Search in sources :

Example 26 with IntObject

use of org.apache.sysml.runtime.instructions.cp.IntObject in project systemml by apache.

the class ParForProgramBlock method createEmptyUnscopedVariables.

/**
 * Create empty matrix objects and scalars for all unscoped vars
 * (created within the parfor).
 *
 * NOTE: parfor gives no guarantees on the values of those objects - hence
 * we return -1 for sclars and empty matrix objects.
 *
 * @param out local variable map
 * @param sb statement block
 */
private static void createEmptyUnscopedVariables(LocalVariableMap out, StatementBlock sb) {
    VariableSet updated = sb.variablesUpdated();
    VariableSet livein = sb.liveIn();
    // for all vars IN <updated> AND NOT IN <livein>
    for (String var : updated.getVariableNames()) if (!livein.containsVariable(var)) {
        // create empty output
        DataIdentifier dat = updated.getVariable(var);
        DataType datatype = dat.getDataType();
        ValueType valuetype = dat.getValueType();
        Data dataObj = null;
        switch(datatype) {
            case SCALAR:
                switch(valuetype) {
                    case BOOLEAN:
                        dataObj = new BooleanObject(false);
                        break;
                    case INT:
                        dataObj = new IntObject(-1);
                        break;
                    case DOUBLE:
                        dataObj = new DoubleObject(-1d);
                        break;
                    case STRING:
                        dataObj = new StringObject("-1");
                        break;
                    default:
                        throw new DMLRuntimeException("Value type not supported: " + valuetype);
                }
                break;
            case MATRIX:
            case FRAME:
                // because metadata (e.g., outputinfo) not known at this place.
                break;
            case UNKNOWN:
                break;
            default:
                throw new DMLRuntimeException("Data type not supported: " + datatype);
        }
        if (dataObj != null)
            out.put(var, dataObj);
    }
}
Also used : VariableSet(org.apache.sysml.parser.VariableSet) DataIdentifier(org.apache.sysml.parser.DataIdentifier) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) ValueType(org.apache.sysml.parser.Expression.ValueType) DoubleObject(org.apache.sysml.runtime.instructions.cp.DoubleObject) StringObject(org.apache.sysml.runtime.instructions.cp.StringObject) DataType(org.apache.sysml.parser.Expression.DataType) Data(org.apache.sysml.runtime.instructions.cp.Data) BooleanObject(org.apache.sysml.runtime.instructions.cp.BooleanObject) DMLRuntimeException(org.apache.sysml.runtime.DMLRuntimeException)

Example 27 with IntObject

use of org.apache.sysml.runtime.instructions.cp.IntObject in project incubator-systemml by apache.

the class MLContextUtil method convertInputType.

