rmontanana/BayesNet
rmontanana/BayesNet
1
0
Fork 0
Code Issues 2 Pull Requests Packages Projects Releases 3 Wiki Activity

Complete first approach

Browse Source
This commit is contained in:
Ricardo Montañana Gómez 2023-12-31 12:02:13 +01:00
parent 652e5f623f
commit beadb7465f
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
3 changed files with 60 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

73
src/Platform/GridSearch.cc
View File

@ -44,7 +44,7 @@ namespace platform {
}
return json();
}
vector<std::string> GridSearch::processDatasets(Datasets& datasets)
vector<std::string> GridSearch::processDatasets(Datasets& datasets) const
{
// Load datasets
auto datasets_names = datasets.getNames();
@ -109,7 +109,7 @@ namespace platform {
auto datasets = Datasets(false, Paths::datasets());
auto all_datasets = datasets.getNames();
auto datasets_names = processDatasets(datasets);
for (int idx_dataset = 0; idx_dataset < all_datasets.size(); ++idx_dataset) {
for (int idx_dataset = 0; idx_dataset < datasets_names.size(); ++idx_dataset) {
auto dataset = all_datasets[idx_dataset];
for (const auto& seed : config.seeds) {
auto combinations = grid.getGrid(dataset);
@ -169,7 +169,6 @@ namespace platform {
auto y_train = y.index({ train_t });
auto X_test = X.index({ "...", test_t });
auto y_test = y.index({ test_t });
auto num = 0;
double best_fold_score = 0.0;
int best_idx_combination = -1;
json best_fold_hyper;
@ -222,6 +221,7 @@ namespace platform {
result->idx_dataset = task["idx_dataset"].get<int>();
result->idx_combination = best_idx_combination;
result->score = best_fold_score;
result->n_fold = n_fold;
result->time = timer.getDuration();
// Update progress bar
std::cout << get_color_rank(config_mpi.rank) << "*" << std::flush;
@ -244,17 +244,34 @@ namespace platform {
}
return { start, end };
}
void store_result(std::vector<std::string>& names, Task_Result& result, json& results)
{
json json_result = {
{ "score", result.score },
{ "combination", result.idx_combination },
{ "fold", result.n_fold },
{ "time", result.time },
{ "dataset", result.idx_dataset }
};
auto name = names[result.idx_dataset];
if (!results.contains(name)) {
results[name] = json::array();
}
results[name].push_back(json_result);
}
json producer(json& tasks, struct ConfigMPI& config_mpi, MPI_Datatype& MPI_Result)
{
Task_Result result;
json results;
int num_tasks = tasks.size();
auto datasets = Datasets(false, Paths::datasets());
auto names = datasets.getNames();
for (int i = 0; i < num_tasks; ++i) {
MPI_Status status;
MPI_Recv(&result, 1, MPI_Result, MPI_ANY_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status);
if (status.MPI_TAG == TAG_RESULT) {
//Store result
// TODO
store_result(names, result, results);
}
MPI_Send(&i, 1, MPI_INT, status.MPI_SOURCE, TAG_TASK, MPI_COMM_WORLD);
}
@ -264,19 +281,42 @@ namespace platform {
MPI_Recv(&result, 1, MPI_Result, MPI_ANY_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status);
if (status.MPI_TAG == TAG_RESULT) {
//Store result
// TODO
store_result(names, result, results);
}
MPI_Send(&i, 1, MPI_INT, status.MPI_SOURCE, TAG_END, MPI_COMM_WORLD);
}
return results;
}
json select_best_results_folds(json& all_results)
json select_best_results_folds(json& all_results, std::string& model)
{
json results;
Timer timer;
auto grid = GridData(Paths::grid_input(model));
//
// Select the best result of the computed outer folds
//
// TODO
for (const auto& result : results.items()) {
// each result has the results of all the outer folds as each one were a different task
double best_score = 0.0;
