void BuildTable::CalcBuildTable (int cur, int endbuild, int depth, ResInfo res)
{
const UnitDef* d = deflist [cur].def;
res.buildtime += d->buildTime;
res.energy += d->energyCost;
res.metal += d->metalCost;
float score = CalcScore(depth,res);
std::vector<int> &bb=buildby[cur];
for (std::vector<int>::iterator a = bb.begin(); a!=bb.end(); ++a) // for every unit that can build cur
{
BuildTable::Table::ent& ent = table.get (*a, endbuild);
float entscore = CalcScore (ent.depth, ent.res);
if (ent.id < 0 || entscore > score)
{
ent.id = cur;
ent.depth = depth;
ent.res = res;
CalcBuildTable(*a, endbuild, depth+1, res);
}
}
}
/*>void DisplayScores(FILE *fp, char **SeqTable, int nseq, int seqlen,
int MaxInMatrix, int Method, BOOL Extended)
-------------------------------------------------------------------
Display the variability scores for each position in the alignment
11.09.96 Original By: ACRM
17.09.96 Added MaxInMatrix and prints amino acid list
15.07.08 Added Extended parameter and printing
*/
void DisplayScores(FILE *fp, char **SeqTable, int nseq, int seqlen,
int MaxInMatrix, int Method, BOOL Extended)
{
int i, j;
for(i=0; i<seqlen; i++)
{
if(Extended)
{
fprintf(fp,"%4d %9.6f ",
i+1,
CalcScore(SeqTable, nseq, seqlen, i,
MaxInMatrix, Method));
}
else
{
fprintf(fp,"%4d %6.3f ",
i+1,
CalcScore(SeqTable, nseq, seqlen, i,
MaxInMatrix, Method));
}
for(j=0; j<nseq; j++)
{
fprintf(fp,"%c",SeqTable[j][i]);
}
fprintf(fp,"\n");
}
}
/********************************************************
*! @brief 関数
-
@param[out] -
@param[in] -
@par -
@return -
@note
*********************************************************/
PRIVATE EVALUATE_TREE_T* CreateEvaluateTree( PLAYER_T CurrentPlayer )
{
EVALUATE_TREE_T *pEvaluateTreeTop;
EVALUATE_TABLE_T *pReversiTableTop;
SIZE_T AllocateAreaSize;
unsigned int Depth;
/* Create Evaluate Table of Top Node */
pReversiTableTop = (EVALUATE_TABLE_T*)malloc( sizeof(EVALUATE_TABLE_T) );
AllocateAreaSize = sizeof( pReversiTableTop->aEvaluatReversiTable );
CopyCurrentReversiTable( pReversiTableTop->aEvaluatReversiTable, AllocateAreaSize );
/* Create Evaluate Tree Top Node */
pEvaluateTreeTop = (EVALUATE_TREE_T*)malloc( sizeof(EVALUATE_TREE_T) );
pEvaluateTreeTop->Depth = 0;
pEvaluateTreeTop->NodeID = 0;
pEvaluateTreeTop->DiscInfo.h = 0;
pEvaluateTreeTop->DiscInfo.v = 0;
pEvaluateTreeTop->DiscInfo.CurrentPlayer= TOGGLE_PLAYER( CurrentPlayer ); /* Currentは１手前の相手ターンの盤面 */
pEvaluateTreeTop->NumNextIndex = 0;
pEvaluateTreeTop->pEvaluatReversiTable = pReversiTableTop;
pEvaluateTreeTop->Score = CalcScore( pEvaluateTreeTop->DiscInfo.CurrentPlayer,
pEvaluateTreeTop->pEvaluatReversiTable->aEvaluatReversiTable );
pEvaluateTreeTop->pNextNode = NULL;
pEvaluateTreeTop->pNextDepthNode = NULL;
/* Create Tree */
MakeTree( pEvaluateTreeTop );
return pEvaluateTreeTop;
}
void KENLM<Model>::EvaluateInIsolation(MemPool &pool, const System &system,
const Phrase<Moses2::Word> &source, const TargetPhraseImpl &targetPhrase, Scores &scores,
SCORE &estimatedScore) const
{
// contains factors used by this LM
float fullScore, nGramScore;
size_t oovCount;
CalcScore(targetPhrase, fullScore, nGramScore, oovCount);
float estimateScore = fullScore - nGramScore;
bool GetLMEnableOOVFeature = false;
if (GetLMEnableOOVFeature) {
float scoresVec[2], estimateScoresVec[2];
scoresVec[0] = nGramScore;
scoresVec[1] = oovCount;
scores.PlusEquals(system, *this, scoresVec);
estimateScoresVec[0] = estimateScore;
estimateScoresVec[1] = 0;
SCORE weightedScore = Scores::CalcWeightedScore(system, *this,
estimateScoresVec);
estimatedScore += weightedScore;
} else {
scores.PlusEquals(system, *this, nGramScore);
SCORE weightedScore = Scores::CalcWeightedScore(system, *this,
estimateScore);
estimatedScore += weightedScore;
}
}
void LanguageModel::EvaluateInIsolation(const Phrase &source
, const TargetPhrase &targetPhrase
, ScoreComponentCollection &scoreBreakdown
, ScoreComponentCollection &estimatedFutureScore) const
{
// contains factors used by this LM
float fullScore, nGramScore;
size_t oovCount;
CalcScore(targetPhrase, fullScore, nGramScore, oovCount);
float estimateScore = fullScore - nGramScore;
if (StaticData::Instance().GetLMEnableOOVFeature()) {
vector<float> scores(2), estimateScores(2);
scores[0] = nGramScore;
scores[1] = oovCount;
scoreBreakdown.Assign(this, scores);
estimateScores[0] = estimateScore;
estimateScores[1] = 0;
estimatedFutureScore.Assign(this, estimateScores);
} else {
scoreBreakdown.Assign(this, nGramScore);
estimatedFutureScore.Assign(this, estimateScore);
}
}
FFState* LexicalReordering::Evaluate(
const Hypothesis& hypo,
const FFState* prev_state,
ScoreComponentCollection* out) const {
out->PlusEquals(this, CalcScore(const_cast<Hypothesis*>(&hypo)));
//TODO need to return proper state, calc score should not use previous
//hypothesis, it should use the state.
