void ResizeImageTransformer<Dtype>::SampleTransformParams(const vector<int>& in_shape) {
ImageTransformer<Dtype>::SampleTransformParams(in_shape);
CHECK_GE(in_shape.size(), 2);
CHECK_LE(in_shape.size(), 4);
int in_width = in_shape[in_shape.size() - 1];
int in_height = in_shape[in_shape.size() - 2];
if (param_.width_size()) {
SampleFixedIndependent();
} else if (param_.size_size()) {
SampleFixedTied();
} else if (param_.width_perc_size()) {
SamplePercIndependent(in_width, in_height);
} else if (param_.size_perc_size()) {
SamplePercTied(in_width, in_height);
} else {
CHECK(0) << "Invalid resize param";
}
PrintParams();
}
//---------------------------------------------------------
bool MPI_Solver :: MPI_ConseqSolve( int argc, char **argv )
{
// read all cnf in current dir and start then in conseq mode
std::string dir = std::string(".");
int cnf_count = 0;
std::vector<std::string> files;
std::vector<std::string> cnf_files;
std::fstream out_file;
int current_obj_val = -1;
unsigned long long process_sat_count= 0;
double cnf_time_from_node;
//PBSolver_cut pbs_cut;
std::stringstream solve_sstream;
double start_sec;
double final_sec;
Solver *S;
std::vector<std::vector<bool>> interrupted_problems_var_values_from_process, sat_assignments_from_process;
// MPI start
//MPI_Request request;
int corecount = 10, rank = 0;
/*MPI_Init( &argc, &argv );
MPI_Comm_size( MPI_COMM_WORLD, &corecount );
MPI_Comm_rank( MPI_COMM_WORLD, &rank );*/
files = std::vector<std::string>( );
cnf_files = std::vector<std::string>( );
// get all files in current dir
getdir( dir, files );
for ( unsigned i = 0; i < files.size( ); i++ ) {
if ( files[i].find( ".cnf" ) != std::string::npos ) {
cnf_count++;
cnf_files.push_back( files[i] );
if ( rank == 0 )
std::cout << std::endl << "founded cnf " << files[i].c_str( );
}
}
if ( cnf_count > corecount ) {
if ( rank == 0 ) {
std::cout << std::endl << "Warning. Count of cnf-file > corecount";
std::cout << std::endl << "Only first " << corecount << " cnf will be processed";
std::cout << std::endl << "cnf_count changed to corecount";
}
cnf_count = corecount;
}
else if ( cnf_count == 0 ) {
if ( rank == 0 ) std::cout << std::endl << "Error. No cnf-files in dir";
return false;
}
if ( rank > cnf_count - 1 )
std::cout << std::endl << "core # " << rank << " with no job";
else {// do job
std::stringstream sstream;
sstream << "answer_" << rank + 1;
std::string out_file_name = sstream.str( );
sstream.str( "" );
sstream.clear();
start_sec = MPI_Wtime( ); // get init time
input_cnf_name = &cnf_files[rank][0]; // set current name of file
std::cout << std::endl << "input_cnf_name is " << input_cnf_name;
unsigned int zero_mask[FULL_MASK_LEN];
for ( int i = 0; i < FULL_MASK_LEN; i++ )
zero_mask[i] = 0;
if ( !ReadIntCNF( ) ) { // Read original CNF
std::cout << "\n Error in ReadIntCNF" << std::endl; return 1;
}
std::cout << std::endl << "end of ReadIntCNF";
if ( rank == 0 )
PrintParams( );
if ( !IsPB ) {
int current_task_index = 0;
std::cout << std::endl << std::endl << "Standart mode of SAT solving";
if ( !SolverRun( S, process_sat_count, cnf_time_from_node, current_task_index,
interrupted_problems_var_values_from_process, sat_assignments_from_process ) )
{
std::cout << std::endl << "Error in SolverRun";
return false;
}
if ( process_sat_count ) {
if ( !AnalyzeSATset( cnf_time_from_node ) ) {
// is't needed to deallocate memory - MPI_Abort will do it
std::cout << "\n Error in Analyzer" << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
return false;
}
}
}
final_sec = MPI_Wtime( ) - start_sec;
sstream << input_cnf_name << " " << final_sec << " sec" << std::endl;
out_file.open( out_file_name.c_str( ), std::ios_base :: out ); // open and clear out file
out_file << sstream.rdbuf( );
out_file << solve_sstream.rdbuf( );
std::cout << std::endl << "*** sstream " << sstream.str( );
std::cout << std::endl << "*** solve_sstream " << solve_sstream.str( );
out_file.close( );
}
MPI_Finalize( ); // MPI end
std::cout << std::endl << "End of ControlConseqProcessSolve";
return true;
}
int main(int argc, char* argv[]){
// Start timing!
