C++ InitRandom函数代码示例

void NeuronalNet::CreateNet() {
	// init random weights:

	
	InitRandom(&inputWeights, 71);
	InitRandom(&hiddenBias, 25);
	InitRandom(&hiddenWeights, 25);
	InitRandom(&outputBias, 1);
	
}

static void NextRandom(double *random, long n)
{
  long j;
  if (idum<=0) InitRandom(0.0);

  while (n--) {
    /* compute idum= (IA1*idum)%IM1 without overflow */
    idum= IA1*(idum%IQ1) - IR1*(idum/IQ1);
    if (idum<0) idum+= IM1;

    /* compute idum2= (IA2*idum2)%IM2 without overflow */
    idum2= IA2*(idum2%IQ2) - IR2*(idum2/IQ2);
    if (idum2<0) idum2+= IM2;

    /* previous result is used to determine which element of the shuffle
       table to use for this result */
    j= iy/NDIV;            /* in range 0..NTAB-1 */
    iy= iv[j]-idum2;
    iv[j]= idum;
    if (iy<1) iy+= IMM1;

    /* Really only IMM1 possible values can be returned, 1<=iy<=IMM1.
       Algorithm given by Press and Teukolsky has a slight bug.
       Here, the return values are centered in IMM1 equal bins.
       If 2.e9 distinct values are not enough, could use, say, idum2
       to scoot the points around randomly within bins...  */
    *random++= AM*(iy-0.5);
  }
}

int main( int argc, char **argv )
{
  int num_sample=100000;
  int t0=clock();
  InitRandom(100000);
  int t1=clock();

  ///Initialization performance
  printf("** Time elapsed for initialization of %d sample is %d\n \n",num_sample,t1-t0);
  Hash2D.Set(Allocated.begin(),Allocated.end());

  ///Box Query performance
  t0=clock();
  MyScalarType avg_test=TestBox(num_sample);
  t1=clock();
  printf("** Time elapsed for %d BOX queries is %d\n, average found %5.5f \n \n",num_sample,t1-t0,avg_test);
  

  ///Intersecting segment performance
  t0=clock();
  MyScalarType avg_int=TestIntersection(num_sample);
  t1=clock();
  printf("** Time elapsed for %d INTERSECTION queries is %d\n, average found %5.5f \n \n",num_sample,t1-t0,avg_int);
	
  ///closest test
  t0=clock();
  MyScalarType avg_clos=TestClosest(num_sample);
  t1=clock();
  printf("** Time elapsed for %d CLOSEST queries is %d\n, average found %5.5f \n \n",num_sample,t1-t0,avg_clos);
	
 ///reinitialize structure
  MyMark.mark=0;
  Hash2D.Clear();
  int n_test=1000;
  InitRandom(n_test,100,0.1);
  Hash2D.Set(Allocated.begin(),Allocated.end());

  int tested_int=TestCorrectIntersect(n_test);
  printf("** Correct Intersect on %d test are %d \n",n_test,tested_int);
	
  int tested_clos=TestCorrectClosest(n_test);
  printf("** Correct Closest on %d test are %d \n",n_test,tested_clos);

  return 0;
}

void Y_random_seed(int nArgs)
{
  double seed= 0.0;
  if (nArgs==1) {
    if (YNotNil(sp)) seed= YGetReal(sp);
  } else if (nArgs>0) {
    YError("random_seed takes exactly zero or one arguments");
  }
  InitRandom(seed);
}

void InitBackground()
{
	int x, y;

	InitRandom();
	for ( x = 0; x < PARALLAX_GRID_WIDTH; x++ ) {
		for ( y = 0; y < PARALLAX_GRID_HEIGHT; y++ ) {
			front_tiles[ x ][ y ] = GetRandom() % num_star_tiles;
			back_tiles[ x ][ y ] = GetRandom() % num_star_tiles;
		}
	}
}

/*************************************************************************
* This function is the entry point for PWMETIS that accepts exact weights
* for the target partitions
**************************************************************************/
void METIS_WPartGraphRecursive(int *nvtxs, idxtype *xadj, idxtype *adjncy, idxtype *vwgt, 
                               idxtype *adjwgt, int *wgtflag, int *numflag, int *nparts, 
                               floattype *tpwgts, int *options, int *edgecut, idxtype *part)
{
  int i, j;
  GraphType graph;
  CtrlType ctrl;
  floattype *mytpwgts;

  if (*numflag == 1)
    Change2CNumbering(*nvtxs, xadj, adjncy);