/**
 * Convert input types to internal SystemML representations
 *
 * @param parameterName
 *            The name of the input parameter
 * @param parameterValue
 *            The value of the input parameter
 * @param metadata
 *            matrix/frame metadata
 * @return input in SystemML data representation
 */
public static Data convertInputType(String parameterName, Object parameterValue, Metadata metadata) {
    String name = parameterName;
    Object value = parameterValue;
    boolean hasMetadata = (metadata != null) ? true : false;
    boolean hasMatrixMetadata = hasMetadata && (metadata instanceof MatrixMetadata) ? true : false;
    boolean hasFrameMetadata = hasMetadata && (metadata instanceof FrameMetadata) ? true : false;
    if (name == null) {
        throw new MLContextException("Input parameter name is null");
    } else if (value == null) {
        throw new MLContextException("Input parameter value is null for: " + parameterName);
    } else if (value instanceof JavaRDD<?>) {
        @SuppressWarnings("unchecked") JavaRDD<String> javaRDD = (JavaRDD<String>) value;
        if (hasMatrixMetadata) {
            MatrixMetadata matrixMetadata = (MatrixMetadata) metadata;
            if (matrixMetadata.getMatrixFormat() == MatrixFormat.IJV) {
                return MLContextConversionUtil.javaRDDStringIJVToMatrixObject(javaRDD, matrixMetadata);
            } else {
                return MLContextConversionUtil.javaRDDStringCSVToMatrixObject(javaRDD, matrixMetadata);
            }
        } else if (hasFrameMetadata) {
            FrameMetadata frameMetadata = (FrameMetadata) metadata;
            if (frameMetadata.getFrameFormat() == FrameFormat.IJV) {
                return MLContextConversionUtil.javaRDDStringIJVToFrameObject(javaRDD, frameMetadata);
            } else {
                return MLContextConversionUtil.javaRDDStringCSVToFrameObject(javaRDD, frameMetadata);
            }
        } else if (!hasMetadata) {
            String firstLine = javaRDD.first();
            boolean isAllNumbers = isCSVLineAllNumbers(firstLine);
            if (isAllNumbers) {
                return MLContextConversionUtil.javaRDDStringCSVToMatrixObject(javaRDD);
            } else {
                return MLContextConversionUtil.javaRDDStringCSVToFrameObject(javaRDD);
            }
        }
    } else if (value instanceof RDD<?>) {
        @SuppressWarnings("unchecked") RDD<String> rdd = (RDD<String>) value;
        if (hasMatrixMetadata) {
            MatrixMetadata matrixMetadata = (MatrixMetadata) metadata;
            if (matrixMetadata.getMatrixFormat() == MatrixFormat.IJV) {
                return MLContextConversionUtil.rddStringIJVToMatrixObject(rdd, matrixMetadata);
            } else {
                return MLContextConversionUtil.rddStringCSVToMatrixObject(rdd, matrixMetadata);
            }
        } else if (hasFrameMetadata) {
            FrameMetadata frameMetadata = (FrameMetadata) metadata;
            if (frameMetadata.getFrameFormat() == FrameFormat.IJV) {
                return MLContextConversionUtil.rddStringIJVToFrameObject(rdd, frameMetadata);
            } else {
                return MLContextConversionUtil.rddStringCSVToFrameObject(rdd, frameMetadata);
            }
        } else if (!hasMetadata) {
            String firstLine = rdd.first();
            boolean isAllNumbers = isCSVLineAllNumbers(firstLine);
            if (isAllNumbers) {
                return MLContextConversionUtil.rddStringCSVToMatrixObject(rdd);
            } else {
                return MLContextConversionUtil.rddStringCSVToFrameObject(rdd);
            }
        }
    } else if (value instanceof MatrixBlock) {
        MatrixBlock matrixBlock = (MatrixBlock) value;
        return MLContextConversionUtil.matrixBlockToMatrixObject(name, matrixBlock, (MatrixMetadata) metadata);
    } else if (value instanceof FrameBlock) {
