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https://github.com/marian-nmt/marian.git
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don't use shuffle
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parent
f044b8dfbb
commit
88678e59bc
24
src/sgd.cu
24
src/sgd.cu
@ -21,7 +21,7 @@ SGD::SGD(Expr& cost_func, Expr& inX, Expr& inY,
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yData_(yData),
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numClasses_(numClasses),
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epochs_(epochs),
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batchSize_(batchSize)
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maxBatchSize_(batchSize)
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{}
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void SGD::Run()
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@ -29,28 +29,28 @@ void SGD::Run()
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std::srand ( unsigned ( std::time(0) ) );
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size_t numExamples = xData_.size()/ numFeatures_;
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Tensor xt({(int)batchSize_, (int)numExamples}, 0.0f);
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Tensor yt({(int)batchSize_, (int)numClasses_}, 0.0f);
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Tensor xt({(int)maxBatchSize_, (int)numExamples}, 0.0f);
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Tensor yt({(int)maxBatchSize_, (int)numClasses_}, 0.0f);
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vector<size_t> shuffle = CreateShuffle(numExamples);
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for (size_t numEpoch = 0; numEpoch < epochs_; ++numEpoch) {
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std::cerr << "Starting epoch #" << numEpoch << std::endl;
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size_t startId = 0;
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size_t endId = startId + batchSize_;
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size_t endId = startId + maxBatchSize_;
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while (endId < numExamples) {
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PrepareBatch(startId, batchSize_, shuffle, xt, yt);
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PrepareBatch(startId, endId, maxBatchSize_, shuffle, xt, yt);
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*inX_ = xt;
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*inY_ = yt;
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cost_function_->forward(batchSize_);
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cost_function_->forward(maxBatchSize_);
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cost_function_->backward();
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UpdateModel();
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startId += batchSize_;
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endId += batchSize_;
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startId += maxBatchSize_;
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endId += maxBatchSize_;
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}
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}
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}
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@ -69,23 +69,23 @@ std::vector<size_t> SGD::CreateShuffle(size_t numExamples) const {
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void SGD::PrepareBatch(
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size_t startId,
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size_t endId,
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size_t batchSize,
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const std::vector<size_t> &shuffle,
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Tensor& xt,
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Tensor& yt) {
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/*
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std::vector<float> x(xData_.begin() + startId * numFeatures_,
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xData_.begin() + endId * numFeatures_);
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std::vector<float> y(yData_.begin() + startId * numClasses_,
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yData_.begin() + endId * numClasses_);
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*/
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/*
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std::vector<float> x(batchSize * numFeatures_);
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std::vector<float> y(batchSize * numClasses_);
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std::vector<float>::iterator startXIter = x.begin();
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std::vector<float>::iterator startYIter = y.begin();
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size_t endId = startId + batchSize;
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for (size_t i = startId; i < endId; ++i) {
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size_t startXDataId = i * numFeatures_;
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size_t startYDataId = i * numClasses_;
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@ -104,7 +104,7 @@ void SGD::PrepareBatch(
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startXIter += batchSize * numFeatures_;
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startYIter += batchSize * numClasses_;
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}
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*/
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xt.set(x);
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yt.set(y);
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}
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@ -30,11 +30,12 @@ class SGD {
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std::vector<float>& yData_;
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const size_t numClasses_;
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const size_t epochs_;
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const size_t batchSize_;
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const size_t maxBatchSize_;
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std::vector<size_t> CreateShuffle(size_t numExamples) const;
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void PrepareBatch(
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size_t startId,
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size_t endId,
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size_t batchSize,
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const std::vector<size_t> &shuffle,
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Tensor& xt,
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