return NULL;
}
int Umeyama(const gsl_matrix * const A,
const gsl_matrix * const B,
gsl_matrix * const Assignment,
float *score)
{
int res = 0;
gsl_matrix_complex *AE = NULL, *BE = NULL;
gsl_matrix *P = NULL,
*AS = NULL,
*BS = NULL,
*AN = NULL,
*BN = NULL,
*AssignmentT = NULL;
#ifdef USE_ASP
long *col_mate;
long *row_mate;
cost **pTempCost;
int i, j;
#endif
struct timeval start, end;
long mtime, seconds, useconds;
#ifdef VERBOSE
PrintGSLMatrix(A, "Umeyama A");
PrintGSLMatrix(B, "Umeyama B");
#endif
AE = gsl_matrix_complex_alloc(A->size1, A->size2); if(AE == NULL) goto _exit;
AS = gsl_matrix_alloc(A->size1, A->size2); if(AS == NULL) goto _exit;
AN = gsl_matrix_alloc(A->size1, A->size2); if(AN == NULL) goto _exit;
ComputeHermitianMatrix(A, AE, AS, AN);
#ifdef VERBOSE
PrintGSLMatrix(AS, "AS");
PrintGSLMatrix(AN, "AN");
#endif
if( IsHermitian(AE) == false )
{
fprintf(stderr, "FATAL: AE is not Hermitian!\n");
exit(0);
}
#ifdef VERBOSE
fprintf(stderr, "Verified AE is Hermitian.\n");
#endif
BE = gsl_matrix_complex_alloc(B->size1, B->size2); if(BE == NULL) goto _exit;
BS = gsl_matrix_alloc(B->size1, B->size2); if(BS == NULL) goto _exit;
BN = gsl_matrix_alloc(B->size1, B->size2); if(BN == NULL) goto _exit;
ComputeHermitianMatrix(B, BE, BS, BN);
#ifdef VERBOSE
PrintGSLMatrix(BS, "BS");
PrintGSLMatrix(BN, "BN");
#endif
if( IsHermitian(BE) == false )
{
fprintf(stderr, "FATAL: BE is not Hermitian!\n");
exit(0);
}
#ifdef VERBOSE
fprintf(stderr, "Verified BE is Hermitian.\n");
WriteComplexMatrixToFile(BE);
PrintGSLMatrixComplex(AE, "AE");
PrintGSLMatrixComplex(BE, "BE");
#endif
P = gsl_matrix_alloc(A->size1, A->size2); if(P == NULL) goto _exit;
res = EigenDecomp(AE, BE, P);
if( res == -1 ) goto _exit;
#ifdef VERBOSE
PrintGSLMatrix(P, "P");
PrintGSLMatrix(P, "Computing Hungarian");
#endif
// Begin timing Hungarian
gettimeofday(&start, NULL);
#ifdef USE_ASP
col_mate = new long[P->size1];
row_mate = new long[P->size1];
pTempCost = new cost*[P->size1];
for(i = 0; i < P->size1; ++i)
pTempCost[i] = new cost[P->size2];
for(i = 0; i < P->size1; ++i)
for(j = 0; j < P->size2; ++j)
pTempCost[i][j] = gsl_matrix_get(P, i, j);
asp(P->size1, pTempCost, col_mate, row_mate);
for(i = 0; i < P->size1; ++i)
delete[] pTempCost[i];
delete[] pTempCost;
// Update assignment matrix
for(i = 0; i < P->size1; ++i)
gsl_matrix_set(Assignment, i, col_mate[i], 1);
delete[] col_mate;
delete[] row_mate;
#else
Hungarian(P, true, Assignment);
#endif
// End timing Hungarian
gettimeofday(&end, NULL);
seconds = end.tv_sec - start.tv_sec;
useconds = end.tv_usec - start.tv_usec;
mtime = ((seconds) * 1000 + useconds/1000.0) + 0.5;
fprintf(stderr, "%ld ms\t", mtime);
// PrintGSLMatrixUint(Assignment, "Assignment");
// Allocate and initialize AssgtT
AssignmentT = gsl_matrix_alloc(Assignment->size1, Assignment->size2);
if(AssignmentT == NULL) goto _exit;
gsl_matrix_memcpy(AssignmentT, Assignment);
gsl_matrix_transpose(AssignmentT);
/*
PrintGSLMatrix(AS, "AS");
PrintGSLMatrix(AN, "AN");
PrintGSLMatrix(BS, "BS");
PrintGSLMatrix(BN, "BN");
*/
*score = CalcScore(AS, AN, BS, BN, Assignment, AssignmentT);
_exit:
if(P != NULL) gsl_matrix_free(P);
if(AS != NULL) gsl_matrix_free(AS);
if(AN != NULL) gsl_matrix_free(AN);
if(BS != NULL) gsl_matrix_free(BS);
if(BN != NULL) gsl_matrix_free(BN);
if(AE != NULL) gsl_matrix_complex_free(AE);
