Examples with ExecType org.apache.sysml.lops.LopProperties.ExecType used on opensource projects

Example 26 with ExecType

use of org.apache.sysml.lops.LopProperties.ExecType in project incubator-systemml by apache.

the class WeightedCrossEntropyR method getInstructions.

@Override
public String getInstructions(String input1, String input2, String input3, String input4, String output) {
    StringBuilder sb = new StringBuilder();
    final ExecType et = getExecType();
    sb.append(et);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(OPCODE);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(0).prepInputOperand(input1));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(1).prepInputOperand(input2));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(2).prepInputOperand(input3));
    sb.append(Lop.OPERAND_DELIMITOR);
    if ((et == ExecType.MR) && (getInputs().get(3).getDataType() == DataType.SCALAR)) {
        sb.append(getInputs().get(3).prepScalarInputOperand(et));
    } else {
        sb.append(getInputs().get(3).prepInputOperand(input4));
    }
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(prepOutputOperand(output));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_wcemmType);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_cacheU);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_cacheV);
    return sb.toString();
}

Example 27 with ExecType

use of org.apache.sysml.lops.LopProperties.ExecType in project incubator-systemml by apache.

the class WeightedDivMM method getInstructions.

/* CP/SPARK instruction generation */
@Override
public String getInstructions(String input1, String input2, String input3, String input4, String output) {
    StringBuilder sb = new StringBuilder();
    final ExecType et = getExecType();
    sb.append(et);
    sb.append(Lop.OPERAND_DELIMITOR);
    if (et == ExecType.CP)
        sb.append(OPCODE_CP);
    else
        sb.append(OPCODE);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(0).prepInputOperand(input1));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(1).prepInputOperand(input2));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(2).prepInputOperand(input3));
    sb.append(Lop.OPERAND_DELIMITOR);
    if ((et == ExecType.MR) && (getInputs().get(3).getDataType() == DataType.SCALAR)) {
        sb.append(getInputs().get(3).prepScalarInputOperand(et));
    } else {
        sb.append(getInputs().get(3).prepInputOperand(input4));
    }
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(prepOutputOperand(output));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_weightsType);
    //append degree of parallelism
    if (et == ExecType.CP) {
        sb.append(OPERAND_DELIMITOR);
        sb.append(_numThreads);
    }
    return sb.toString();
}

Example 28 with ExecType

use of org.apache.sysml.lops.LopProperties.ExecType in project incubator-systemml by apache.

the class WeightedDivMMR method getInstructions.

/* CP/SPARK instruction generation */
@Override
public String getInstructions(String input1, String input2, String input3, String input4, String output) {
    StringBuilder sb = new StringBuilder();
    final ExecType et = getExecType();
    sb.append(et);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(OPCODE);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(0).prepInputOperand(input1));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(1).prepInputOperand(input2));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(getInputs().get(2).prepInputOperand(input3));
    sb.append(Lop.OPERAND_DELIMITOR);
    if ((et == ExecType.MR) && (getInputs().get(3).getDataType() == DataType.SCALAR)) {
        sb.append(getInputs().get(3).prepScalarInputOperand(et));
    } else {
        sb.append(getInputs().get(3).prepInputOperand(input4));
    }
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(prepOutputOperand(output));
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_weightsType);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_cacheU);
    sb.append(Lop.OPERAND_DELIMITOR);
    sb.append(_cacheV);
    return sb.toString();
}

Example 29 with ExecType

use of org.apache.sysml.lops.LopProperties.ExecType in project incubator-systemml by apache.

the class TernaryOp method constructLopsCentralMoment.

/**
	 * Method to construct LOPs when op = CENTRAILMOMENT.
	 * 
	 * @throws HopsException if HopsException occurs
	 * @throws LopsException if LopsException occurs
	 */
private void constructLopsCentralMoment() throws HopsException, LopsException {
    if (_op != OpOp3.CENTRALMOMENT)
        throw new HopsException("Unexpected operation: " + _op + ", expecting " + OpOp3.CENTRALMOMENT);
    ExecType et = optFindExecType();
    if (et == ExecType.MR) {
        CombineBinary combine = CombineBinary.constructCombineLop(OperationTypes.PreCentralMoment, getInput().get(0).constructLops(), getInput().get(1).constructLops(), DataType.MATRIX, getValueType());
        combine.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getInput().get(0).getRowsInBlock(), getInput().get(0).getColsInBlock(), getInput().get(0).getNnz());
        CentralMoment cm = new CentralMoment(combine, getInput().get(2).constructLops(), DataType.MATRIX, getValueType(), et);
        cm.getOutputParameters().setDimensions(1, 1, 0, 0, -1);
        setLineNumbers(cm);
        UnaryCP unary1 = new UnaryCP(cm, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
        unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(unary1);
        setLops(unary1);
    } else //CP / SPARK
    {
        CentralMoment cm = new CentralMoment(getInput().get(0).constructLops(), getInput().get(1).constructLops(), getInput().get(2).constructLops(), getDataType(), getValueType(), et);
        cm.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(cm);
        setLops(cm);
    }
}

Example 30 with ExecType

use of org.apache.sysml.lops.LopProperties.ExecType in project incubator-systemml by apache.

the class TernaryOp method constructLopsCtable.

