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https://github.com/marian-nmt/marian.git
synced 2024-09-11 06:15:56 +03:00
move cuda device into graph. Add EOS, padding, UNK to vocab
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728ca05152
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2965bde889
@ -37,5 +37,14 @@ std::string Expr::Debug() const
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strm << marian::Debug(shape);
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return strm.str();
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}
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///////////////////////////////////////////////////////
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ExpressionGraph::ExpressionGraph(int cudaDevice)
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: stack_(new ChainableStack)
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{
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std::srand (time(NULL));
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cudaSetDevice(0);
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}
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}
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@ -38,9 +38,7 @@ class Expr {
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class ExpressionGraph {
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public:
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ExpressionGraph()
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: stack_(new ChainableStack)
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{}
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ExpressionGraph(int cudaDevice);
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void forward(size_t batchSize) {
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for(auto&& v : *stack_) {
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@ -23,8 +23,6 @@ SGD::SGD(ExpressionGraph& g, float eta,
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void SGD::Run()
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{
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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)maxBatchSize_, (int)numExamples}, 0.0f);
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Tensor yt({(int)maxBatchSize_, (int)numClasses_}, 0.0f);
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@ -4,7 +4,6 @@
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#include "vocab.h"
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int main(int argc, char** argv) {
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cudaSetDevice(0);
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using namespace std;
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using namespace marian;
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@ -22,7 +21,7 @@ int main(int argc, char** argv) {
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std::vector<Expr> Y;
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std::vector<Expr> H;
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ExpressionGraph g;
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ExpressionGraph g(0);
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for (int t = 0; t < num_inputs; ++t) {
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X.emplace_back(g.input(shape={batch_size, input_size}));
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@ -16,7 +16,7 @@ int main(int argc, char** argv) {
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using namespace marian;
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using namespace keywords;
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ExpressionGraph g;
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ExpressionGraph g(0);
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Expr x = named(g.input(shape={whatevs, IMAGE_SIZE}), "x");
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Expr y = named(g.input(shape={whatevs, LABEL_SIZE}), "y");
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@ -10,7 +10,7 @@ const size_t IMAGE_SIZE = 784;
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const size_t LABEL_SIZE = 10;
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int BATCH_SIZE = 10000;
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ExpressionGraph build_graph() {
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ExpressionGraph build_graph(int cudaDevice) {
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std::cerr << "Loading model params...";
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NpzConverter converter("../scripts/test_model_single/model.npz");
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@ -22,7 +22,7 @@ ExpressionGraph build_graph() {
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std::cerr << "Building model...";
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ExpressionGraph g;
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ExpressionGraph g(cudaDevice);
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auto x = named(g.input(shape={whatevs, IMAGE_SIZE}), "x");
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auto y = named(g.input(shape={whatevs, LABEL_SIZE}), "y");
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@ -46,15 +46,12 @@ ExpressionGraph build_graph() {
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}
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int main(int argc, char** argv) {
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cudaSetDevice(1);
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std::cerr << "Loading test set...";
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std::vector<float> testImages = datasets::mnist::ReadImages("../examples/mnist/t10k-images-idx3-ubyte", BATCH_SIZE, IMAGE_SIZE);
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std::vector<float> testLabels = datasets::mnist::ReadLabels("../examples/mnist/t10k-labels-idx1-ubyte", BATCH_SIZE, LABEL_SIZE);
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std::cerr << "Done." << std::endl;
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ExpressionGraph g = build_graph();
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ExpressionGraph g = build_graph(1);
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Tensor xt({BATCH_SIZE, IMAGE_SIZE});
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Tensor yt({BATCH_SIZE, LABEL_SIZE});
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@ -7,9 +7,7 @@ using namespace marian;
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using namespace keywords;
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int main(int argc, char** argv) {
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cudaSetDevice(0);
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const size_t IMAGE_SIZE = 784;
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const size_t LABEL_SIZE = 10;
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const size_t BATCH_SIZE = 24;
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@ -59,7 +57,7 @@ int main(int argc, char** argv) {
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std::cerr << "\tDone." << std::endl;
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ExpressionGraph g;
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ExpressionGraph g(0);
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auto x = g.input(shape={whatevs, IMAGE_SIZE}, name="X");
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auto y = g.input(shape={whatevs, LABEL_SIZE}, name="Y");
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@ -24,6 +24,21 @@ inline std::vector<std::string> Tokenize(const std::string& str,
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return tokens;
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}
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////////////////////////////////////////////////////////
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size_t Vocab::GetUNK() const
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{
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return std::numeric_limits<size_t>::max();
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}
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size_t Vocab::GetPad() const
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{
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return std::numeric_limits<size_t>::max() - 1;
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}
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size_t Vocab::GetEOS() const
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{
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return std::numeric_limits<size_t>::max() - 2;
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}
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size_t Vocab::GetOrCreate(const std::string &word)
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{
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@ -10,6 +10,9 @@ public:
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size_t GetOrCreate(const std::string &word);
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std::vector<size_t> ProcessSentence(const std::string &sentence);
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size_t GetUNK() const;
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size_t GetPad() const;
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size_t GetEOS() const;
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protected:
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typedef std::unordered_map<std::string, size_t> Coll;
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Coll coll_;
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