boost::timer::cpu_timer myTimer;
cout << endl;
cout << "BEGIN" << endl;
// BEGIN: setup
FIELDCONTAINER field;
DATA params;
GRIDINFO grid;
LAPLACIANSTENCIL stencil;
// Read in parameter files & populate "params"
GetParams(argc,argv,¶ms);
CheckParams(¶ms);
if( params.flag == 0){
// Use info to setup "grid" and "field" struct
SetupGrid(&grid, ¶ms);
SetupField(¶ms, &field);
SetupLaplacianStencil(¶ms, &stencil);
// Print params to screen & logfile
ofstream logout;
logout.open(params.OutDir + params.RunID + "_log.dat");
PrintParams(cout, ¶ms, &stencil, 0);
PrintParams(logout, ¶ms, &stencil, 0);
logout.close();
// END: setup
// BEGIN: solving
// Setup initial conditions
InitialConditions(¶ms, &grid, &field);
// Solve field equation
SolveKG3D(¶ms, &grid, &field, &stencil);
// Delete arrays
field.CleanField(&field);
// END: solving
// BEGIN: feedback
myTimer.stop();
params.TotalRunTime = myTimer.elapsed().wall / 1e6;
logout.open(params.OutDir + params.RunID + "_log.dat",std::ofstream::app);
PrintParams(cout, ¶ms, &stencil, 1);
PrintParams(logout, ¶ms, &stencil, 1);
logout.close();
// END: feedback
} // END if( params.flag == 0){}
}// end main()
bool MPI_Solver :: ControlProcessSolve( std::vector<int> extern_var_choose_order,
std::vector<std::vector<bool>> &interrupted_problems_var_values,
std::vector<satisfying_assignment> &satisfying_assignments )
{
interrupted_problems_var_values.clear();
std::vector<bool> cur_interrupted_problems_var_values;
satisfying_assignment cur_satisfying_assignment;
std::cout << std::endl << "ControlProcessSolve is running" << std::endl;
std::cout << "solving_iteration_count " << solving_iteration_count << std::endl;
if ( solving_iteration_count == 0 ) {
if ( !ReadIntCNF() ) { // Read original CNF
std::cerr << "Error in ReadIntCNF" << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
if ( !MakeVarChoose() ) {
std::cerr << "Error in MakeVarChoose" << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
}
if ( extern_var_choose_order.size() > 0 )
var_choose_order = extern_var_choose_order;
std::cout << "var_choose_order " << std::endl;
for ( auto &x : var_choose_order )
std::cout << x << " ";
std::cout << std::endl;
// log(a)/log(b) = log(_a)b
unsigned max_possible_tasks_count = (unsigned)(pow( 2, ceil( log(corecount - 1)/log(2) ))) * (unsigned)(pow(2,koef_val) );
std::cout << "max_possible_tasks_count " << max_possible_tasks_count << std::endl;
std::cout << "current part_mask_var_count " << part_mask_var_count << std::endl;
part_mask_var_count = (unsigned)(log(max_possible_tasks_count)/log(2));
if ( part_mask_var_count > var_choose_order.size() )
part_mask_var_count = var_choose_order.size();
// change batch size to treshold value if needed
if ( var_choose_order.size() - part_mask_var_count > RECOMMEND_BATCH_VAR_COUNT ) {
part_mask_var_count = var_choose_order.size() - RECOMMEND_BATCH_VAR_COUNT;
std::cout << "part_mask_var_count changed to " << part_mask_var_count << std::endl;
}
if ( part_mask_var_count > MAX_PART_MASK_VAR_COUNT )
part_mask_var_count = MAX_PART_MASK_VAR_COUNT;
if ( var_choose_order.size() - part_mask_var_count > MAX_BATCH_VAR_COUNT ) {
std::cerr << "Error. var_choose_order.size() - part_mask_var_count > MAX_BATCH_VAR_COUNT" << std::endl;
std::cerr << var_choose_order.size() - part_mask_var_count << " < " << MAX_BATCH_VAR_COUNT << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