  SetUpGraph(&graph, OP_PMETIS, *nvtxs, 1, xadj, adjncy, vwgt, adjwgt, *wgtflag);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType = PMETIS_CTYPE;
    ctrl.IType = PMETIS_ITYPE;
    ctrl.RType = PMETIS_RTYPE;
    ctrl.dbglvl = PMETIS_DBGLVL;
  }
  else {
    ctrl.CType = options[OPTION_CTYPE];
    ctrl.IType = options[OPTION_ITYPE];
    ctrl.RType = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }
  ctrl.optype = OP_PMETIS;
  ctrl.CoarsenTo = 20;
  ctrl.maxvwgt = 1.5*(idxsum(*nvtxs, graph.vwgt)/ctrl.CoarsenTo);

  mytpwgts = fmalloc(*nparts, "PWMETIS: mytpwgts");
  for (i=0; i<*nparts; i++) 
    mytpwgts[i] = tpwgts[i];

  InitRandom(-1);

  AllocateWorkSpace(&ctrl, &graph, *nparts);

  IFSET(ctrl.dbglvl, DBG_TIME, InitTimers(&ctrl));
  IFSET(ctrl.dbglvl, DBG_TIME, starttimer(ctrl.TotalTmr));

  *edgecut = MlevelRecursiveBisection(&ctrl, &graph, *nparts, part, mytpwgts, 1.000, 0);

  IFSET(ctrl.dbglvl, DBG_TIME, stoptimer(ctrl.TotalTmr));
  IFSET(ctrl.dbglvl, DBG_TIME, PrintTimers(&ctrl));

  FreeWorkSpace(&ctrl, &graph);
  free(mytpwgts);

  if (*numflag == 1)
    Change2FNumbering(*nvtxs, xadj, adjncy, part);
}

/*************************************************************************
* This function is the entry point for OEMETIS
**************************************************************************/
void METIS_EdgeND(int *nvtxs, idxtype *xadj, idxtype *adjncy, int *numflag, int *options, 
                  idxtype *perm, idxtype *iperm) 
{
  int i, j;
  GraphType graph;
  CtrlType ctrl;

  if (*numflag == 1)
    Change2CNumbering(*nvtxs, xadj, adjncy);

  SetUpGraph(&graph, OP_OEMETIS, *nvtxs, 1, xadj, adjncy, NULL, NULL, 0);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType = OEMETIS_CTYPE;
    ctrl.IType = OEMETIS_ITYPE;
    ctrl.RType = OEMETIS_RTYPE;
    ctrl.dbglvl = OEMETIS_DBGLVL;
  }
  else {
    ctrl.CType = options[OPTION_CTYPE];
    ctrl.IType = options[OPTION_ITYPE];
    ctrl.RType = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }
  ctrl.oflags  = 0;
  ctrl.pfactor = -1;
  ctrl.nseps   = 1;

  ctrl.optype = OP_OEMETIS;
  ctrl.CoarsenTo = 20;
  ctrl.maxvwgt = 1.5*(idxsum(*nvtxs, graph.vwgt)/ctrl.CoarsenTo);

  InitRandom(-1);

  AllocateWorkSpace(&ctrl, &graph, 2);

  IFSET(ctrl.dbglvl, DBG_TIME, InitTimers(&ctrl));
  IFSET(ctrl.dbglvl, DBG_TIME, starttimer(ctrl.TotalTmr));

  MlevelNestedDissection(&ctrl, &graph, iperm, ORDER_UNBALANCE_FRACTION, *nvtxs);

  IFSET(ctrl.dbglvl, DBG_TIME, stoptimer(ctrl.TotalTmr));
  IFSET(ctrl.dbglvl, DBG_TIME, PrintTimers(&ctrl));

  for (i=0; i<*nvtxs; i++)
    perm[iperm[i]] = i;

  FreeWorkSpace(&ctrl, &graph);

  if (*numflag == 1)
    Change2FNumberingOrder(*nvtxs, xadj, adjncy, perm, iperm);
}

SRBM::SRBM(int vNum, int hNum): 
m_vNum(vNum), m_hNum(hNum)
{
	// allocate space
	m_pVB = (double *) m_pool.Allocate(sizeof(double) * vNum);
	m_pHB = (double *) m_pool.Allocate(sizeof(double) * hNum);
	m_ppW = (double **)m_pool.Allocate(sizeof(double*) * vNum);
	for (int i = 0; i < vNum; ++i)
		m_ppW[i] =  (double *) m_pool.Allocate(sizeof(double) * hNum);