if(BE != NULL) gsl_matrix_complex_free(BE);
if(AssignmentT != NULL) gsl_matrix_free(AssignmentT);
return res;
}
/********************************************************
*! @brief 関数
-
@param[out] -
@param[in] -
@par -
@return -
@note
*********************************************************/
PRIVATE void MakeTree( EVALUATE_TREE_T *pCurrentNode )
{
int h, v;
DISC_INFO_T DiscInfo;
ERROR_CHECK Result;
EVALUATE_TREE_T *pNextDepthNode;
EVALUATE_TREE_T *pNextNode;
if ( pCurrentNode->Depth <= DEPTH_MAX ) {
#ifdef DEBUG_MAKE_NODE
printf("\nDepth = %d, NodeID = %d, CurrentPlayer = %d, Pos = [%d, %d], Score = %d"
,pCurrentNode->Depth ,pCurrentNode->NodeID ,pCurrentNode->DiscInfo.CurrentPlayer ,pCurrentNode->DiscInfo.h
,pCurrentNode->DiscInfo.v/COEF_LINE ,pCurrentNode->Score );
PrintReversiTable( pCurrentNode->pEvaluatReversiTable->aEvaluatReversiTable );
#endif
/* 有効な位置を探す */
for ( v=REALV(1); v < VERTICAL_NUM; v=v+REALV(1) ) {
for ( h=REALH(1); h < HORIZON_NUM; h=h+REALH(1) ) {
DiscInfo.h = h;
DiscInfo.v = v;
DiscInfo.CurrentPlayer = TOGGLE_PLAYER( pCurrentNode->DiscInfo.CurrentPlayer );
Result = CheckInputPos( &DiscInfo, pCurrentNode->pEvaluatReversiTable->aEvaluatReversiTable, FALSE );
/* 有効な位置を見つけたら新しいノードを生成する */
if ( Result == SUCCESS ) {
if ( pCurrentNode->NumNextIndex == 0 ) { /* 1つでも有効な位置が見つかったら次の深さのノードを生成する */
/* Tableへのポインタは生成し終わったら消滅して欲しいのでスコープは必要最低限に限定する */
EVALUATE_TABLE_T *pNextDepthTable;
/* Create Evaluate Table of Next Depth Node */
pNextDepthTable = (EVALUATE_TABLE_T*)malloc( sizeof(EVALUATE_TABLE_T) );
memcpy( pNextDepthTable, pCurrentNode->pEvaluatReversiTable, sizeof(EVALUATE_TABLE_T) ); /* CurrentノードのTableをコピーする */
ReversingDisc( DiscInfo, pNextDepthTable->aEvaluatReversiTable ); /* コピーしたTableで石をひっくり返す */
/* Create Evaluate Tree Next Depth Node */
pCurrentNode->pNextDepthNode = (EVALUATE_TREE_T*)malloc( sizeof(EVALUATE_TREE_T) );
pNextDepthNode = pCurrentNode->pNextDepthNode; /* 確保した領域にポインタを繋ぐ */
pNextDepthNode->Depth = pCurrentNode->Depth + 1;
pNextDepthNode->NodeID = pCurrentNode->NumNextIndex;
pNextDepthNode->DiscInfo.h = DiscInfo.h;
pNextDepthNode->DiscInfo.v = DiscInfo.v;
pNextDepthNode->DiscInfo.CurrentPlayer = DiscInfo.CurrentPlayer;
pNextDepthNode->pEvaluatReversiTable = pNextDepthTable;
pNextDepthNode->Score = CalcScore( pNextDepthNode->DiscInfo.CurrentPlayer,
pNextDepthNode->pEvaluatReversiTable->aEvaluatReversiTable );
pNextDepthNode->pNextNode = NULL;
pNextDepthNode->pNextDepthNode = NULL;
/* Create Evaluate Tree Next Next Depth Node */
MakeTree( pNextDepthNode );
/* 探索深度限界判定 */
if ( pNextDepthNode != NULL ) {
/* NextDepthがまだ探索深度限界に達していない */
pNextNode = pNextDepthNode->pNextNode; /* 以後、新しい選択肢が見つかったらNextNodeに新規Nodeを追加していく */
} else {
/* NextDepthが探索深度限界に達していた */
return; /* 深度限界なので他の選択肢を探る必要なし */
}
} else { /* 次の選択肢が見つかったらノードを生成する */
/* Tableへのポインタは生成し終わったら消滅して欲しいのでスコープは必要最低限に限定する */
EVALUATE_TABLE_T *pNextTable;
/* Create Evaluate Table of Next Node */
pNextTable = (EVALUATE_TABLE_T*)malloc( sizeof(EVALUATE_TABLE_T) );
memcpy( pNextTable, pCurrentNode->pEvaluatReversiTable, sizeof(EVALUATE_TABLE_T) ); /* CurrentノードのTableをコピーする */
ReversingDisc( DiscInfo, pNextTable->aEvaluatReversiTable ); /* コピーしたTableで石をひっくり返す */
/* Create Evaluate Tree Next Node */
pNextNode = (EVALUATE_TREE_T*)malloc( sizeof(EVALUATE_TREE_T) );
pNextNode->Depth = pCurrentNode->pNextDepthNode->Depth;