std::cout << "part_mask_var_count " << part_mask_var_count << std::endl;
// get default count of tasks = power of part_mask_var_count
unsigned part_var_power = ( 1 << part_mask_var_count );
std::cout << "part_var_power " << part_var_power << std::endl;
// TODO add extended tasks counting
all_tasks_count = part_var_power;
std::cout << "all_tasks_count " << all_tasks_count << std::endl;
if ( (int)all_tasks_count < corecount-1 ) {
std::cerr << "Error. all_tasks_count < corecount-1" << std::endl;
std::cerr << all_tasks_count << " < " << corecount-1 << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
if ( solving_iteration_count == 0 )
PrintParams( );
if ( skip_tasks >= all_tasks_count ) {
std::cerr << "skip_tasks >= all_tasks_count " << std::endl;
std::cerr << skip_tasks << " >= " << all_tasks_count << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
values_arr.resize( all_tasks_count );
for ( unsigned i = 0; i < values_arr.size(); ++i )
values_arr[i].resize( FULL_MASK_LEN );
if ( !MakeStandardMasks( part_var_power ) ) {
std::cerr << "Error in MakeStandartMasks" << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
std::cout << "Correct end of MakeStandartMasks" << std::endl;
unsigned solved_tasks_count = 0;
// write init info
WriteSolvingTimeInfo( solving_times, solved_tasks_count );
int *var_choose_order_int = new int[MAX_CORE_LEN];
for( unsigned i=0; i < MAX_CORE_LEN; ++i ) {
if ( i < var_choose_order.size() )
var_choose_order_int[i] = var_choose_order[i];
else
var_choose_order_int[i] = -1;
}
std::cout << "before sending configuration info" << std::endl;
// send core_len once to every compute process
for ( int i=0; i < corecount-1; ++i ) {
MPI_Send( &core_len, 1, MPI_INT, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( &all_tasks_count, 1, MPI_UNSIGNED, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( &solving_iteration_count, 1, MPI_INT, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( &max_solving_time, 1, MPI_DOUBLE, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( &start_activity, 1, MPI_DOUBLE, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( var_choose_order_int, MAX_CORE_LEN, MPI_INT, i + 1, 0, MPI_COMM_WORLD );
}
delete[] var_choose_order_int;
int next_task_index = 0;
//unsigned start_tasks_count = min( corecount - 1, (int)all_tasks_count );
unsigned start_tasks_count = ((corecount - 1) < (int)all_tasks_count) ? (unsigned)(corecount - 1) : all_tasks_count;
int char_arr_len;
char *char_arr;
unsigned elem_index;
std::cout << "start_tasks_count " << start_tasks_count << std::endl;
// send to all cores (except # 0) tasks from 1st range
for ( int i = 0; i < (int)start_tasks_count; ++i ) {
// send new index of task for reading tasks from file
MPI_Send( &next_task_index, 1, MPI_INT, i + 1, 0, MPI_COMM_WORLD );
if ( ( verbosity > 1 ) && ( i == 0 ) )
std::cout << "sended next_task_index " << next_task_index << std::endl;
copy( values_arr[i].begin(), values_arr[i].end(), mask_value );
MPI_Send( full_mask, FULL_MASK_LEN, MPI_UNSIGNED, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( part_mask, FULL_MASK_LEN, MPI_UNSIGNED, i + 1, 0, MPI_COMM_WORLD );
MPI_Send( mask_value, FULL_MASK_LEN, MPI_UNSIGNED, i + 1, 0, MPI_COMM_WORLD );
next_task_index++;
}
std::cout << "after sending start_tasks_count" << std::endl;
total_solving_times[0] = 1 << 30; // start min len
