int TSch::AddTask(
const TStrV& DimObjNmV, const TSecTm& StartTm, const TSecTm& EndTm){
IAssert(DimObjNmV.Len()==GetDims());
int TaskId=GetNewTaskId();
PSchTask Task=PSchTask(new TSchTask(TaskId, DimObjNmV, StartTm, EndTm));
IdToTaskH.AddDat(TaskId, Task);
for (int DimN=0; DimN<GetDims(); DimN++){
DimV[DimN]->AddTask(Task);}
return TaskId;
}
bool TSch::IsTaskOk(const PSchTask& Task, TSchTaskV& DimIcTaskV) const {
DimIcTaskV.Gen(GetDims(), GetDims());
bool Ok=true;
for (int DimN=0; DimN<GetDims(); DimN++){
PSchTask IcTask;
if (!DimV[DimN]->IsTaskOk(Task, IcTask)){
DimIcTaskV[DimN]=IcTask; Ok=false;
}
}
return Ok;
}
void DenseMat<CPU, Dtype>::SparseMM(SparseMat<CPU, Dtype>& A, DenseMat<CPU, Dtype>& B, Trans transa, Trans transb, Dtype alpha, Dtype beta)
{
assert(transb == Trans::N);
size_t m, n, k;
GetDims(A.rows, A.cols, transa, B.rows, B.cols, transb, m, n, k);
Resize(m, n);
MKLHelper_CSRMM(CPU_CharT(transa), A.rows, this->cols, A.cols, alpha,
(char*)"GLNC", A.data->val, A.data->col_idx, A.data->ptr, A.data->ptr + 1,
B.data, B.cols,
beta, data, this->cols);
}
void DenseMat<CPU, Dtype>::GeMM(DenseMat<CPU, Dtype>& A, DenseMat<CPU, Dtype>& B, Trans transa, Trans transb, Dtype alpha, Dtype beta)
{
size_t m, n, k;
GetDims(A.rows, A.cols, transa, B.rows, B.cols, transb, m, n, k);
Resize(m, n);
MKLHelper_GeMM(CblasRowMajor, CPU_T(transa), CPU_T(transb),
m, n, k, alpha,
A.data, A.cols,
B.data, B.cols,
beta, data, this->cols);
}
// get tensor shape of the slice referenced by a given FrameRange
// Important: This shape does carry offset and stride; it's not just dimensions.
TensorShape ComputationNodeBase::GetTensorSliceFor(size_t rank, const FrameRange& fr) const
{
// form the actual tensor that describes the full object
// Note: This may have strides.
auto tensorShape = GetTensorShape(rank);
// determine the slice dimensions described by the FrameRange
// Note: These are dimensions without strides.
let slice = TensorSliceWithMBLayoutFor(tensorShape.GetDims(), fr, GetMBLayout());
// narrow the tensor
// Note: Strides are honored correctly.
tensorShape.NarrowTo(slice);
return tensorShape;
}
void TSch::DelTask(const int& TaskId){
PSchTask Task=IdToTaskH.GetDat(TaskId);
for (int DimN=0; DimN<GetDims(); DimN++){
DimV[DimN]->DelTask(Task);}
}
int TSch::GetDimN(const TStr& DimNm) const {
for (int DimN=0; DimN<GetDims(); DimN++){
if (GetDimNm(DimN)==DimNm){return DimN;}}
return -1;
}
TStrV TSch::GetDimNmV() const {
TStrV DimNmV(GetDims(), 0);
for (int DimN=0; DimN<GetDims(); DimN++){
DimNmV.Add(GetDimNm(DimN));}
return DimNmV;
}