json best;
for (const auto& result_fold : result.value()) {
double score = result_fold["score"].get<double>();
if (score > best_score) {
best_score = score;
best = result_fold;
}
}
auto dataset = result.key();
auto combinations = grid.getGrid(dataset);
json json_best = {
{ "score", best_score },
{ "hyperparameters", combinations[best["combination"].get<int>()] },
{ "date", get_date() + " " + get_time() },
{ "grid", grid.getInputGrid(dataset) },
{ "duration", timer.translate2String(best["time"].get<double>()) }
};
results[dataset] = json_best;
}
return results;
}
void consumer(Datasets& datasets, json& tasks, struct ConfigGrid& config, struct ConfigMPI& config_mpi, MPI_Datatype& MPI_Result)
@ -303,8 +343,8 @@ namespace platform {
* Each task is a json object with the following structure:
* {
* "dataset": "dataset_name",
* "idx_dataset": idx_dataset,
* "seed": # of seed to use,
* "model": "model_name",
* "Fold": # of fold to process
* }
*
@ -331,14 +371,15 @@ namespace platform {
Task_Result result;
int tasks_size;
MPI_Datatype MPI_Result;
MPI_Datatype type[4] = { MPI_UNSIGNED, MPI_UNSIGNED, MPI_DOUBLE, MPI_DOUBLE };
int blocklen[4] = { 1, 1, 1, 1 };
MPI_Aint disp[4];
MPI_Datatype type[5] = { MPI_UNSIGNED, MPI_UNSIGNED, MPI_INT, MPI_DOUBLE, MPI_DOUBLE };
int blocklen[5] = { 1, 1, 1, 1, 1 };
MPI_Aint disp[5];
disp[0] = offsetof(Task_Result, idx_dataset);
disp[1] = offsetof(Task_Result, idx_combination);
disp[2] = offsetof(Task_Result, score);
disp[3] = offsetof(Task_Result, time);
MPI_Type_create_struct(4, blocklen, disp, type, &MPI_Result);
disp[2] = offsetof(Task_Result, n_fold);
disp[3] = offsetof(Task_Result, score);
disp[4] = offsetof(Task_Result, time);
MPI_Type_create_struct(5, blocklen, disp, type, &MPI_Result);
MPI_Type_commit(&MPI_Result);
//
// 0.2 Manager creates the tasks
@ -369,7 +410,7 @@ namespace platform {
auto datasets = Datasets(config.discretize, Paths::datasets());
if (config_mpi.rank == config_mpi.manager) {
auto all_results = producer(tasks, config_mpi, MPI_Result);
auto results = select_best_results_folds(all_results);
auto results = select_best_results_folds(all_results, config.model);
save(results);
} else {
consumer(datasets, tasks, config, config_mpi, MPI_Result);
@ -381,8 +422,8 @@ namespace platform {
* Each task is a json object with the following structure:
* {
* "dataset": "dataset_name",
* "idx_dataset": idx_dataset,
* "seed": # of seed to use,
* "model": "model_name",
* "Fold": # of fold to process
* }
*

3
src/Platform/GridSearch.h
View File

@ -33,6 +33,7 @@ namespace platform {
typedef struct {
uint idx_dataset;
uint idx_combination;
int n_fold;
double score;
double time;
} Task_Result;
@ -52,7 +53,7 @@ namespace platform {
private:
void save(json& results);
json initializeResults();
vector<std::string> processDatasets(Datasets& datasets);
vector<std::string> processDatasets(Datasets& datasets) const;
pair<double, json> processFileSingle(std::string fileName, Datasets& datasets, std::vector<json>& combinations);
pair<double, json> processFileNested(std::string fileName, Datasets& datasets, std::vector<json>& combinations);
struct ConfigGrid config;

2
src/Platform/b_grid.cc
View File

@ -201,7 +201,7 @@ int main(int argc, char** argv)
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &mpi_config.rank);
MPI_Comm_size(MPI_COMM_WORLD, &mpi_config.n_procs);
grid_search.go_mpi(mpi_config);
grid_search.go_producer_consumer(mpi_config);
if (mpi_config.rank == mpi_config.manager) {
auto results = grid_search.getResults();
list_results(results, config.model);