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NiuTrans.Tensor
Commit d69372b3 by xiaotong
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add a new class XParamKeeper

parent 90599e05
正在显示 包含 125 行增加 和 101 行删除
source/train/TTrain.cpp
...@@ -90,7 +90,7 @@ void TestTrain() ...@@ -90,7 +90,7 @@ void TestTrain()
TTModel model; TTModel model;
model.Init(config, -1); model.Init(config, -1);
tmpTT = (XTensor*)model.params[0]; tmpTT = model.params[0].param;
XOptimizer optimizer; XOptimizer optimizer;
optimizer.Init(config); optimizer.Init(config);
......
source/train/XLeader.cpp
...@@ -91,8 +91,8 @@ Set the server model. It distributes the server-side parameters on different dev ...@@ -91,8 +91,8 @@ Set the server model. It distributes the server-side parameters on different dev
void XLeader::SetServerModel(XConfig * config, XModel * model, XList * memberModels) void XLeader::SetServerModel(XConfig * config, XModel * model, XList * memberModels)
{ {
serverModel.Clear(); serverModel.Clear();
for (int i = 0; i < model->params.count; i++) { for (int i = 0; i < model->paramNum; i++) {
XTensor * param = (XTensor*)model->params[i]; XTensor * param = model->params[i].param;
serverModel.AddParam(param); serverModel.AddParam(param);
} }
......
source/train/XModel.cpp
...@@ -33,17 +33,34 @@ ...@@ -33,17 +33,34 @@
/* the nts (NiuTrans.Tensor) namespace */ /* the nts (NiuTrans.Tensor) namespace */
namespace nts { namespace nts {
/* constructor */
XParamKeeper::XParamKeeper()
{
param = NULL;
flag = PARAM_STATE_NOT_READY;
MUTEX_INIT(accessLock);
MUTEX_INIT(trainLock);
}
/* constructor */
XParamKeeper::~XParamKeeper()
{
MUTEX_DELE(accessLock);
MUTEX_DELE(trainLock);
}
/* constructor */ /* constructor */
XModel::XModel() XModel::XModel()
{ {
flags = NULL; params = NULL;
paramNum = 0;
MUTEX_INIT(modelMutex); MUTEX_INIT(modelMutex);
} }
/* de-constructor */ /* de-constructor */
XModel::~XModel() XModel::~XModel()
{ {
delete[] flags;
Clear(); Clear();
MUTEX_DELE(modelMutex); MUTEX_DELE(modelMutex);
} }
...@@ -51,7 +68,8 @@ XModel::~XModel() ...@@ -51,7 +68,8 @@ XModel::~XModel()
/* clear the model */ /* clear the model */
void XModel::Clear() void XModel::Clear()
{ {
params.Clear(); delete[] params;
paramNum = 0;
} }
/* /*
...@@ -104,22 +122,27 @@ add a parameter tensor ...@@ -104,22 +122,27 @@ add a parameter tensor
void XModel::AddParam(XTensor* param) void XModel::AddParam(XTensor* param)
{ {
param->SetVarFlag(); param->SetVarFlag();
params.Add(param);
PARAM_STATE * newFlags = new PARAM_STATE[params.count]; XParamKeeper * newParams = new XParamKeeper[paramNum + 1];
memcpy(newFlags, flags, sizeof(PARAM_STATE) * (params.count - 1)); for (int i = 0; i < paramNum; i++) {
newFlags[params.count - 1] = PARAM_STATE_NOT_READY; newParams[i].param = params[i].param;
newParams[i].flag = params[i].flag;
}
delete[] flags; newParams[paramNum].param = param;
flags = newFlags; newParams[paramNum].flag = PARAM_STATE_NOT_READY;
delete[] params;
params = newParams;
paramNum++;
} }
/* check if the parameters are well-defined for training */ /* check if the parameters are well-defined for training */
bool XModel::CheckParam() bool XModel::CheckParam()
{ {
for (int i = 0; i < params.count; i++) { for (int i = 0; i < paramNum; i++) {
XTensor * param = (XTensor*)params[i]; XTensor * param = params[i].param;
if (!param->isGrad) if (!param->isGrad)
return false; return false;
} }
...@@ -130,25 +153,18 @@ bool XModel::CheckParam() ...@@ -130,25 +153,18 @@ bool XModel::CheckParam()
/* initial model for running the it */ /* initial model for running the it */
void XModel::InitForRun() void XModel::InitForRun()
{ {
for (int i = 0; i < params.count; i++) { for (int i = 0; i < paramNum; i++) {
XTensor * param = (XTensor*)params[i]; params[i].param->isGradFinished = false;
param->isGradFinished = false; params[i].flag = PARAM_STATE_NOT_READY;
flags[i] = PARAM_STATE_NOT_READY;
} }
} }
/* refresh the model */ /* refresh the model */
void XModel::RefreshMe() void XModel::RefreshMe()
{ {
for (int i = 0; i < params.count; i++) { for (int i = 0; i < paramNum; i++) {
XTensor * param = params.GetItem(i); params[i].param->isGradFinished = false;
param->isGradFinished = false; params[i].flag = PARAM_STATE_NOT_READY;
}
delete[] flags;
flags = new PARAM_STATE[params.count];
for (int i = 0; i < params.count; i++) {
flags[i] = PARAM_STATE_NOT_READY;
} }
} }
......