pNextNode->NodeID = pCurrentNode->NumNextIndex;
pNextNode->DiscInfo.h = DiscInfo.h;
pNextNode->DiscInfo.v = DiscInfo.v;
pNextNode->DiscInfo.CurrentPlayer = DiscInfo.CurrentPlayer;
pNextNode->pEvaluatReversiTable = pNextTable;
pNextNode->Score = CalcScore( pNextNode->DiscInfo.CurrentPlayer,
pNextNode->pEvaluatReversiTable->aEvaluatReversiTable );
pNextNode->pNextNode = NULL;
pNextNode->pNextDepthNode = NULL;
/* Create Evaluate Tree Next Depth Next Node */
MakeTree( pNextNode );
/* pNextNodeに今回生成したNodeのNextNodeアドレスを入れておく
* 新しい選択肢が見つかったらpNextNodeに追加していく */
pNextNode = pNextNode->pNextNode;
}
pCurrentNode->NumNextIndex++; /* 有効な選択肢が見つかったら次の深さのノード数をインクリメントする */
}
}
}
} else {
/* 評価木の深度が限界に達したので、確保した領域を解放してTree生成終了 */
FREE( pCurrentNode->pEvaluatReversiTable );
FREE( pCurrentNode );
return;
}
#ifdef DEBUG_MAKE_NODE
printf("\n [Depth = %d] NumNextIndex = %d" ,pCurrentNode->Depth ,pCurrentNode->NumNextIndex );
#endif
return;
}
void GreedyTensorSearch(const TTrainData& data,
const TVector<int>& splitCounts,
double modelLength,
TProfileInfo& profile,
TFold* fold,
TLearnContext* ctx,
TSplitTree* resSplitTree) {
TSplitTree currentSplitTree;
TrimOnlineCTRcache({fold});
TVector<TIndexType> indices(data.LearnSampleCount);
MATRIXNET_INFO_LOG << "\n";
const bool useStatsFromPrevTree = AreStatsFromPrevTreeUsed(ctx->Params.ObliviousTreeOptions.Get());
if (useStatsFromPrevTree) {
AssignRandomWeights(data.LearnSampleCount, ctx, fold);
ctx->StatsFromPrevTree.GarbageCollect();
}
for (ui32 curDepth = 0; curDepth < ctx->Params.ObliviousTreeOptions->MaxDepth; ++curDepth) {
TCandidateList candList;
AddFloatFeatures(data, ctx, &ctx->StatsFromPrevTree, &candList);
AddOneHotFeatures(data, ctx, &ctx->StatsFromPrevTree, &candList);
AddSimpleCtrs(data, fold, ctx, &ctx->StatsFromPrevTree, &candList);
AddTreeCtrs(data, currentSplitTree, fold, ctx, &ctx->StatsFromPrevTree, &candList);
auto IsInCache = [&fold](const TProjection& proj) -> bool {return fold->GetCtrRef(proj).Feature.empty();};
SelectCtrsToDropAfterCalc(ctx->Params.SystemOptions->CpuUsedRamLimit, data.GetSampleCount(), ctx->Params.SystemOptions->NumThreads, IsInCache, &candList);
CheckInterrupted(); // check after long-lasting operation
if (!useStatsFromPrevTree) {
AssignRandomWeights(data.LearnSampleCount, ctx, fold);
}
profile.AddOperation(TStringBuilder() << "AssignRandomWeights, depth " << curDepth);
double scoreStDev = ctx->Params.ObliviousTreeOptions->RandomStrength * CalcScoreStDev(*fold) * CalcScoreStDevMult(data.LearnSampleCount, modelLength);
TVector<size_t> candLeafCount(candList.ysize(), 1);
const ui64 randSeed = ctx->Rand.GenRand();
ctx->LocalExecutor.ExecRange([&](int id) {
auto& candidate = candList[id];
if (candidate.Candidates[0].SplitCandidate.Type == ESplitType::OnlineCtr) {
const auto& proj = candidate.Candidates[0].SplitCandidate.Ctr.Projection;
if (fold->GetCtrRef(proj).Feature.empty()) {
ComputeOnlineCTRs(data,
*fold,
proj,
ctx,
&fold->GetCtrRef(proj),
&candidate.ResultingCtrTableSize);
candLeafCount[id] = candidate.ResultingCtrTableSize;
}
}
TVector<TVector<double>> allScores(candidate.Candidates.size());
ctx->LocalExecutor.ExecRange([&](int oneCandidate) {
if (candidate.Candidates[oneCandidate].SplitCandidate.Type == ESplitType::OnlineCtr) {
const auto& proj = candidate.Candidates[oneCandidate].SplitCandidate.Ctr.Projection;