for ( unsigned i = 1; i < total_solving_times.size(); ++i )
total_solving_times[i] = 0;
process_sat_count = 0;
MPI_Status status, current_status;
while ( solved_tasks_count < all_tasks_count ) {
// recieve from core message about solved task
MPI_Recv( &process_sat_count, 1, MPI_INT, MPI_ANY_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );
if ( verbosity > 0 )
std::cout << "recieved process_sat_count " << process_sat_count << std::endl;
current_status = status;
MPI_Recv( solving_times, SOLVING_TIME_LEN, MPI_DOUBLE, current_status.MPI_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );
if ( verbosity > 0 )
std::cout << "recieved solving_times " << std::endl;
// get interrupted tasks if such exist
MPI_Probe( current_status.MPI_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );;
MPI_Get_count( &status, MPI_CHAR, &char_arr_len );
if ( ( char_arr_len > 1 ) && ( char_arr_len % var_choose_order.size() != 0 ) ) {
std::cerr << "char_arr_len % var_choose_order.size() != 0" << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
if ( char_arr_len > 0 ) {
char_arr = new char[char_arr_len];
MPI_Recv( char_arr, char_arr_len, MPI_CHAR, current_status.MPI_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );
if ( char_arr_len > 1 ) {
//std::cout << "recieved char_arr_len " << char_arr_len << std::endl;
cur_interrupted_problems_var_values.resize( var_choose_order.size() );
elem_index=0;
for ( int j=0; j < var_choose_order.size(); j++ ) {
cur_interrupted_problems_var_values[elem_index++] = (char_arr[j] == '1' ? true : false);
if ( (j+1) % var_choose_order.size() == 0 ) {
interrupted_problems_var_values.push_back( cur_interrupted_problems_var_values );
elem_index=0;
}
}
}
delete[] char_arr;
}
// get satisfying assignments if such exist
MPI_Probe( current_status.MPI_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );;
MPI_Get_count( &status, MPI_CHAR, &char_arr_len );
if ( ( char_arr_len > 1 ) && ( char_arr_len % var_count != 0 ) ) {
std::cerr << "char_arr_len % var_count != 0" << std::endl;
std::cerr << char_arr_len << " % " << var_count << " != 0 " << std::endl;
MPI_Abort( MPI_COMM_WORLD, 0 );
}
if ( char_arr_len > 0 ) {
cur_satisfying_assignment.solving_time = solving_times[3]; // sat solving time
char_arr = new char[char_arr_len];
MPI_Recv( char_arr, char_arr_len, MPI_CHAR, current_status.MPI_SOURCE, MPI_ANY_TAG, MPI_COMM_WORLD, &status );
if ( char_arr_len > 1 ) { // read several assignments from one array
std::cout << "recieved char_arr_len " << char_arr_len << std::endl;
elem_index=0;
cur_satisfying_assignment.str.resize( var_count );
for ( int j=0; j < char_arr_len; j++ ) {
cur_satisfying_assignment.str[elem_index++] = char_arr[j];
if ( (j+1) % var_count == 0 ) {
satisfying_assignments.push_back( cur_satisfying_assignment );
elem_index=0;
}
}
}
delete[] char_arr;
}
if ( char_arr_len > 1 )
std::cout << "interrupted_problems_var_values.size() " << interrupted_problems_var_values.size() << std::endl;
/*char_send_array = new char[interrupted_problems_var_values_from_process.size() * var_choose_order.size()];
char_send_array_index = 0;
for ( auto &x : interrupted_problems_var_values_from_process )
for ( auto &y : x )
char_send_array[char_send_array_index++] = (y == true ? '1' : '0');
MPI_Send( char_send_array, char_send_array_index, MPI_CHAR, 0, 0, MPI_COMM_WORLD );
delete[] char_send_array;*/
solved_tasks_count++;
