rmontanana/BayesNet
rmontanana/BayesNet
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Fix sample building

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This commit is contained in:
Ricardo Montañana Gómez 2023-12-04 19:12:44 +01:00
parent cc316bb8d3
commit f0d6f0cc38
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
3 changed files with 13 additions and 11 deletions
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4
Makefile
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@ -49,10 +49,10 @@ dependency: ## Create a dependency graph diagram of the project (build/dependenc
cd $(f_debug) && cmake .. --graphviz=dependency.dot && dot -Tpng dependency.dot -o dependency.png
buildd: ## Build the debug targets
cmake --build $(f_debug) -t $(app_targets) $(n_procs)
cmake --build $(f_debug) -t $(app_targets) BayesNetSample $(n_procs)
buildr: ## Build the release targets
cmake --build $(f_release) -t $(app_targets) $(n_procs)
cmake --build $(f_release) -t $(app_targets) BayesNetSample $(n_procs)
clean: ## Clean the tests info
@echo ">>> Cleaning Debug BayesNet tests...";

4
sample/CMakeLists.txt
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@ -1,8 +1,10 @@
include_directories(${BayesNet_SOURCE_DIR}/src/Platform)
include_directories(${BayesNet_SOURCE_DIR}/src/BayesNet)
include_directories(${BayesNet_SOURCE_DIR}/src/PyClassifiers)
include_directories(${Python3_INCLUDE_DIRS})
include_directories(${BayesNet_SOURCE_DIR}/lib/Files)
include_directories(${BayesNet_SOURCE_DIR}/lib/mdlp)
include_directories(${BayesNet_SOURCE_DIR}/lib/argparse/include)
include_directories(${BayesNet_SOURCE_DIR}/lib/json/include)
add_executable(BayesNetSample sample.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc ${BayesNet_SOURCE_DIR}/src/Platform/Models.cc)
target_link_libraries(BayesNetSample BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}")
target_link_libraries(BayesNetSample BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}" PyWrap)

16
sample/sample.cc
View File

@ -29,7 +29,7 @@ pair<std::vector<mdlp::labels_t>, map<std::string, int>> discretize(std::vector<
return { Xd, maxes };
}
bool file_exists(const std::std::std::string& name)
bool file_exists(const std::string& name)
{
if (FILE* file = fopen(name.c_str(), "r")) {
fclose(file);
@ -72,7 +72,7 @@ int main(int argc, char** argv)
argparse::ArgumentParser program("BayesNetSample");
program.add_argument("-d", "--dataset")
.help("Dataset file name")
.action([valid_datasets](const std::std::std::string& value) {
.action([valid_datasets](const std::string& value) {
if (find(valid_datasets.begin(), valid_datasets.end(), value) != valid_datasets.end()) {
return value;
}
@ -84,20 +84,20 @@ int main(int argc, char** argv)
.default_value(std::string{ PATH }
);
program.add_argument("-m", "--model")
.help("Model to use " + platform::Models::instance()->tostd::string())
.action([](const std::std::std::string& value) {
.help("Model to use " + platform::Models::instance()->tostring())
.action([](const std::string& value) {
static const std::vector<std::string> choices = platform::Models::instance()->getNames();
if (find(choices.begin(), choices.end(), value) != choices.end()) {
return value;
}
throw runtime_error("Model must be one of " + platform::Models::instance()->tostd::string());
throw runtime_error("Model must be one of " + platform::Models::instance()->tostring());
}
);
program.add_argument("--discretize").help("Discretize input dataset").default_value(false).implicit_value(true);
program.add_argument("--dumpcpt").help("Dump CPT Tables").default_value(false).implicit_value(true);
program.add_argument("--stratified").help("If Stratified KFold is to be done").default_value(false).implicit_value(true);
program.add_argument("--tensors").help("Use tensors to store samples").default_value(false).implicit_value(true);
program.add_argument("-f", "--folds").help("Number of folds").default_value(5).scan<'i', int>().action([](const std::std::string& value) {
program.add_argument("-f", "--folds").help("Number of folds").default_value(5).scan<'i', int>().action([](const std::string& value) {
try {
auto k = stoi(value);
if (k < 2) {
@ -184,8 +184,8 @@ int main(int argc, char** argv)
file.close();
std::cout << "Graph saved in " << model_name << "_" << file_name << ".dot" << std::endl;
std::cout << "dot -Tpng -o " + dot_file + ".png " + dot_file + ".dot " << std::endl;
std::string stratified_std::string = stratified ? " Stratified" : "";
std::cout << nFolds << " Folds" << stratified_std::string << " Cross validation" << std::endl;
std::string stratified_string = stratified ? " Stratified" : "";
std::cout << nFolds << " Folds" << stratified_string << " Cross validation" << std::endl;
std::cout << "==========================================" << std::endl;
torch::Tensor Xt = torch::zeros({ static_cast<int>(Xd.size()), static_cast<int>(Xd[0].size()) }, torch::kInt32);
torch::Tensor yt = torch::tensor(y, torch::kInt32);