Y_ASSERT(!fold->GetCtrRef(proj).Feature.empty());
}
allScores[oneCandidate] = CalcScore(data.AllFeatures,
splitCounts,
*fold,
indices,
ctx->ParamsUsedWithStatsFromPrevTree,
ctx->Params,
candidate.Candidates[oneCandidate].SplitCandidate,
currentSplitTree.GetDepth(),
&ctx->StatsFromPrevTree);
}, NPar::TLocalExecutor::TExecRangeParams(0, candidate.Candidates.ysize())
, NPar::TLocalExecutor::WAIT_COMPLETE);
if (candidate.Candidates[0].SplitCandidate.Type == ESplitType::OnlineCtr && candidate.ShouldDropCtrAfterCalc) {
fold->GetCtrRef(candidate.Candidates[0].SplitCandidate.Ctr.Projection).Feature.clear();
}
TFastRng64 rand(randSeed + id);
rand.Advance(10); // reduce correlation between RNGs in different threads
for (size_t i = 0; i < allScores.size(); ++i) {
double bestScoreInstance = MINIMAL_SCORE;
auto& splitInfo = candidate.Candidates[i];
const auto& scores = allScores[i];
for (int binFeatureIdx = 0; binFeatureIdx < scores.ysize(); ++binFeatureIdx) {
const double score = scores[binFeatureIdx];
const double scoreInstance = TRandomScore(score, scoreStDev).GetInstance(rand);
if (scoreInstance > bestScoreInstance) {
bestScoreInstance = scoreInstance;
splitInfo.BestScore = TRandomScore(score, scoreStDev);
splitInfo.BestBinBorderId = binFeatureIdx;
}
}
}
}, 0, candList.ysize(), NPar::TLocalExecutor::WAIT_COMPLETE);
size_t maxLeafCount = 1;
for (size_t leafCount : candLeafCount) {
maxLeafCount = Max(maxLeafCount, leafCount);
}
fold->DropEmptyCTRs();
CheckInterrupted(); // check after long-lasting operation
profile.AddOperation(TStringBuilder() << "Calc scores " << curDepth);
const TCandidateInfo* bestSplitCandidate = nullptr;
double bestScore = MINIMAL_SCORE;
for (const auto& subList : candList) {
for (const auto& candidate : subList.Candidates) {
double score = candidate.BestScore.GetInstance(ctx->Rand);
TProjection projection = candidate.SplitCandidate.Ctr.Projection;
ECtrType ctrType = ctx->CtrsHelper.GetCtrInfo(projection)[candidate.SplitCandidate.Ctr.CtrIdx].Type;
if (!ctx->LearnProgress.UsedCtrSplits.has(std::make_pair(ctrType, projection)) && score != MINIMAL_SCORE) {
score *= pow(1 / (1 + subList.ResultingCtrTableSize / static_cast<double>(maxLeafCount)), ctx->Params.ObliviousTreeOptions->ModelSizeReg.Get());
}
if (score > bestScore) {
bestScore = score;
bestSplitCandidate = &candidate;
}
}
}
if (bestScore == MINIMAL_SCORE) {
break;
}
if (bestSplitCandidate->SplitCandidate.Type == ESplitType::OnlineCtr) {
TProjection projection = bestSplitCandidate->SplitCandidate.Ctr.Projection;
ECtrType ctrType = ctx->CtrsHelper.GetCtrInfo(projection)[bestSplitCandidate->SplitCandidate.Ctr.CtrIdx].Type;
ctx->LearnProgress.UsedCtrSplits.insert(std::make_pair(ctrType, projection));
}
auto bestSplit = TSplit(bestSplitCandidate->SplitCandidate, bestSplitCandidate->BestBinBorderId);
if (bestSplit.Type == ESplitType::OnlineCtr) {
const auto& proj = bestSplit.Ctr.Projection;
if (fold->GetCtrRef(proj).Feature.empty()) {
size_t totalLeafCount;
ComputeOnlineCTRs(data,
*fold,
proj,
ctx,
&fold->GetCtrRef(proj),
&totalLeafCount);
DropStatsForProjection(*fold, *ctx, proj, &ctx->StatsFromPrevTree);
}
} else if (bestSplit.Type == ESplitType::OneHotFeature) {
bestSplit.BinBorder = data.AllFeatures.OneHotValues[bestSplit.FeatureIdx][bestSplit.BinBorder];
}
SetPermutedIndices(bestSplit, data.AllFeatures, curDepth + 1, *fold, &indices, ctx);
