdsOnCpu_ = nullptr; | ||
| } | ||
| } else if (inputLayers_.size() == 3U) { | ||
| Matrix::resizeOrCreate(startIdsOnCpu_, | ||
| indices1->getHeight(), | ||
| indices1->getWidth(), | ||
| false /* trans */, | ||
| false /* useGpu */); | ||
| startIdsOnCpu_->copyFrom(*indices1); | ||
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| const MatrixPtr indices2 = getInputValue(2); | ||
| Matrix::resizeOrCreate(endIdsOnCpu_, | ||
| indices2->getHeight(), | ||
| indices2->getWidth(), | ||
| false /* trans */, | ||
| false /* useGpu */); | ||
| endIdsOnCpu_->copyFrom(*indices2); | ||
| } | ||
| } | ||
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| void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, | ||
| const MatrixPtr ends) { | ||
| CHECK(starts || ends) << "At least one of the start or end indices " | ||
| << "should be given."; | ||
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| outSeqStartPos_.resize(1, 0); | ||
| outSubSeqStartPos_.resize(1, 0); | ||
| selectedRows_.clear(); | ||
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| size_t beamSize = starts ? starts->getWidth() : ends->getWidth(); | ||
| size_t rowIdx = 0; | ||
| for (size_t i = 0; i < inputSeqInfoVec_.size(); ++i) { | ||
| for (size_t j = 0; j < inputSeqInfoVec_[i].size() - 1; ++j) { | ||
| for (size_t k = 0; k < beamSize; ++k) { | ||
| if (starts && starts->getElement(rowIdx, k) == -1.) break; | ||
| if (ends && ends->getElement(rowIdx, k) == -1.) break; | ||
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| int begPos = inputSeqInfoVec_[i][j]; | ||
| if (starts) begPos += starts->getElement(rowIdx, k); | ||
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| int endPos = inputSeqInfoVec_[i][j + 1] - 1; | ||
| if (ends) endPos = inputSeqInfoVec_[i][j] + ends->getElement(rowIdx, k); | ||
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| int seqLen = endPos - begPos + 1; | ||
| CHECK_GT(seqLen, 0U); | ||
| for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m); | ||
| inputSeqInfoVec_.size() > 1 | ||
| ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen) | ||
| : outSeqStartPos_.push_back(outSeqStartPos_.back() + seqLen); | ||
| } | ||
| rowIdx++; | ||
| } | ||
| if (inputSeqInfoVec_.size() > 1) | ||
| outSeqStartPos_.push_back(outSubSeqStartPos_.back()); | ||
| } | ||
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| if (useGpu_) { | ||
| rowIndice_ = IVector::create(selectedRows_.size(), useGpu_); | ||
| rowIndice_->copyFrom(selectedRows_.data(), selectedRows_.size()); | ||
| } else { | ||
| rowIndice_ = | ||
| IVector::create(selectedRows_.data(), selectedRows_.size(), useGpu_); | ||
| } | ||
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| // create the sequence information for the output. | ||
| ICpuGpuVector::resizeOrCreate( | ||
| output_.sequenceStartPositions, outSeqStartPos_.size(), false); | ||
| output_.sequenceStartPositions->copyFrom( | ||
| outSeqStartPos_.data(), outSeqStartPos_.size(), false); | ||
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| if (inputSeqInfoVec_.size() > 1) { | ||
| ICpuGpuVector::resizeOrCreate( | ||
| output_.subSequenceStartPositions, outSubSeqStartPos_.size(), false); | ||
| output_.subSequenceStartPositions->copyFrom( | ||
| outSubSeqStartPos_.data(), outSubSeqStartPos_.size(), false); | ||
| } | ||
| } | ||
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| void SequenceSliceLayer::forward(PassType passType) { | ||
| Layer::forward(passType); | ||
| checkInputs(); | ||
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| const Argument& inputSeq = getInput(0); | ||
| inputSeqInfoVec_.clear(); | ||
| Argument::reorganizeSeqInfo(inputSeq.sequenceStartPositions, | ||
| inputSeq.subSequenceStartPositions, | ||
| inputSeqInfoVec_); | ||
| if (!useGpu_) { | ||
| if (inputLayers_.size() == 2U) { | ||
| startIdsOnCpu_ = config_.select_first() ? getInputValue(1) : nullptr; | ||
| endIdsOnCpu_ = config_.select_first() ? nullptr : getInputValue(1); | ||
| } else if (inputLayers_.size() == 3U) { | ||
| startIdsOnCpu_ = getInputValue(1); | ||
| endIdsOnCpu_ = getInputValue(2); | ||
| } | ||
| } else | ||
| copySliceIdsToCpu(); | ||
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| // calculate the selected row indices in a batch, | ||
| // and build the output sequence information. | ||
| calSelectedRows(startIdsOnCpu_ ? startIdsOnCpu_ : nullptr, | ||
| endIdsOnCpu_ ? endIdsOnCpu_ : nullptr); | ||
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| resetOutput(selectedRows_.size(), getSize()); | ||
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| getOutputValue()->selectRows(*getInputValue(0), *rowIndice_); | ||
| } | ||
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| void SequenceSliceLayer::backward(const UpdateCallback& callback) { | ||
| getOutputGrad()->addToRows(*getInputGrad(0), *rowIndice_); | ||
| } | ||
|
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| } // namespace paddle |
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