Examples with DataType org.apache.sysml.parser.Expression.DataType used on opensource projects

Example 51 with DataType

use of org.apache.sysml.parser.Expression.DataType in project systemml by apache.

the class GenerateClassesForMLContext method generateFunctionCallMethod.

/**
 * Obtain method for invoking a script function.
 *
 * @param scriptFilePath
 *            the path to a script file
 * @param fs
 *            a SystemML function statement
 * @param dmlFunctionCall
 *            a string representing the invocation of a script function
 * @return string representation of a method that performs a function call
 */
public static String generateFunctionCallMethod(String scriptFilePath, FunctionStatement fs, String dmlFunctionCall) {
    createFunctionOutputClass(scriptFilePath, fs);
    StringBuilder sb = new StringBuilder();
    sb.append("public ");
    // begin return type
    ArrayList<DataIdentifier> oparams = fs.getOutputParams();
    if (oparams.size() == 0) {
        sb.append("void");
    } else if (oparams.size() == 1) {
        // if 1 output, no need to encapsulate it, so return the output
        // directly
        DataIdentifier oparam = oparams.get(0);
        String type = getParamTypeAsString(oparam);
        sb.append(type);
    } else {
        String fullFunctionOutputClassName = getFullFunctionOutputClassName(scriptFilePath, fs);
        sb.append(fullFunctionOutputClassName);
    }
    sb.append(" ");
    // end return type
    sb.append(fs.getName());
    sb.append("(");
    ArrayList<DataIdentifier> inputParams = fs.getInputParams();
    for (int i = 0; i < inputParams.size(); i++) {
        if (i > 0) {
            sb.append(", ");
        }
        DataIdentifier inputParam = inputParams.get(i);
        /*
			 * Note: Using Object is currently preferrable to using
			 * datatype/valuetype to explicitly set the input type to
			 * Integer/Double/Boolean/String since Object allows the automatic
			 * handling of things such as automatic conversions from longs to
			 * ints.
			 */
        sb.append("Object ");
        sb.append(inputParam.getName());
    }
    sb.append(") {\n");
    sb.append("String scriptString = \"" + dmlFunctionCall + "\";\n");
    sb.append("org.apache.sysml.api.mlcontext.Script script = new org.apache.sysml.api.mlcontext.Script(scriptString);\n");
    if ((inputParams.size() > 0) || (oparams.size() > 0)) {
        sb.append("script");
    }
    for (int i = 0; i < inputParams.size(); i++) {
        DataIdentifier inputParam = inputParams.get(i);
        String name = inputParam.getName();
        sb.append(".in(\"" + name + "\", " + name + ")");
    }
    for (int i = 0; i < oparams.size(); i++) {
        DataIdentifier outputParam = oparams.get(i);
        String name = outputParam.getName();
        sb.append(".out(\"" + name + "\")");
    }
    if ((inputParams.size() > 0) || (oparams.size() > 0)) {
        sb.append(";\n");
    }
    sb.append("org.apache.sysml.api.mlcontext.MLResults results = script.execute();\n");
    if (oparams.size() == 0) {
        sb.append("return;\n");
    } else if (oparams.size() == 1) {
        DataIdentifier o = oparams.get(0);
        DataType dt = o.getDataType();
        ValueType vt = o.getValueType();
        if ((dt == DataType.SCALAR) && (vt == ValueType.INT)) {
            sb.append("long res = results.getLong(\"" + o.getName() + "\");\nreturn res;\n");
        } else if ((dt == DataType.SCALAR) && (vt == ValueType.DOUBLE)) {
            sb.append("double res = results.getDouble(\"" + o.getName() + "\");\nreturn res;\n");
        } else if ((dt == DataType.SCALAR) && (vt == ValueType.BOOLEAN)) {
            sb.append("boolean res = results.getBoolean(\"" + o.getName() + "\");\nreturn res;\n");
        } else if ((dt == DataType.SCALAR) && (vt == ValueType.STRING)) {
            sb.append("String res = results.getString(\"" + o.getName() + "\");\nreturn res;\n");
        } else if (dt == DataType.MATRIX) {
            sb.append("org.apache.sysml.api.mlcontext.Matrix res = results.getMatrix(\"" + o.getName() + "\");\nreturn res;\n");
        } else if (dt == DataType.FRAME) {
            sb.append("org.apache.sysml.api.mlcontext.Frame res = results.getFrame(\"" + o.getName() + "\");\nreturn res;\n");
        }
    } else {
        for (int i = 0; i < oparams.size(); i++) {
            DataIdentifier outputParam = oparams.get(i);
            String name = outputParam.getName().toLowerCase();
            String type = getParamTypeAsString(outputParam);
            DataType dt = outputParam.getDataType();
            ValueType vt = outputParam.getValueType();
            if ((dt == DataType.SCALAR) && (vt == ValueType.INT)) {
                sb.append(type + " " + name + " = results.getLong(\"" + outputParam.getName() + "\");\n");
            } else if ((dt == DataType.SCALAR) && (vt == ValueType.DOUBLE)) {
                sb.append(type + " " + name + " = results.getDouble(\"" + outputParam.getName() + "\");\n");
            } else if ((dt == DataType.SCALAR) && (vt == ValueType.BOOLEAN)) {
                sb.append(type + " " + name + " = results.getBoolean(\"" + outputParam.getName() + "\");\n");
            } else if ((dt == DataType.SCALAR) && (vt == ValueType.STRING)) {
                sb.append(type + " " + name + " = results.getString(\"" + outputParam.getName() + "\");\n");
            } else if (dt == DataType.MATRIX) {
                sb.append(type + " " + name + " = results.getMatrix(\"" + outputParam.getName() + "\");\n");
            } else if (dt == DataType.FRAME) {
                sb.append(type + " " + name + " = results.getFrame(\"" + outputParam.getName() + "\");\n");
            }
        }
        String ffocn = getFullFunctionOutputClassName(scriptFilePath, fs);
        sb.append(ffocn + " res = new " + ffocn + "(");
        for (int i = 0; i < oparams.size(); i++) {
            if (i > 0) {
                sb.append(", ");
            }
            DataIdentifier outputParam = oparams.get(i);
            String name = outputParam.getName().toLowerCase();
            sb.append(name);
        }
        sb.append(");\nreturn res;\n");
    }
    sb.append("}\n");
    return sb.toString();
}