if (useStatsFromPrevTree) {
ctx->ParamsUsedWithStatsFromPrevTree.SelectParametersForSmallestSplitSide(curDepth + 1, *fold, indices, &ctx->LocalExecutor);
}
currentSplitTree.AddSplit(bestSplit);
MATRIXNET_INFO_LOG << BuildDescription(ctx->Layout, bestSplit);
MATRIXNET_INFO_LOG << " score " << bestScore << "\n";
profile.AddOperation(TStringBuilder() << "Select best split " << curDepth);
int redundantIdx = GetRedundantSplitIdx(curDepth + 1, indices);
if (redundantIdx != -1) {
DeleteSplit(curDepth + 1, redundantIdx, ¤tSplitTree, &indices);
MATRIXNET_INFO_LOG << " tensor " << redundantIdx << " is redundant, remove it and stop\n";
break;
}
}
*resSplitTree = std::move(currentSplitTree);
}
void Search(std::vector<int> startNeighbor, int*** srcShitAry, int** srcShitDataAry, int* srcShitSizeAry, const int width, const int height, const int stonesNum, const int* srcMap, const int maxFreeSize){
RESTART :
aStack.clear();
int freeSize = maxFreeSize;
int* map = new int[(width+1) * height]; //対象領域だけを考慮したマップ
for(int i = 0; i < (width+1)*height; i++) map[i] = srcMap[i];
int*** shitAry = srcShitAry; //起点配列表現をした糞（ズク）の配列
int** shitDataAry = srcShitDataAry;
int* shitSizeAry = srcShitSizeAry;
/*
int*** shitAry = new int**[stonesNum]; //起点配列表現をした糞（ズク）の配列
int** shitDataAry = new int*[stonesNum];
int* shitSizeAry = new int[stonesNum];
for(int s = 0; s < stonesNum; s++){
//糞（ズク）配列のコピー
shitAry[s] = new int*[8];
for(int i = 0; i < 8; i++){
if(srcShitAry[s][i] == 0) {
shitAry[s][i] = 0;
continue;
}
shitAry[s][i] = new int[17];
for(int j = 0; j < 17; j++){
shitAry[s][i][j] = srcShitAry[s][i][j];
}
}
//糞（ズク）データ配列のコピー
shitDataAry[s] = new int[8];
for(int i = 0; i < 8; i++){
shitDataAry[s] = srcShitDataAry[s];
}
//サイズ配列のコピー
shitSizeAry[s] = srcShitSizeAry[s];
}*/
int areaAry[1025]; //下の方でつかいまわしている
int subAreaMap[2048];
int putPoints[17];
int putAryLength;
int putShitNum = 0;
int startKn = 0;
std::stack<WideData*> bdStack;
int DEBUG_COUNT = 0;
int kn = 0;
int tmlCount = 0;
while(1){
//幅優先探索用のコード
bool startFlag = false;
if(bdStack.size() == 0){
kn = startKn;
startFlag = true;
startKn++;
if(startKn == stonesNum){
break;
}
} else {
PUT_PROCESS:
kn = bdStack.top()->GetShitNumber();
int remove = RemoveShit(map, kn, shitSizeAry[kn], width, height);
freeSize += remove;
if(remove != 0) {
putShitNum--;
aStack.pop_back();
}
if(!bdStack.top()->Exist()) {
delete bdStack.top();
bdStack.pop();
continue;
}
//実配置処理
wdElement* data = bdStack.top()->GetNext();
while(data->deadArea > minScore || (data->deadArea == minScore && data->needShitNum+putShitNum >= minScore_minShitNum)){
if(!bdStack.top()->Exist()){
delete bdStack.top();
bdStack.pop();
goto PUT_PROCESS;
}
data = bdStack.top()->GetNext();
}
int st = data->st;
int placePoint = data->basePoint;
int DUMMY;
PutShit(map, kn, shitAry[kn][st], placePoint, width+1, height, &DUMMY);
putShitNum++;
freeSize -= shitSizeAry[kn];
Answer_t ans; ans.basePoint=placePoint; ans.state=st; ans.shitNumber=kn;
aStack.push_back(ans);
if(kn == stonesNum-1){
goto TERMINAL;
}
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("\tshit : %d(%c)\n", kn, kn+49);
DEBUG_printMap(map, width+1, height);
printf("free : %d\n", freeSize);
printf("dead : %d\n", data->deadArea);
DEBUG_waitKey();
#endif
#endif
kn++;
while(kn < stonesNum && shitSizeAry[kn] > data->maxAreaSize){