if ( verbosity > 0 )
std::cout << "solved_tasks_count " << solved_tasks_count << std::endl;
if ( process_sat_count ) {
sat_count += process_sat_count;
std::cout << "sat_count " << sat_count << std::endl;
if ( finding_first_sat_time == 0 ) // first time only
finding_first_sat_time = MPI_Wtime() - total_start_time;
}
WriteSolvingTimeInfo( solving_times, solved_tasks_count );
if ( sat_count && !IsSolveAll )
break; // exit if SAT set found
if ( next_task_index < (int)all_tasks_count ) {
// send new index of task
MPI_Send( &next_task_index, 1, MPI_INT, current_status.MPI_SOURCE, 0, MPI_COMM_WORLD );
// send to free core new task in format of minisat input masks
copy( values_arr[next_task_index].begin(), values_arr[next_task_index].end(), mask_value );
MPI_Send( mask_value, FULL_MASK_LEN, MPI_UNSIGNED, current_status.MPI_SOURCE, 0, MPI_COMM_WORLD );
next_task_index++;
}
} // while ( solved_tasks_count < all_tasks_count )
solving_iteration_count++;
return true;
}
void FNeuralNetLMBase::TrainLM(const string &validationfile,
const string &outbase,
bool nce_ppl) {
// =============
// Prepare for the training
// Equivalent to ReadLM
word_vocab_.ReadVocabFromTxt(word_vocab_filename_);
if (word_vocab_.empty()) {
cerr << "empty word vocabulary!" << endl;
exit(EXIT_FAILURE);
}
factor_vocab_.ReadVocabFromTxt(factor_vocab_filename_);
if (factor_vocab_.empty()) {
cerr << "empty factor vocabulary!" << endl;
exit(EXIT_FAILURE);
}
ReadDecompFromTxt(decomp_filename_);
PrintParams();
CheckParams();
AllocateModel();
InitializeNeuralNet();
// ==== END ====
// Read the data
FNNLMDataReader train_data(train_filenames_, &word_vocab_, &factor_vocab_,
shuffle_datafiles_, shuffle_sentences_);
vector<string> validation_filenames = { validationfile };
FNNLMDataReader validation_data(validation_filenames, &word_vocab_, &factor_vocab_, false, false);
// Set NCE sampling.
if (nce_) {
// TODO: flatten noise_distribution_?
vector<int> word_count(word_vocab_.size(), 0);
int num_word_tokens = 0;
const size_t eos_widx = word_vocab().eos_idx();
vector<int> factor_count(factor_vocab_.size(), 0);
int num_factor_tokens = 0;
const size_t eos_fidx = factor_vocab().eos_idx();
vector<pair<size_t, vector<size_t>>> sentence;
train_data.StartEpoch();
while(train_data.GetSentence(sentence)) {
for (vector<pair<size_t, vector<size_t>>>::const_iterator it = sentence.begin(); it != sentence.end(); ++it) {
word_count[it->first]++;
num_word_tokens++;
if (weight_factor_output_ > 0) {
for (size_t p = 0; p < it->second.size(); p++) {
factor_count[it->second[p]]++;
num_factor_tokens++;
}
}
}
word_count[eos_widx]++;
num_word_tokens++;
if (weight_factor_output_ > 0) {
factor_count[eos_fidx]++;
num_factor_tokens++;
}
}
word_noise_distribution_ = Distribution(word_count.begin(), word_count.end());
word_noise_pdf_ = word_noise_distribution_.param().probabilities();
if (weight_factor_output_ > 0) {
factor_noise_distribution_ = Distribution(factor_count.begin(), factor_count.end());
factor_noise_pdf_ = factor_noise_distribution_.param().probabilities();
}
NCECheckSampling();
log_num_negative_samples_ = log(num_negative_samples_);
}
BatchSGDTrain(train_data, validation_data, outbase, nce_ppl);
cout << "================================================================================" << endl;
cout << "Log-likelihood (base e) on validation is: " \
<< EvalLM(validation_data, false) << endl;
}