Example 52 with DataType

use of org.apache.sysml.parser.Expression.DataType in project systemml by apache.

the class GenerateClassesForMLContext method getSimpleParamTypeAsString.

/**
 * Obtain a string representation of a parameter type, where a Matrix or
 * Frame is represented by its simple class name.
 *
 * @param param
 *            the function parameter
 * @return string representation of a parameter type
 */
public static String getSimpleParamTypeAsString(DataIdentifier param) {
    DataType dt = param.getDataType();
    ValueType vt = param.getValueType();
    if ((dt == DataType.SCALAR) && (vt == ValueType.INT)) {
        return "long";
    } else if ((dt == DataType.SCALAR) && (vt == ValueType.DOUBLE)) {
        return "double";
    } else if ((dt == DataType.SCALAR) && (vt == ValueType.BOOLEAN)) {
        return "boolean";
    } else if ((dt == DataType.SCALAR) && (vt == ValueType.STRING)) {
        return "String";
    } else if (dt == DataType.MATRIX) {
        return "Matrix";
    } else if (dt == DataType.FRAME) {
        return "Frame";
    }
    return null;
}

Example 53 with DataType

use of org.apache.sysml.parser.Expression.DataType in project systemml by apache.

the class ParForStatementBlock method rCheckCandidates.