/**
	 * Method to construct LOPs when op = CTABLE.
	 * 
	 * @throws HopsException if HopsException occurs
	 * @throws LopsException if LopsException occurs
	 */
private void constructLopsCtable() throws HopsException, LopsException {
    if (_op != OpOp3.CTABLE)
        throw new HopsException("Unexpected operation: " + _op + ", expecting " + OpOp3.CTABLE);
    /*
		 * We must handle three different cases: case1 : all three
		 * inputs are vectors (e.g., F=ctable(A,B,W)) case2 : two
		 * vectors and one scalar (e.g., F=ctable(A,B)) case3 : one
		 * vector and two scalars (e.g., F=ctable(A))
		 */
    // identify the particular case
    // F=ctable(A,B,W)
    DataType dt1 = getInput().get(0).getDataType();
    DataType dt2 = getInput().get(1).getDataType();
    DataType dt3 = getInput().get(2).getDataType();
    Ternary.OperationTypes tertiaryOpOrig = Ternary.findCtableOperationByInputDataTypes(dt1, dt2, dt3);
    // Compute lops for all inputs
    Lop[] inputLops = new Lop[getInput().size()];
    for (int i = 0; i < getInput().size(); i++) {
        inputLops[i] = getInput().get(i).constructLops();
    }
    ExecType et = optFindExecType();
    //reset reblock requirement (see MR ctable / construct lops)
    setRequiresReblock(false);
    if (et == ExecType.CP || et == ExecType.SPARK) {
        //for CP we support only ctable expand left
        Ternary.OperationTypes tertiaryOp = isSequenceRewriteApplicable(true) ? Ternary.OperationTypes.CTABLE_EXPAND_SCALAR_WEIGHT : tertiaryOpOrig;
        boolean ignoreZeros = false;
        if (isMatrixIgnoreZeroRewriteApplicable()) {
            //table - rmempty - rshape
            ignoreZeros = true;
            inputLops[0] = ((ParameterizedBuiltinOp) getInput().get(0)).getTargetHop().getInput().get(0).constructLops();
            inputLops[1] = ((ParameterizedBuiltinOp) getInput().get(1)).getTargetHop().getInput().get(0).constructLops();
        }
        Ternary tertiary = new Ternary(inputLops, tertiaryOp, getDataType(), getValueType(), ignoreZeros, et);
        tertiary.getOutputParameters().setDimensions(_dim1, _dim2, getRowsInBlock(), getColsInBlock(), -1);
        tertiary.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
        //force blocked output in CP (see below), otherwise binarycell
        if (et == ExecType.SPARK) {
            tertiary.getOutputParameters().setDimensions(_dim1, _dim2, -1, -1, -1);
            setRequiresReblock(true);
        } else
            tertiary.getOutputParameters().setDimensions(_dim1, _dim2, getRowsInBlock(), getColsInBlock(), -1);
        //tertiary opt, w/o reblock in CP
        setLops(tertiary);
    } else //MR
    {
        //for MR we support both ctable expand left and right
        Ternary.OperationTypes tertiaryOp = isSequenceRewriteApplicable() ? Ternary.OperationTypes.CTABLE_EXPAND_SCALAR_WEIGHT : tertiaryOpOrig;
        Group group1 = null, group2 = null, group3 = null, group4 = null;
        group1 = new Group(inputLops[0], Group.OperationTypes.Sort, getDataType(), getValueType());
        group1.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
        group1.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
        Ternary tertiary = null;
        // create "group" lops for MATRIX inputs
        switch(tertiaryOp) {
            case CTABLE_TRANSFORM:
                // F = ctable(A,B,W)
                group2 = new Group(inputLops[1], Group.OperationTypes.Sort, getDataType(), getValueType());
                group2.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
                group2.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
                group3 = new Group(inputLops[2], Group.OperationTypes.Sort, getDataType(), getValueType());
                group3.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
                group3.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
                if (inputLops.length == 3)
                    tertiary = new Ternary(new Lop[] { group1, group2, group3 }, tertiaryOp, getDataType(), getValueType(), et);
                else
                    // output dimensions are given
                    tertiary = new Ternary(new Lop[] { group1, group2, group3, inputLops[3], inputLops[4] }, tertiaryOp, getDataType(), getValueType(), et);
                break;
            case CTABLE_TRANSFORM_SCALAR_WEIGHT:
                // F = ctable(A,B) or F = ctable(A,B,1)
                group2 = new Group(inputLops[1], Group.OperationTypes.Sort, getDataType(), getValueType());
                group2.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
                group2.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