	// randomly initialize 
	InitRandom();
}

/*************************************************************************
* This function is the entry point for ONWMETIS. It requires weights on the
* vertices. It is for the case that the matrix has been pre-compressed.
**************************************************************************/
void METIS_NodeComputeSeparator(int *nvtxs, idxtype *xadj, idxtype *adjncy, idxtype *vwgt, 
           idxtype *adjwgt, float *ubfactor, int *options, int *sepsize, idxtype *part) 
{
  int i, j, tvwgt, tpwgts[2];
  GraphType graph;
  CtrlType ctrl;

  SetUpGraph(&graph, OP_ONMETIS, *nvtxs, 1, xadj, adjncy, vwgt, adjwgt, 3);
  tvwgt = idxsum(*nvtxs, graph.vwgt);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType  = ONMETIS_CTYPE;
    ctrl.IType  = ONMETIS_ITYPE;
    ctrl.RType  = ONMETIS_RTYPE;
    ctrl.dbglvl = ONMETIS_DBGLVL;
  }
  else {
    ctrl.CType  = options[OPTION_CTYPE];
    ctrl.IType  = options[OPTION_ITYPE];
    ctrl.RType  = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }

  ctrl.oflags    = OFLAG_COMPRESS; /* For by-passing the pre-coarsening for multiple runs */
  ctrl.RType     = 2;  /* Standard 1-sided node refinement code */
  ctrl.pfactor   = 0;
  ctrl.nseps     = 5;  /* This should match NUM_INIT_MSECTIONS in ParMETISLib/defs.h */
  ctrl.optype    = OP_ONMETIS;

  InitRandom(options[7]);

  AllocateWorkSpace(&ctrl, &graph, 2);

  /*============================================================
   * Perform the bisection
   *============================================================*/ 
  tpwgts[0] = tvwgt/2;
  tpwgts[1] = tvwgt-tpwgts[0];

  MlevelNodeBisectionMultiple(&ctrl, &graph, tpwgts, *ubfactor*.95);

  *sepsize = graph.pwgts[2];
  idxcopy(*nvtxs, graph.where, part);

  GKfree((void **)&graph.gdata, &graph.rdata, &graph.label, LTERM);


  FreeWorkSpace(&ctrl, &graph);

}

/*************************************************************************
* This function is the entry point for ONWMETIS. It requires weights on the
* vertices. It is for the case that the matrix has been pre-compressed.
**************************************************************************/
void METIS_NodeComputeSeparator(idxtype *nvtxs, idxtype *xadj, idxtype *adjncy, idxtype *vwgt, 
           idxtype *adjwgt, idxtype *options, idxtype *sepsize, idxtype *part) 
{
  idxtype i, j, tvwgt, tpwgts[2];
  GraphType graph;
  CtrlType ctrl;

  SetUpGraph(&graph, OP_ONMETIS, *nvtxs, 1, xadj, adjncy, vwgt, adjwgt, 3);
  tvwgt = idxsum(*nvtxs, graph.vwgt, 1);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType = ONMETIS_CTYPE;
    ctrl.IType = ONMETIS_ITYPE;
    ctrl.RType = ONMETIS_RTYPE;
    ctrl.dbglvl = ONMETIS_DBGLVL;
  }
  else {
    ctrl.CType = options[OPTION_CTYPE];
    ctrl.IType = options[OPTION_ITYPE];
    ctrl.RType = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }

  ctrl.oflags  = 0;
  ctrl.pfactor = 0;
  ctrl.nseps = 3;
  ctrl.optype = OP_ONMETIS;
  ctrl.CoarsenTo = amin(100, *nvtxs-1);
  ctrl.maxvwgt = 1.5*tvwgt/ctrl.CoarsenTo;

  InitRandom(options[7]);

  AllocateWorkSpace(&ctrl, &graph, 2);

  /*============================================================
   * Perform the bisection
   *============================================================*/ 
  tpwgts[0] = tvwgt/2;
  tpwgts[1] = tvwgt-tpwgts[0];

  MlevelNodeBisectionMultiple(&ctrl, &graph, tpwgts, 1.02);

  *sepsize = graph.pwgts[2];
  idxcopy(*nvtxs, graph.where, part);

  FreeGraph(&graph, 0);

  FreeWorkSpace(&ctrl, &graph);