source/train/XModel.h
...@@ -50,6 +50,31 @@ enum PARAM_STATE { PARAM_STATE_NOT_READY, ...@@ -50,6 +50,31 @@ enum PARAM_STATE { PARAM_STATE_NOT_READY,
PARAM_STATE_COLLECTED, PARAM_STATE_COLLECTED,
PARAM_STATE_UPDATED }; PARAM_STATE_UPDATED };
/* parameter keeper */
class XParamKeeper
{
public:
/* the parameter */
XTensor * param;
/* the parameter state */
PARAM_STATE flag;
/* a mutex for locking and unlocking the parameter */
MUTEX_HANDLE accessLock;
/* a mutex of the overall training */
MUTEX_HANDLE trainLock;
public:
/* constructor */
XParamKeeper();
/* constructor */
~XParamKeeper();
};
/* a model template for training */ /* a model template for training */
class XModel class XModel
{ {
...@@ -58,11 +83,11 @@ protected: ...@@ -58,11 +83,11 @@ protected:
MUTEX_HANDLE modelMutex; MUTEX_HANDLE modelMutex;
public: public:
/* the list of model parameters (pointers to the parameter tensor) */ /* the list of model parameters */
TensorList params; XParamKeeper * params;
/* flags of the parameters */ /* parameter number */
PARAM_STATE * flags; int paramNum;
public: public:
......
source/train/XWorkerBroadcast.cpp
...@@ -57,20 +57,17 @@ broadcast data for a parameter ...@@ -57,20 +57,17 @@ broadcast data for a parameter
*/ */
void XWorkerBroadcast::BroadcastDataSingle(XModel * source, XList * targetList, int pid) void XWorkerBroadcast::BroadcastDataSingle(XModel * source, XList * targetList, int pid)
{ {
CheckNTErrors(source->flags[pid] == PARAM_STATE_UPDATED, CheckNTErrors(source->params[pid].flag == PARAM_STATE_UPDATED,
"The parameter is not ready for broadcasting"); "The parameter is not ready for broadcasting");
TensorList & sp = source->params;
for (int i = 0; i < targetList->count; i++) { for (int i = 0; i < targetList->count; i++) {
XModel * target = (XModel*)targetList->GetItem(i); XModel * target = (XModel*)targetList->GetItem(i);
TensorList & tp = target->params;
/* data transmit */ /* data transmit */
BroadcastP2P(sp.GetItem(pid), tp.GetItem(pid)); BroadcastP2P(source->params[pid].param, target->params[pid].param);
/* update the flag */ /* update the flag */
target->flags[pid] = PARAM_STATE_UPDATED; target->params[pid].flag = PARAM_STATE_UPDATED;
} }
} }
...@@ -82,21 +79,20 @@ broadcast data for a model ...@@ -82,21 +79,20 @@ broadcast data for a model
*/ */
void XWorkerBroadcast::BroadcastData(XModel * source, XList * targetList, long sleepTime) void XWorkerBroadcast::BroadcastData(XModel * source, XList * targetList, long sleepTime)
{ {
TensorList & sp = source->params;
int finished = 0; int finished = 0;
int * finishedFlag = new int[sp.count]; int * finishedFlag = new int[source->paramNum];
memset(finishedFlag, 0, sizeof(int) * sp.count); memset(finishedFlag, 0, sizeof(int) * source->paramNum);
/* check */ /* check */
for (int i = 0; i < targetList->count; i++) { for (int i = 0; i < targetList->count; i++) {
TensorList & tp = ((XModel*)targetList->GetItem(i))->params; XModel * target = (XModel*)targetList->GetItem(i);
CheckNTErrors(sp.count == tp.count, "Incompatiable models!"); CheckNTErrors(source->paramNum == target->paramNum, "Incompatiable models!");
} }
/* the major body of broadcasting */ /* the major body of broadcasting */
while (1) { while (1) {
for (int i = 0; i < sp.count; i++) { for (int i = 0; i < source->paramNum; i++) {
if (source->flags[i] == PARAM_STATE_UPDATED && finishedFlag[i] == 0) { if (source->params[i].flag == PARAM_STATE_UPDATED && finishedFlag[i] == 0) {