        FrameBlock frameBlock = (FrameBlock) value;
        return MLContextConversionUtil.frameBlockToFrameObject(name, frameBlock, (FrameMetadata) metadata);
    } else if (value instanceof Dataset<?>) {
        @SuppressWarnings("unchecked") Dataset<Row> dataFrame = (Dataset<Row>) value;
        dataFrame = MLUtils.convertVectorColumnsToML(dataFrame);
        if (hasMatrixMetadata) {
            return MLContextConversionUtil.dataFrameToMatrixObject(dataFrame, (MatrixMetadata) metadata);
        } else if (hasFrameMetadata) {
            return MLContextConversionUtil.dataFrameToFrameObject(dataFrame, (FrameMetadata) metadata);
        } else if (!hasMetadata) {
            boolean looksLikeMatrix = doesDataFrameLookLikeMatrix(dataFrame);
            if (looksLikeMatrix) {
                return MLContextConversionUtil.dataFrameToMatrixObject(dataFrame);
            } else {
                return MLContextConversionUtil.dataFrameToFrameObject(dataFrame);
            }
        }
    } else if (value instanceof Matrix) {
        Matrix matrix = (Matrix) value;
        if ((matrix.hasBinaryBlocks()) && (!matrix.hasMatrixObject())) {
            if (metadata == null) {
                metadata = matrix.getMatrixMetadata();
            }
            JavaPairRDD<MatrixIndexes, MatrixBlock> binaryBlocks = matrix.toBinaryBlocks();
            return MLContextConversionUtil.binaryBlocksToMatrixObject(binaryBlocks, (MatrixMetadata) metadata);
        } else {
            return matrix.toMatrixObject();
        }
    } else if (value instanceof Frame) {
        Frame frame = (Frame) value;
        if ((frame.hasBinaryBlocks()) && (!frame.hasFrameObject())) {
            if (metadata == null) {
                metadata = frame.getFrameMetadata();
            }
            JavaPairRDD<Long, FrameBlock> binaryBlocks = frame.toBinaryBlocks();
            return MLContextConversionUtil.binaryBlocksToFrameObject(binaryBlocks, (FrameMetadata) metadata);
        } else {
            return frame.toFrameObject();
        }
    } else if (value instanceof double[][]) {
        double[][] doubleMatrix = (double[][]) value;
        return MLContextConversionUtil.doubleMatrixToMatrixObject(name, doubleMatrix, (MatrixMetadata) metadata);
    } else if (value instanceof URL) {
        URL url = (URL) value;
        return MLContextConversionUtil.urlToMatrixObject(url, (MatrixMetadata) metadata);
    } else if (value instanceof Integer) {
        return new IntObject((Integer) value);
    } else if (value instanceof Double) {
        return new DoubleObject((Double) value);
    } else if (value instanceof String) {
        return new StringObject((String) value);
    } else if (value instanceof Boolean) {
        return new BooleanObject((Boolean) value);
    }
    return null;
}
Also used : MatrixBlock(org.apache.sysml.runtime.matrix.data.MatrixBlock) DoubleObject(org.apache.sysml.runtime.instructions.cp.DoubleObject) URL(java.net.URL) RDD(org.apache.spark.rdd.RDD) JavaRDD(org.apache.spark.api.java.JavaRDD) JavaPairRDD(org.apache.spark.api.java.JavaPairRDD) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) FrameBlock(org.apache.sysml.runtime.matrix.data.FrameBlock) JavaPairRDD(org.apache.spark.api.java.JavaPairRDD) StringObject(org.apache.sysml.runtime.instructions.cp.StringObject) Dataset(org.apache.spark.sql.Dataset) JavaRDD(org.apache.spark.api.java.JavaRDD) MatrixObject(org.apache.sysml.runtime.controlprogram.caching.MatrixObject) DoubleObject(org.apache.sysml.runtime.instructions.cp.DoubleObject) FrameObject(org.apache.sysml.runtime.controlprogram.caching.FrameObject) BooleanObject(org.apache.sysml.runtime.instructions.cp.BooleanObject) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) StringObject(org.apache.sysml.runtime.instructions.cp.StringObject) Row(org.apache.spark.sql.Row) BooleanObject(org.apache.sysml.runtime.instructions.cp.BooleanObject)