}

/*************************************************************************
* This function is the entry point for KWMETIS
**************************************************************************/
void METIS_mCPartGraphKway(int *nvtxs, int *ncon, idxtype *xadj, idxtype *adjncy, 
                          idxtype *vwgt, idxtype *adjwgt, int *wgtflag, int *numflag, 
                          int *nparts, floattype *rubvec, int *options, int *edgecut, 
                          idxtype *part)
{
  int i, j;
  GraphType graph;
  CtrlType ctrl;

  if (*numflag == 1)
    Change2CNumbering(*nvtxs, xadj, adjncy);

  SetUpGraph(&graph, OP_KMETIS, *nvtxs, *ncon, xadj, adjncy, vwgt, adjwgt, *wgtflag);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType  = McKMETIS_CTYPE;
    ctrl.IType  = McKMETIS_ITYPE;
    ctrl.RType  = McKMETIS_RTYPE;
    ctrl.dbglvl = McKMETIS_DBGLVL;
  }
  else {
    ctrl.CType  = options[OPTION_CTYPE];
    ctrl.IType  = options[OPTION_ITYPE];
    ctrl.RType  = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }
  ctrl.optype = OP_KMETIS;
  ctrl.CoarsenTo = amax((*nvtxs)/(20*log2Int(*nparts)), 30*(*nparts));

  ctrl.nmaxvwgt = 1.5/(1.0*ctrl.CoarsenTo);

  InitRandom(-1);

  AllocateWorkSpace(&ctrl, &graph, *nparts);

  IFSET(ctrl.dbglvl, DBG_TIME, InitTimers(&ctrl));
  IFSET(ctrl.dbglvl, DBG_TIME, starttimer(ctrl.TotalTmr));

  ASSERT(CheckGraph(&graph));
  *edgecut = MCMlevelKWayPartitioning(&ctrl, &graph, *nparts, part, rubvec);

  IFSET(ctrl.dbglvl, DBG_TIME, stoptimer(ctrl.TotalTmr));
  IFSET(ctrl.dbglvl, DBG_TIME, PrintTimers(&ctrl));

  FreeWorkSpace(&ctrl, &graph);

  if (*numflag == 1)
    Change2FNumbering(*nvtxs, xadj, adjncy, part);
}

/*************************************************************************
* This function is the entry point for KWMETIS with seed specification
* in options[7] 
**************************************************************************/
void METIS_WPartGraphKway2(idxtype *nvtxs, idxtype *xadj, idxtype *adjncy, idxtype *vwgt, 
                          idxtype *adjwgt, idxtype *wgtflag, idxtype *numflag, idxtype *nparts, 
                          float *tpwgts, idxtype *options, idxtype *edgecut, idxtype *part)
{
  idxtype i, j;
  GraphType graph;
  CtrlType ctrl;

  if (*numflag == 1)
    Change2CNumbering(*nvtxs, xadj, adjncy);

  SetUpGraph(&graph, OP_KMETIS, *nvtxs, 1, xadj, adjncy, vwgt, adjwgt, *wgtflag);

  if (options[0] == 0) {  /* Use the default parameters */
    ctrl.CType = KMETIS_CTYPE;
    ctrl.IType = KMETIS_ITYPE;
    ctrl.RType = KMETIS_RTYPE;
    ctrl.dbglvl = KMETIS_DBGLVL;
  }
  else {
    ctrl.CType = options[OPTION_CTYPE];
    ctrl.IType = options[OPTION_ITYPE];
    ctrl.RType = options[OPTION_RTYPE];
    ctrl.dbglvl = options[OPTION_DBGLVL];
  }
  ctrl.optype = OP_KMETIS;
  ctrl.CoarsenTo = 20*(*nparts);
  ctrl.maxvwgt = 1.5*((graph.vwgt ? idxsum(*nvtxs, graph.vwgt, 1) : (*nvtxs))/ctrl.CoarsenTo);

  InitRandom(options[7]);

  AllocateWorkSpace(&ctrl, &graph, *nparts);

  IFSET(ctrl.dbglvl, DBG_TIME, InitTimers(&ctrl));
  IFSET(ctrl.dbglvl, DBG_TIME, gk_startcputimer(ctrl.TotalTmr));

  *edgecut = MlevelKWayPartitioning(&ctrl, &graph, *nparts, part, tpwgts, 1.03);