/* broadcasting */ /* broadcasting */
BroadcastDataSingle(source, targetList, i); BroadcastDataSingle(source, targetList, i);
...@@ -107,7 +103,7 @@ void XWorkerBroadcast::BroadcastData(XModel * source, XList * targetList, long s ...@@ -107,7 +103,7 @@ void XWorkerBroadcast::BroadcastData(XModel * source, XList * targetList, long s
} }
} }
if (finished == sp.count * targetList->count) if (finished == source->paramNum * targetList->count)
break; break;
XSleep(sleepTime); XSleep(sleepTime);
...@@ -186,7 +182,7 @@ bool XWorkerBroadcast::AddJobBroadcastSingle(XModel * source, XList * targetList ...@@ -186,7 +182,7 @@ bool XWorkerBroadcast::AddJobBroadcastSingle(XModel * source, XList * targetList
{ {
CheckNTErrors(source != NULL, "no input source tensor!"); CheckNTErrors(source != NULL, "no input source tensor!");
CheckNTErrors(targetList != NULL, "no input target tensor list!"); CheckNTErrors(targetList != NULL, "no input target tensor list!");
CheckNTErrors(pid >= 0 && pid < source->params.count, "illegal parameter index!"); CheckNTErrors(pid >= 0 && pid < source->paramNum, "illegal parameter index!");
XList args; XList args;
args.Add(this); args.Add(this);
......
source/train/XWorkerCollect.cpp
...@@ -67,26 +67,25 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -67,26 +67,25 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
XOptimizer * optimizer, XWorkerUpdate * updater, XOptimizer * optimizer, XWorkerUpdate * updater,
XWorkerBroadcast * broadcaster, long sleepTime) XWorkerBroadcast * broadcaster, long sleepTime)
{ {
TensorList & tp = server->params;
int finished = 0; int finished = 0;
for (int j = 0; j < tp.count; j++) for (int j = 0; j < server->paramNum; j++)
server->flags[j] = PARAM_STATE_NOT_READY; server->params[j].flag = PARAM_STATE_NOT_READY;
/* check */ /* check */
for (int i = 0; i < memberAll->count; i++) { for (int i = 0; i < memberAll->count; i++) {
TensorList & sp = ((XModel*)memberAll->GetItem(i))->params; XModel * source = (XModel*)memberAll->GetItem(i);
CheckNTErrors(sp.count == tp.count, "Incompatiable models!"); CheckNTErrors(source->paramNum == server->paramNum, "Incompatiable models!");
} }
for (int i = 0; i < memberActive->count; i++) { for (int i = 0; i < memberActive->count; i++) {
TensorList & sp = ((XModel*)memberActive->GetItem(i))->params; XModel * source = (XModel*)memberActive->GetItem(i);
CheckNTErrors(sp.count == tp.count, "Incompatiable models!"); CheckNTErrors(source->paramNum == server->paramNum, "Incompatiable models!");
} }
/* counts how many member models are collect for each parameters */ /* counts how many member models are collect for each parameters */
int * finishedCount = new int[tp.count]; int * finishedCount = new int[server->paramNum];
memset(finishedCount, 0, sizeof(int) * tp.count); memset(finishedCount, 0, sizeof(int) * server->paramNum);
/* This is a simple implementation of the wait-and-collect process. But /* This is a simple implementation of the wait-and-collect process. But
there is a risk that some models are not available, that is, the there is a risk that some models are not available, that is, the
...@@ -94,26 +93,29 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -94,26 +93,29 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
to break after waiting for a short time. */ to break after waiting for a short time. */