//サイズ的に置けない糞（ズク）をスキップ
kn++;
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("%d skipped\n\n", kn);
#endif
#endif
}
if(kn == stonesNum) {
goto TERMINAL;
}
//int deadArea = CalcDeadArea(map, width+1, height, freeSize, &(shitSizeAry[kn]), stonesNum-kn, areaAry, &needShitNum);
/*
if(minScore < data->deadArea || (minScore == data->deadArea && minScore_minShitNum <= data->needShitNum+putShitNum)){
continue;
}*/
}
//配置処理ここまで
BREADTH_MAKE:
std::vector<wdElement*>* breadthData = new std::vector<wdElement*>();
for(int st = 0; st < 8; st++){
const int* shit = shitAry[kn][st];
if(shitAry[kn][st] == 0) continue;
//ベースポイント配列作成
std::vector<int> baseAry;
if(startFlag){
baseAry = startNeighbor;
} else {
std::vector<int>* neighbor = CalcNeighborPoint(map, width+1, height); //ココ
for(int s = 0; shit[s] != -1; s++){
for(int n = 0; n < neighbor->size(); n++){
int value = (*neighbor)[n] - shit[s];
for(int i = 0; i < baseAry.size(); i++){
if(value == baseAry[i]){
goto NEXT;
}
}
baseAry.push_back(value);
NEXT:;
}
}
delete neighbor;
}
//全てのベースポイントを探索
for(int i = 0; i < baseAry.size(); i++){
int basePoint = baseAry[i];
/*
printf("%d\n", basePoint);
bool a = DEBUG_JudgePutable(map, shit, basePoint, width, height, putPoints, &putAryLength);
DEBUG_printPutShitOnMap(map, putPoints, putAryLength, width, height);
DEBUG_waitKey();
*/
if(JudgePutable(map, shit, basePoint, width, height)){
int neighborNum;
PutShit(map, kn, shitAry[kn][st], basePoint, width+1, height, &neighborNum);
freeSize -= shitSizeAry[kn];
int needShitNum = 0;
int fit;
int checkArea = CheckSubArea(map, width+1, height, freeSize, areaAry, subAreaMap, &fit);
int deadArea = CalcDeadArea(map, width+1, height, freeSize, &(shitSizeAry[kn]), stonesNum-kn, areaAry, &needShitNum);
//doko
RemoveShit(map, kn, shitSizeAry[kn], width, height);
freeSize += shitSizeAry[kn];
//ここでやれるだろ
if(minScore < deadArea || (minScore == deadArea && minScore_minShitNum <= needShitNum+putShitNum)){
continue;
}
wdElement* temp = new wdElement();
temp->st = st;
temp->basePoint = basePoint;
temp->fit = fit;
temp->fit2 = neighborNum;
temp->deadArea = deadArea;
temp->maxAreaSize = checkArea;
temp->needShitNum = needShitNum;
breadthData->push_back(temp);
}
}
}
if(breadthData->size() == 0){ //置けないなら
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("%d cannot place\n\n", kn);
#endif
#endif
delete breadthData;
kn++;
if(kn == stonesNum) goto TERMINAL;
goto BREADTH_MAKE;
} else {
InsertSort(breadthData, breadthData->size());
// for(int i = 0; i < breadthData->size(); i++){
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("shit %d(%c) place pattern\n", kn, kn+49);
#endif
#endif
for(int i = 0; i < breadthData->size() && (breadthData->data())[i]->rank == 0; i++){
wdElement* elm = breadthData->data()[i];
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("\t%d | %d-(%d, %d) : %d [%d %d]", elm->rank, elm->st, elm->basePoint%(width+1), elm->basePoint/(width+1), elm->deadArea, elm->fit, elm->fit2);
DEBUG_waitKey();
#endif
#endif
}
bdStack.push(new WideData(kn, breadthData, startFlag));
}
continue;
TERMINAL:
#ifdef DEBUG_CODE
#ifdef CHECK_CODE
printf("\t<<<terminal>>>\n\n");
#endif
#endif
int score = CalcScore(map, width, height);
bool update = false;
if(minScore > score){
update = true;
} else if(minScore == score){
if(minScore_minShitNum > putShitNum){
update = true;
}
}
if(update){