Example 28 with IntObject

use of org.apache.sysml.runtime.instructions.cp.IntObject in project incubator-systemml by apache.

the class Recompiler method extractDAGOutputStatistics.

public static void extractDAGOutputStatistics(Hop hop, LocalVariableMap vars, boolean overwrite) {
    if (// for all writes to symbol table
    hop instanceof DataOp && ((DataOp) hop).getDataOpType() == DataOpTypes.TRANSIENTWRITE) {
        String varName = hop.getName();
        if (// not existing so far
        !vars.keySet().contains(varName) || overwrite) {
            // extract matrix sizes for size propagation
            if (hop.getDataType() == DataType.MATRIX) {
                MatrixObject mo = new MatrixObject(ValueType.DOUBLE, null);
                MatrixCharacteristics mc = new MatrixCharacteristics(hop.getDim1(), hop.getDim2(), ConfigurationManager.getBlocksize(), ConfigurationManager.getBlocksize(), hop.getNnz());
                MetaDataFormat meta = new MetaDataFormat(mc, null, null);
                mo.setMetaData(meta);
                vars.put(varName, mo);
            } else // extract scalar constants for second constant propagation
            if (hop.getDataType() == DataType.SCALAR) {
                // extract literal assignments
                if (hop.getInput().size() == 1 && hop.getInput().get(0) instanceof LiteralOp) {
                    ScalarObject constant = HopRewriteUtils.getScalarObject((LiteralOp) hop.getInput().get(0));
                    if (constant != null)
                        vars.put(varName, constant);
                } else // extract constant variable assignments
                if (hop.getInput().size() == 1 && hop.getInput().get(0) instanceof DataOp) {
                    DataOp dop = (DataOp) hop.getInput().get(0);
                    String dopvarname = dop.getName();
                    if (dop.isRead() && vars.keySet().contains(dopvarname)) {
                        ScalarObject constant = (ScalarObject) vars.get(dopvarname);
                        // no clone because constant
                        vars.put(varName, constant);
                    }
                } else // extract ncol/nrow variable assignments
                if (hop.getInput().size() == 1 && hop.getInput().get(0) instanceof UnaryOp && (((UnaryOp) hop.getInput().get(0)).getOp() == OpOp1.NROW || ((UnaryOp) hop.getInput().get(0)).getOp() == OpOp1.NCOL)) {
                    UnaryOp uop = (UnaryOp) hop.getInput().get(0);
                    if (uop.getOp() == OpOp1.NROW && uop.getInput().get(0).getDim1() > 0)
                        vars.put(varName, new IntObject(uop.getInput().get(0).getDim1()));
                    else if (uop.getOp() == OpOp1.NCOL && uop.getInput().get(0).getDim2() > 0)
                        vars.put(varName, new IntObject(uop.getInput().get(0).getDim2()));
                } else // remove other updated scalars
                {
                    // we need to remove other updated scalars in order to ensure result
                    // correctness of recompilation w/o being too conservative
                    vars.remove(varName);
                }
            }
        } else // already existing: take largest
        {
            Data dat = vars.get(varName);
            if (dat instanceof MatrixObject) {
                MatrixObject mo = (MatrixObject) dat;
                MatrixCharacteristics mc = mo.getMatrixCharacteristics();
                if (OptimizerUtils.estimateSizeExactSparsity(mc.getRows(), mc.getCols(), (mc.getNonZeros() >= 0) ? ((double) mc.getNonZeros()) / mc.getRows() / mc.getCols() : 1.0) < OptimizerUtils.estimateSize(hop.getDim1(), hop.getDim2())) {
                    // update statistics if necessary
                    mc.setDimension(hop.getDim1(), hop.getDim2());
                    mc.setNonZeros(hop.getNnz());
                }
            } else // scalar (just overwrite)
            {
                if (hop.getInput().size() == 1 && hop.getInput().get(0) instanceof LiteralOp) {
                    ScalarObject constant = HopRewriteUtils.getScalarObject((LiteralOp) hop.getInput().get(0));
                    if (constant != null)
                        vars.put(varName, constant);
                }
            }
        }
    }
}
Also used : MetaDataFormat(org.apache.sysml.runtime.matrix.MetaDataFormat) ScalarObject(org.apache.sysml.runtime.instructions.cp.ScalarObject) MatrixObject(org.apache.sysml.runtime.controlprogram.caching.MatrixObject) UnaryOp(org.apache.sysml.hops.UnaryOp) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) CacheableData(org.apache.sysml.runtime.controlprogram.caching.CacheableData) Data(org.apache.sysml.runtime.instructions.cp.Data) LiteralOp(org.apache.sysml.hops.LiteralOp) DataOp(org.apache.sysml.hops.DataOp) MatrixCharacteristics(org.apache.sysml.runtime.matrix.MatrixCharacteristics)

Example 29 with IntObject

use of org.apache.sysml.runtime.instructions.cp.IntObject in project incubator-systemml by apache.

the class ProgramConverter method parseDataObject.