while (1) { while (1) {
if (collectMode == DATA_COLLECT_P2P) { if (collectMode == DATA_COLLECT_P2P) {
for (int j = 0; j < tp.count; j++) { for (int j = 0; j < server->paramNum; j++) {
XParamKeeper &paramServer = server->params[j];
/* tp[j]->isGradFinished is true only if the model finishes the computation /* tp[j]->isGradFinished is true only if the model finishes the computation
(in another process) */ (in another process) */
if (server->flags[j] != PARAM_STATE_NOT_READY || !tp[j]->isGradFinished) if (paramServer.flag != PARAM_STATE_NOT_READY || !paramServer.param->isGradFinished)
continue; continue;
/* check if all the models (or part of them) are ready */ /* check if all the models (or part of them) are ready */
for (int i = 0; i < memberActive->count; i++) { for (int i = 0; i < memberActive->count; i++) {
XModel * source = (XModel*)memberActive->GetItem(i); XModel * source = (XModel*)memberActive->GetItem(i);
TensorList & sp = source->params; XParamKeeper &paramSource = source->params[j];
/* sp[j]->isGradFinished is true only if the model finishes the computation /* sp[j]->isGradFinished is true only if the model finishes the computation
(in another process) */ (in another process) */
if (source->flags[j] == PARAM_STATE_NOT_READY && sp[j]->isGradFinished) { if (paramSource.flag == PARAM_STATE_NOT_READY && paramSource.param->isGradFinished) {
/* data transmit */ /* data transmit */
CollectP2P(sp[j]->grad, tp[j]->grad); CollectP2P(paramSource.param->grad, paramServer.param->grad);
/* reset the flag */ /* reset the flag */
source->flags[j] = PARAM_STATE_COLLECTED; paramSource.flag = PARAM_STATE_COLLECTED;
finished++; finished++;
finishedCount[j]++; finishedCount[j]++;
...@@ -121,7 +123,7 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -121,7 +123,7 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
broadcast the new parameters to member models broadcast the new parameters to member models
(in another thread) */ (in another thread) */
if (finishedCount[j] == memberActive->count) { if (finishedCount[j] == memberActive->count) {
server->flags[j] = PARAM_STATE_COLLECTED; paramServer.flag = PARAM_STATE_COLLECTED;
if(updater != NULL) if(updater != NULL)
updater->AddJobUpdateSingle(server, memberAll, j, optimizer, broadcaster); updater->AddJobUpdateSingle(server, memberAll, j, optimizer, broadcaster);
} }
...@@ -133,31 +135,32 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -133,31 +135,32 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
} }
} }
else if (collectMode == DATA_COLLECT_REDUCESUM) { else if (collectMode == DATA_COLLECT_REDUCESUM) {
for (int j = 0; j < tp.count; j++) { for (int j = 0; j < server->paramNum; j++) {
bool ready = true; bool ready = true;
XParamKeeper &paramServer = server->params[j];
/* tp[j]->isGradFinished is true only if the model finishes the computation /* tp[j]->isGradFinished is true only if the model finishes the computation
(in another process) */ (in another process) */
if (server->flags[j] != PARAM_STATE_NOT_READY || !tp[j]->isGradFinished) if (paramServer.flag != PARAM_STATE_NOT_READY || !paramServer.param->isGradFinished)
continue; continue;
/* check if all the models (or part of them) are ready */ /* check if all the models (or part of them) are ready */
for (int i = 0; i < memberActive->count; i++) { for (int i = 0; i < memberActive->count; i++) {