/**
 * This method recursively checks a candidate against StatementBlocks for anti, data and output dependencies.
 * A LanguageException is raised if at least one dependency is found, where it is guaranteed that no false negatives
 * (undetected dependency) but potentially false positives (misdetected dependency) can appear.
 *
 * @param c candidate
 * @param cdt candidate data type
 * @param asb list of statement blocks
 * @param sCount statement count
 * @param dep array of boolean potential output dependencies
 */
private void rCheckCandidates(Candidate c, DataType cdt, ArrayList<StatementBlock> asb, Integer sCount, boolean[] dep) {
    // check candidate only (output dependency if scalar or constant matrix subscript)
    if (cdt == DataType.SCALAR || // dat2 checked for other candidate
    cdt == DataType.OBJECT) {
        // every write to a scalar or complete data object is an output dependency
        dep[0] = true;
        if (ABORT_ON_FIRST_DEPENDENCY)
            return;
    } else if (cdt == DataType.MATRIX) {
        if (runConstantCheck(c._dat) && !c._isAccum) {
            if (LOG.isTraceEnabled())
                LOG.trace("PARFOR: Possible output dependency detected via constant self-check: var '" + c._var + "'.");
            dep[0] = true;
            if (ABORT_ON_FIRST_DEPENDENCY)
                return;
        }
    }
    // check candidate against all statements
    for (StatementBlock sb : asb) for (Statement s : sb._statements) {
        sCount++;
        if (s instanceof ForStatement) {
            // incl parfor
            // despite separate dependency analysis for each nested parfor, we need to
            // recursively check nested parfor as well in order to ensure correcteness
            // of constantChecks with regard to outer indexes
            rCheckCandidates(c, cdt, ((ForStatement) s).getBody(), sCount, dep);
        } else if (s instanceof WhileStatement) {
            rCheckCandidates(c, cdt, ((WhileStatement) s).getBody(), sCount, dep);
        } else if (s instanceof IfStatement) {
            rCheckCandidates(c, cdt, ((IfStatement) s).getIfBody(), sCount, dep);
            rCheckCandidates(c, cdt, ((IfStatement) s).getElseBody(), sCount, dep);
        } else if (s instanceof FunctionStatement) {
            rCheckCandidates(c, cdt, ((FunctionStatement) s).getBody(), sCount, dep);
        } else {
            // CHECK output dependencies
            List<DataIdentifier> datsUpdated = getDataIdentifiers(s, true);
            if (datsUpdated != null) {
                for (DataIdentifier write : datsUpdated) {
                    if (!c._var.equals(write.getName()))
                        continue;
                    if (cdt != DataType.MATRIX) {
                        // cannot infer type, need to exit (conservative approach)
                        throw new LanguageException("PARFOR loop dependency analysis: " + "cannot check for dependencies due to unknown datatype of var '" + c._var + "'.");
                    }
                    DataIdentifier dat2 = write;
                    // skip self-check
                    if (c._dat == dat2)
                        continue;
                    if (runEqualsCheck(c._dat, dat2)) {
                    // intra-iteration output dependencies (same index function) are OK
                    } else if (runBanerjeeGCDTest(c._dat, dat2)) {
                        LOG.trace("PARFOR: Possible output dependency detected via GCD/Banerjee: var '" + write + "'.");
                        dep[0] = true;
                        if (ABORT_ON_FIRST_DEPENDENCY)
                            return;
                    }
                }
            }
            List<DataIdentifier> datsRead = getDataIdentifiers(s, false);
            if (datsRead == null)
                continue;
            // check data and anti dependencies
            for (DataIdentifier read : datsRead) {
                if (!c._var.equals(read.getName()))
                    continue;
                DataIdentifier dat2 = read;
                DataType dat2dt = _vsParent.getVariables().get(read.getName()).getDataType();
                if (cdt == DataType.SCALAR || cdt == DataType.OBJECT || dat2dt == DataType.SCALAR || dat2dt == DataType.OBJECT) {
                    // every write, read combination involving a scalar is a data dependency
                    dep[1] = true;
                    if (ABORT_ON_FIRST_DEPENDENCY)
                        return;
                } else if (cdt == DataType.MATRIX && dat2dt == DataType.MATRIX) {
                    boolean invalid = false;
                    if (runEqualsCheck(c._dat, dat2))
                        // read/write on same index, and not constant (checked for output) is OK
                        invalid = runConstantCheck(dat2);
                    else if (runBanerjeeGCDTest(c._dat, dat2))
                        invalid = true;
                    else if (!(dat2 instanceof IndexedIdentifier))
                        // non-indexed access to candidate result variable -> always a dependency
                        invalid = true;
                    if (invalid) {
                        LOG.trace("PARFOR: Possible data/anti dependency detected via GCD/Banerjee: var '" + read + "'.");
                        dep[1] = true;
                        dep[2] = true;
                        if (ABORT_ON_FIRST_DEPENDENCY)
                            return;
                    }
                } else {
                    // cannot infer type, need to exit (conservative approach)
                    throw new LanguageException("PARFOR loop dependency analysis: " + "cannot check for dependencies due to unknown datatype of var '" + c._var + "'.");
                }
            }
        }
    }
}

Example 54 with DataType

use of org.apache.sysml.parser.Expression.DataType in project systemml by apache.

the class ScalarInstruction method isFirstArgumentScalar.

private static boolean isFirstArgumentScalar(String inst) {
    // get first argument
    String[] parts = InstructionUtils.getInstructionPartsWithValueType(inst);
    String arg1 = parts[1];
    // get data type of first argument
    String[] subparts = arg1.split(Lop.VALUETYPE_PREFIX);
    DataType dt = DataType.valueOf(subparts[1]);
    return (dt == DataType.SCALAR);
}

Example 55 with DataType

use of org.apache.sysml.parser.Expression.DataType in project systemml by apache.

the class BinarySPInstruction method parseInstruction.

public static BinarySPInstruction parseInstruction(String str) {
    CPOperand in1 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
    CPOperand in2 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
    CPOperand out = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
    String opcode = null;
    boolean isBroadcast = false;
    VectorType vtype = null;
    if (str.startsWith("SPARK" + Lop.OPERAND_DELIMITOR + "map")) {
        String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
        InstructionUtils.checkNumFields(parts, 5);
        opcode = parts[0];
        in1.split(parts[1]);
        in2.split(parts[2]);
        out.split(parts[3]);
        vtype = VectorType.valueOf(parts[5]);
        isBroadcast = true;
    } else {
        opcode = parseBinaryInstruction(str, in1, in2, out);
    }
    DataType dt1 = in1.getDataType();
    DataType dt2 = in2.getDataType();
    Operator operator = InstructionUtils.parseExtendedBinaryOrBuiltinOperator(opcode, in1, in2);
    if (dt1 == DataType.MATRIX || dt2 == DataType.MATRIX) {
        if (dt1 == DataType.MATRIX && dt2 == DataType.MATRIX) {
            if (isBroadcast)
                return new BinaryMatrixBVectorSPInstruction(operator, in1, in2, out, vtype, opcode, str);
            else
                return new BinaryMatrixMatrixSPInstruction(operator, in1, in2, out, opcode, str);
        } else
            return new BinaryMatrixScalarSPInstruction(operator, in1, in2, out, opcode, str);
    }
    return null;
}