@Override
public void refreshSizeInformation() {
if (getDataType() == DataType.SCALAR) {
// do nothing always known
} else if (_op == OpOp1.CAST_AS_MATRIX && getInput().get(0).getDataType() == DataType.SCALAR) {
// prevent propagating 0 from scalar (which would be interpreted as unknown)
setDim1(1);
setDim2(1);
} else // general case
{
// If output is a Matrix then this operation is of type (B = op(A))
// Dimensions of B are same as that of A, and sparsity may/maynot change
Hop input = getInput().get(0);
setDim1(input.getDim1());
setDim2(input.getDim2());
if (_op == OpOp1.ABS
|| _op == OpOp1.COS
|| _op == OpOp1.SIN
|| _op == OpOp1.TAN
|| _op == OpOp1.ACOS
|| _op == OpOp1.ASIN
|| _op == OpOp1.ATAN
|| _op == OpOp1.SQRT
|| _op == OpOp1.ROUND
|| _op == OpOp1.SPROP) // sparsity preserving
{
setNnz(input.getNnz());
}
}
}
private Lop constructLopsIQM() throws HopsException, LopsException {
ExecType et = optFindExecType();
Hop input = getInput().get(0);
if (et == ExecType.MR) {
CombineUnary combine =
CombineUnary.constructCombineLop(input.constructLops(), DataType.MATRIX, getValueType());
combine
.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
SortKeys sort =
SortKeys.constructSortByValueLop(
combine,
SortKeys.OperationTypes.WithoutWeights,
DataType.MATRIX,
ValueType.DOUBLE,
ExecType.MR);
// Sort dimensions are same as the first input
sort.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
Data lit = Data.createLiteralLop(ValueType.DOUBLE, Double.toString(0.25));
lit.setAllPositions(
this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
PickByCount pick =
new PickByCount(
sort, lit, DataType.MATRIX, getValueType(), PickByCount.OperationTypes.RANGEPICK);
pick.getOutputParameters().setDimensions(-1, -1, getRowsInBlock(), getColsInBlock(), -1);
setLineNumbers(pick);
PartialAggregate pagg =
new PartialAggregate(
pick,
HopsAgg2Lops.get(Hop.AggOp.SUM),
HopsDirection2Lops.get(Hop.Direction.RowCol),
DataType.MATRIX,
getValueType());
setLineNumbers(pagg);
// Set the dimensions of PartialAggregate LOP based on the
// direction in which aggregation is performed
pagg.setDimensionsBasedOnDirection(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock());
Group group1 = new Group(pagg, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
group1
.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
setLineNumbers(group1);
Aggregate agg1 =
new Aggregate(
group1,
HopsAgg2Lops.get(Hop.AggOp.SUM),
DataType.MATRIX,
getValueType(),
ExecType.MR);
agg1.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
agg1.setupCorrectionLocation(pagg.getCorrectionLocation());
setLineNumbers(agg1);
UnaryCP unary1 =
new UnaryCP(
agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
Unary iqm =
new Unary(
sort,
unary1,
Unary.OperationTypes.MR_IQM,
DataType.SCALAR,
ValueType.DOUBLE,
ExecType.CP);
iqm.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(iqm);
return iqm;
} else {
SortKeys sort =
SortKeys.constructSortByValueLop(
input.constructLops(),
SortKeys.OperationTypes.WithoutWeights,
DataType.MATRIX,
ValueType.DOUBLE,
et);
sort.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
PickByCount pick =
new PickByCount(
sort, null, getDataType(), getValueType(), PickByCount.OperationTypes.IQM, et, true);
pick.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
setLineNumbers(pick);
return pick;
}
}