minScore = score;
minScore_minShitNum = putShitNum;
#ifdef DEBUG_CODE
//DEBUG_printMap(map, width+1, height);
LARGE_INTEGER end;
QueryPerformanceCounter( &end );
printf("score(%d,%d)\n", minScore, minScore_minShitNum);
printf("time : %d\n", (end.QuadPart - start.QuadPart)/liFreq.QuadPart);
#endif
bestAnsStack = aStack;
MAX_TERMINAL_COUNT = HIGH_COUNT;
SendSolution(&bestAnsStack, stonesNum, shitDataAry, width+1);
tmlCount = 0;
} else {
tmlCount++;
#ifdef CHECK_CODE
if(tmlCount%100 == 0){
printf("%d : %d\n", tmlCount/100, kn);
}
#endif
int maxCount = MAX_TERMINAL_COUNT;
if(tmlCount == maxCount){ //十万回終端を探索しても解が改善されないなら
//koko
while(bdStack.size() > 1){
delete bdStack.top();
bdStack.pop();
}
while(aStack.size() > 1){
aStack.pop_back();
}
freeSize += RemoveShitNums(map, startKn, width, height);
//状態をクリア
/*
RemoveAllShit(map, width, height);
freeSize = 0;
*/
putShitNum = 1;
tmlCount = 0;
//
#ifdef DEBUG_CODE
if(MAX_TERMINAL_COUNT == HIGH_COUNT){
printf("focus end : %d\n", MAX_TERMINAL_COUNT);
} else {
printf("replace : %d\n", MAX_TERMINAL_COUNT);
}
#ifdef CHECK_CODE
DEBUG_printMap(map, width+1, height);
printf("free : %d\n", freeSize);
DEBUG_waitKey();
#endif
#endif
MAX_TERMINAL_COUNT = LOW_COUNT;
continue;
}
}
if(bdStack.size() == 0) break;
if(bdStack.top()->GetShitNumber() == stonesNum-1){ //置いた糞（ズク）が最後なら
delete bdStack.top();
bdStack.pop();
int remove = RemoveShit(map, kn, shitSizeAry[kn], width, height);
freeSize += remove;
if(remove != 0) putShitNum--;
aStack.pop_back();
}
}
delete map;
goto RESTART;
}
bool eChatPrefixSpamTester::Check( tString & out, nTimeRolling & timeOut, eChatPrefixSpamType & typeOut )
{
if ( !ShouldCheckMessage( say_ ) )
return false;
RemoveTimedOutPrefixes();
// check from known prefixes
if ( HasKnownPrefix( out, timeOut ) )
{
typeOut = eChatPrefixSpamType_Known;
return true;
}
eChatLastSaid::SaidList & lastSaid = player_->GetLastSaid().lastSaid_;
// Map of Prefix => Data
std::map< tString, PrefixEntry > foundPrefixes;
for ( eChatLastSaid::SaidList::iterator it = lastSaid.begin(); it != lastSaid.end(); ++it )
{
eChatSaidEntry & said = *it;
if ( !ShouldCheckMessage( said ) || say_.Said() == said.Said() )
continue;
int common = CommonPrefix( say_.Said(), said.Said() );
if ( common > 0 )
{
const tString prefix = say_.Said().SubStr(0, common);
// User is talking to a player. Not prefix spam, but we still check the
// message text excluding the player name.
// Example: Player 1: grind center. [etc...]
int nameLen;
if ( ChatDirectedTowardsPlayer( prefix, nameLen ) )
{
said.SetType( eChatMessageType_Public_Direct );
said.said_ = said.said_.SubStr( nameLen + 1 );
return false;
}
if ( foundPrefixes.find(prefix) == foundPrefixes.end() )
foundPrefixes[prefix] = PrefixEntry();
PrefixEntry & data = foundPrefixes[prefix];
data.occurrences += 1;
CalcScore( data, common, prefix );
if ( data.score >= se_prefixSpamRequiredScore )
{
#ifdef DEBUG
con << "Spam prefix found: \"" << se_EscapeColors( prefix ) << "\" with score " << data.score << '\n';
#endif
nTimeRolling t = player_->GetLastSaid().AddPrefix( prefix, data.score, say_.Time() );
timeOut = RemainingTime( t );
// We caught the prefix. Don't catch words that start with the prefix.
RemovePrefixEntries( prefix, said );
out = se_EscapeColors( prefix );
typeOut = eChatPrefixSpamType_New;
return true;
}
}
}
return false;
}