  IFSET(ctrl.dbglvl, DBG_TIME, gk_stopcputimer(ctrl.TotalTmr));
  IFSET(ctrl.dbglvl, DBG_TIME, PrintTimers(&ctrl));

  FreeWorkSpace(&ctrl, &graph);

  if (*numflag == 1)
    Change2FNumbering(*nvtxs, xadj, adjncy, part);
}

LearnableParameter<ElemType>::LearnableParameter(const ScriptableObjects::IConfigRecordPtr configp) :
    LearnableParameter(configp->Get(L"deviceId"), L"<placeholder>", configp->Get(L"shape"))
{
    // TODO: Change dimensions to take a generic tensor instead. That will be a (minor) breaking change that will require fix-ups when converting from NDL to BrainScript.
    AttachInputsFromConfig(configp, this->GetExpectedNumInputs());
    // parameters[rows, [cols=1]] plus other optional parameters (learningRateMultiplier=[1|0|float], init=[uniform|gaussian|fixedvalue], initValueScale=[1|float], value=[0|float])
    if (configp->Exists(L"learningRateMultiplier"))
        SetLearningRateMultiplier(configp->Get(L"learningRateMultiplier"));
    else if (configp->Exists(L"needsGradient") || configp->Exists(L"needGradient") || configp->Exists(L"computeGradient"))
        InvalidArgument("Deprecated parameter names needsGradient|needGradient|computeGradient are not supported in BrainScript. Use learningRateMultiplier instead.");

    wstring initString = configp->Get(L"init");
    if (initString == L"fixedValue")
        Value().SetValue((ElemType) configp->Get(L"value"));
    else if (initString == L"uniform" || initString == L"gaussian")
    {
        // TODO: add these options also to old NDL
        static unsigned long randomSeed = 1;
        int forcedRandomSeed = configp->Get(L"randomSeed"); // forcing a specific random seed is useful for testing to get repeatable initialization independent of evaluation order
        InitRandom((initString == L"uniform"), forcedRandomSeed < 0 ? randomSeed++ : (unsigned long) forcedRandomSeed, configp->Get(L"initValueScale"), configp->Get(L"initOnCPUOnly"));
    }
    else if (initString == L"fromFile")
    {
        wstring initFromFilePath = configp->Get(L"initFromFilePath");
        if (initFromFilePath.empty())
            RuntimeError("initFromFilePath parameter must be provided when using \"fromFile\" initialization method");
        InitFromFile(initFromFilePath);
    }
    else if (initString == L"fromLiteral")
    {
        wstring initFromLiteral = configp->Get(L"initFromLiteral");
        if (initFromLiteral.empty())
            RuntimeError("initFromLiteral parameter must be provided when using \"fromLiteral\" initialization method");
        size_t numRows, numCols;
        auto array = File::LoadMatrixFromStringLiteral<ElemType>(msra::strfun::utf8(initFromLiteral), numRows, numCols);
        InitFromArray(array, numRows, numCols);
    }
    else
        RuntimeError("init must be one of the values of [ uniform | gaussian | fixedValue | fromFile ]");
}

int main(int argc, char *argv[])
{
#if HAVE_SETBUF
    setbuf(stdin, NULL);
#endif
       
    OpenLogFile("Amy.log");

    InitMoves();

    InitAll();
    HashInit();

    /*
     * Process rc file first, then command line options. This way command
     * line options can override rc file settings.
     */

    ProcessRCFile();
    ProcessOptions(argc, argv);

    ShowVersion();

    AllocateHT();
    InitEGTB(EGTBPath);
    RecogInit();

    DoBookLearning();

    Print(0, "\n");

    strcpy(AutoSaveFileName, GetTmpFileName());

    /* Ensure true random behavior. */
    InitRandom(GetTime());

    StateMachine();

    return 0;
}

 void Util::InitUtil() {
   // num_bit16_table_[]を初期化する。
   InitNumBit16Table();
   // attack_table_***_[][]を初期化する。
   InitAttackTable();
   // pawn_move_[][]を初期化する。
   InitPawnMove();
   // pawn_2step_move_[][]を初期化する。
   InitPawn2StepMove();
   // pawn_attack_[][]を初期化する。
   InitPawnAttack();
   // knight_move_[]を初期化する。
   InitKnightMove();
   // bishop_move_[]を初期化する。
   InitBishopMove();
   // rook_move_[]を初期化する。
   InitRookMove();
   // king_move_[]を初期化する。
   InitKingMove();
   // ランダム関連を初期化する。
   InitRandom();
 }