XModel * source = (XModel*)memberActive->GetItem(i); XModel * source = (XModel*)memberActive->GetItem(i);
TensorList & sp = source->params; XParamKeeper &paramSource = source->params[j];
/* sp[j]->isGradFinished is true only if the model finishes the computation /* sp[j]->isGradFinished is true only if the model finishes the computation
(in another process) */ (in another process) */
if (source->flags[j] == PARAM_STATE_COLLECTED || if (paramSource.flag == PARAM_STATE_COLLECTED ||
source->flags[j] == PARAM_STATE_UPDATED || paramSource.flag == PARAM_STATE_UPDATED ||
!sp[j]->isGradFinished) !paramSource.param->isGradFinished)
{ {
ready = false; ready = false;
break; break;
} }
else if (source->flags[j] == PARAM_STATE_NOT_READY) { else if (paramSource.flag == PARAM_STATE_NOT_READY) {
source->flags[j] = PARAM_STATE_READY; paramSource.flag = PARAM_STATE_READY;
} }
} }
...@@ -166,20 +169,19 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -166,20 +169,19 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
for (int i = 0; i < memberActive->count; i++) { for (int i = 0; i < memberActive->count; i++) {
XModel * source = (XModel*)memberActive->GetItem(i); XModel * source = (XModel*)memberActive->GetItem(i);
TensorList & sp = source->params; tensorList.Add(source->params[j].param->grad);
tensorList.Add(sp.GetItem(j)->grad);
} }
/* data transmit */ /* data transmit */
CollectReduceSum(&tensorList, tp.GetItem(j)->grad); CollectReduceSum(&tensorList, server->params[j].param->grad);
/* reset the flags */ /* reset the flags */
for (int i = 0; i < memberActive->count; i++) { for (int i = 0; i < memberActive->count; i++) {
XModel * source = (XModel*)memberActive->GetItem(i); XModel * source = (XModel*)memberActive->GetItem(i);
source->flags[j] = PARAM_STATE_COLLECTED; source->params[j].flag = PARAM_STATE_COLLECTED;
} }
server->flags[j] = PARAM_STATE_COLLECTED; server->params[j].flag = PARAM_STATE_COLLECTED;
finished += memberActive->count; finished += memberActive->count;
/* we call model update (in another thread) and then /* we call model update (in another thread) and then
...@@ -194,7 +196,7 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod ...@@ -194,7 +196,7 @@ void XWorkerCollect::UpdateDataAll(XList * memberActive, XList * memberAll, XMod
} }
/* the collection finishes if all data tensors are processed */ /* the collection finishes if all data tensors are processed */
if (finished == tp.count * memberActive->count) if (finished == server->paramNum * memberActive->count)
break; break;
XSleep(sleepTime); XSleep(sleepTime);
...@@ -333,17 +335,6 @@ bool XWorkerCollect::AddJobCollect(XList * sourceList, XModel * target) ...@@ -333,17 +335,6 @@ bool XWorkerCollect::AddJobCollect(XList * sourceList, XModel * target)
CheckNTErrors(sourceList != NULL, "no input source model list!"); CheckNTErrors(sourceList != NULL, "no input source model list!");
CheckNTErrors(target != NULL, "no input target model!"); CheckNTErrors(target != NULL, "no input target model!");
/*XList args;
args.Add(this);
args.AddInt(sourceList->count);
args.AddList(sourceList);
args.Add(target);
if (isInstantRun)
XWorkerCollect::Collect(&args);
else
queue.EnqueueJob((void*)(char*)XWorkerCollect::Collect, &args);*/
XList args; XList args;
args.Add(this); args.Add(this);
args.AddInt(sourceList->count); args.AddInt(sourceList->count);
......