                if (inputLops.length == 3)
                    tertiary = new Ternary(new Lop[] { group1, group2, inputLops[2] }, tertiaryOp, getDataType(), getValueType(), et);
                else
                    tertiary = new Ternary(new Lop[] { group1, group2, inputLops[2], inputLops[3], inputLops[4] }, tertiaryOp, getDataType(), getValueType(), et);
                break;
            case CTABLE_EXPAND_SCALAR_WEIGHT:
                // F=ctable(seq(1,N),A) or F = ctable(seq,A,1)
                //left 1, right 0 (index of input data)
                int left = isSequenceRewriteApplicable(true) ? 1 : 0;
                Group group = new Group(getInput().get(left).constructLops(), Group.OperationTypes.Sort, getDataType(), getValueType());
                group.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
                if (inputLops.length == 3)
                    tertiary = new Ternary(new Lop[] { //matrix
                    group, //weight
                    getInput().get(2).constructLops(), //left
                    new LiteralOp(left).constructLops() }, tertiaryOp, getDataType(), getValueType(), et);
                else
                    tertiary = new Ternary(new Lop[] { //getInput().get(1).constructLops(), //matrix
                    group, //weight
                    getInput().get(2).constructLops(), //left
                    new LiteralOp(left).constructLops(), inputLops[3], inputLops[4] }, tertiaryOp, getDataType(), getValueType(), et);
                break;
            case CTABLE_TRANSFORM_HISTOGRAM:
                // F=ctable(A,1) or F = ctable(A,1,1)
                if (inputLops.length == 3)
                    tertiary = new Ternary(new Lop[] { group1, getInput().get(1).constructLops(), getInput().get(2).constructLops() }, tertiaryOp, getDataType(), getValueType(), et);
                else
                    tertiary = new Ternary(new Lop[] { group1, getInput().get(1).constructLops(), getInput().get(2).constructLops(), inputLops[3], inputLops[4] }, tertiaryOp, getDataType(), getValueType(), et);
                break;
            case CTABLE_TRANSFORM_WEIGHTED_HISTOGRAM:
                // F=ctable(A,1,W)
                group3 = new Group(getInput().get(2).constructLops(), Group.OperationTypes.Sort, getDataType(), getValueType());
                group3.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
                group3.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
                if (inputLops.length == 3)
                    tertiary = new Ternary(new Lop[] { group1, getInput().get(1).constructLops(), group3 }, tertiaryOp, getDataType(), getValueType(), et);
                else
                    tertiary = new Ternary(new Lop[] { group1, getInput().get(1).constructLops(), group3, inputLops[3], inputLops[4] }, tertiaryOp, getDataType(), getValueType(), et);
                break;
            default:
                throw new HopsException("Invalid ternary operator type: " + _op);
        }
        // output dimensions are not known at compilation time
        tertiary.getOutputParameters().setDimensions(_dim1, _dim2, (_dimInputsPresent ? getRowsInBlock() : -1), (_dimInputsPresent ? getColsInBlock() : -1), -1);
        setLineNumbers(tertiary);
        Lop lctable = tertiary;
        if (!(_disjointInputs || tertiaryOp == Ternary.OperationTypes.CTABLE_EXPAND_SCALAR_WEIGHT)) {
            //no need for aggregation if (1) input indexed disjoint	or one side is sequence	w/ 1 increment
            group4 = new Group(tertiary, Group.OperationTypes.Sort, getDataType(), getValueType());
            group4.getOutputParameters().setDimensions(_dim1, _dim2, (_dimInputsPresent ? getRowsInBlock() : -1), (_dimInputsPresent ? getColsInBlock() : -1), -1);
            group4.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
            Aggregate agg1 = new Aggregate(group4, HopsAgg2Lops.get(AggOp.SUM), getDataType(), getValueType(), ExecType.MR);
            agg1.getOutputParameters().setDimensions(_dim1, _dim2, (_dimInputsPresent ? getRowsInBlock() : -1), (_dimInputsPresent ? getColsInBlock() : -1), -1);
            agg1.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
            // kahamSum is used for aggregation but inputs do not have
            // correction values
            agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
            lctable = agg1;
        }
        setLops(lctable);
        // to introduce reblock lop since table itself outputs in blocked format if dims known.
        if (!dimsKnown() && !_dimInputsPresent) {
            setRequiresReblock(true);
        }
    }
}