source/train/XWorkerUpdate.cpp
...@@ -63,12 +63,10 @@ update a parameter of a model ...@@ -63,12 +63,10 @@ update a parameter of a model
void XWorkerUpdate::UpdateParameter(XModel * server, XList * members, int pid, void XWorkerUpdate::UpdateParameter(XModel * server, XList * members, int pid,
XOptimizer * optimizer, XWorkerBroadcast * broadcaster) XOptimizer * optimizer, XWorkerBroadcast * broadcaster)
{ {
TensorList & params = server->params;
PARAM_STATE * flags = server->flags;
CheckNTErrors(flags[pid] == PARAM_STATE_COLLECTED, "The state of the parameter is wrong!"); CheckNTErrors(server->params[pid].flag == PARAM_STATE_COLLECTED, "The state of the parameter is wrong!");
XTensor * param = params.GetItem(pid); XTensor * param = server->params[pid].param;
XTensor * grad = param->grad; XTensor * grad = param->grad;
CheckNTErrors(grad != NULL, "No gradient!"); CheckNTErrors(grad != NULL, "No gradient!");
...@@ -77,7 +75,7 @@ void XWorkerUpdate::UpdateParameter(XModel * server, XList * members, int pid, ...@@ -77,7 +75,7 @@ void XWorkerUpdate::UpdateParameter(XModel * server, XList * members, int pid,
optimizer->UpdateParam(param, grad, pid); optimizer->UpdateParam(param, grad, pid);
/* set the flag */ /* set the flag */
flags[pid] = PARAM_STATE_UPDATED; server->params[pid].flag = PARAM_STATE_UPDATED;
/* broadcast the new parameter to other models (in anotehr worker/thread) */ /* broadcast the new parameter to other models (in anotehr worker/thread) */
broadcaster->AddJobBroadcastSingle(server, members, pid); broadcaster->AddJobBroadcastSingle(server, members, pid);
...@@ -92,15 +90,13 @@ update the model ...@@ -92,15 +90,13 @@ update the model
void XWorkerUpdate::UpdateModel(XModel * model, XOptimizer * optimizer, long sleepTime) void XWorkerUpdate::UpdateModel(XModel * model, XOptimizer * optimizer, long sleepTime)
{ {
int finished = 0; int finished = 0;
TensorList & params = model->params;
PARAM_STATE * flags = model->flags;
optimizer->Prepare(model); optimizer->Prepare(model);
while (1) { while (1) {
for (int i = 0; i < params.count; i++) { for (int i = 0; i < model->paramNum; i++) {
if (flags[i] == PARAM_STATE_COLLECTED) { if (model->params[i].flag == PARAM_STATE_COLLECTED) {
XTensor * param = params.GetItem(i); XTensor * param = model->params[i].param;
XTensor * grad = param->grad; XTensor * grad = param->grad;
CheckNTErrors(grad != NULL, "No gradient!"); CheckNTErrors(grad != NULL, "No gradient!");
...@@ -109,12 +105,12 @@ void XWorkerUpdate::UpdateModel(XModel * model, XOptimizer * optimizer, long sle ...@@ -109,12 +105,12 @@ void XWorkerUpdate::UpdateModel(XModel * model, XOptimizer * optimizer, long sle
optimizer->UpdateParam(param, grad, i); optimizer->UpdateParam(param, grad, i);
/* set the flag */ /* set the flag */
flags[i] = PARAM_STATE_UPDATED; model->params[i].flag = PARAM_STATE_UPDATED;
finished++; finished++;
} }
} }
if (finished == params.count) if (finished == model->paramNum)
break; break;
XSleep(sleepTime); XSleep(sleepTime);
...@@ -182,7 +178,7 @@ bool XWorkerUpdate::AddJobUpdateSingle(XModel * model, XList * members, int pid, ...@@ -182,7 +178,7 @@ bool XWorkerUpdate::AddJobUpdateSingle(XModel * model, XList * members, int pid,
CheckNTErrors(members != NULL, "No member model list!"); CheckNTErrors(members != NULL, "No member model list!");
CheckNTErrors(optimizer != NULL, "No optimizer!"); CheckNTErrors(optimizer != NULL, "No optimizer!");
CheckNTErrors(broadcaster != NULL, "No broadcaster!"); CheckNTErrors(broadcaster != NULL, "No broadcaster!");
CheckNTErrors(pid >= 0 && pid < model->params.count, "Illegal parameter index!"); CheckNTErrors(pid >= 0 && pid < model->paramNum, "Illegal parameter index!");
XList args; XList args;
args.Add(this); args.Add(this);
......
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