/**
 * NOTE: MRJobConfiguration cannot be used for the general case because program blocks and
 * related symbol tables can be hierarchically structured.
 *
 * @param in data object as string
 * @return array of objects
 */
public static Object[] parseDataObject(String in) {
    Object[] ret = new Object[2];
    StringTokenizer st = new StringTokenizer(in, DATA_FIELD_DELIM);
    String name = st.nextToken();
    DataType datatype = DataType.valueOf(st.nextToken());
    ValueType valuetype = ValueType.valueOf(st.nextToken());
    String valString = st.hasMoreTokens() ? st.nextToken() : "";
    Data dat = null;
    switch(datatype) {
        case SCALAR:
            {
                switch(valuetype) {
                    case INT:
                        dat = new IntObject(Long.parseLong(valString));
                        break;
                    case DOUBLE:
                        dat = new DoubleObject(Double.parseDouble(valString));
                        break;
                    case BOOLEAN:
                        dat = new BooleanObject(Boolean.parseBoolean(valString));
                        break;
                    case STRING:
                        dat = new StringObject(valString);
                        break;
                    default:
                        throw new DMLRuntimeException("Unable to parse valuetype " + valuetype);
                }
                break;
            }
        case MATRIX:
            {
                MatrixObject mo = new MatrixObject(valuetype, valString);
                long rows = Long.parseLong(st.nextToken());
                long cols = Long.parseLong(st.nextToken());
                int brows = Integer.parseInt(st.nextToken());
                int bcols = Integer.parseInt(st.nextToken());
                long nnz = Long.parseLong(st.nextToken());
                InputInfo iin = InputInfo.stringToInputInfo(st.nextToken());
                OutputInfo oin = OutputInfo.stringToOutputInfo(st.nextToken());
                PartitionFormat partFormat = PartitionFormat.valueOf(st.nextToken());
                UpdateType inplace = UpdateType.valueOf(st.nextToken());
                MatrixCharacteristics mc = new MatrixCharacteristics(rows, cols, brows, bcols, nnz);
                MetaDataFormat md = new MetaDataFormat(mc, oin, iin);
                mo.setMetaData(md);
                if (partFormat._dpf != PDataPartitionFormat.NONE)
                    mo.setPartitioned(partFormat._dpf, partFormat._N);
                mo.setUpdateType(inplace);
                dat = mo;
                break;
            }
        default:
            throw new DMLRuntimeException("Unable to parse datatype " + datatype);
    }
    ret[0] = name;
    ret[1] = dat;
    return ret;
}
Also used : MetaDataFormat(org.apache.sysml.runtime.matrix.MetaDataFormat) MatrixObject(org.apache.sysml.runtime.controlprogram.caching.MatrixObject) ValueType(org.apache.sysml.parser.Expression.ValueType) DoubleObject(org.apache.sysml.runtime.instructions.cp.DoubleObject) Data(org.apache.sysml.runtime.instructions.cp.Data) PartitionFormat(org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PartitionFormat) PDataPartitionFormat(org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitionFormat) UpdateType(org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType) DMLRuntimeException(org.apache.sysml.runtime.DMLRuntimeException) MatrixCharacteristics(org.apache.sysml.runtime.matrix.MatrixCharacteristics) OutputInfo(org.apache.sysml.runtime.matrix.data.OutputInfo) StringTokenizer(java.util.StringTokenizer) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) InputInfo(org.apache.sysml.runtime.matrix.data.InputInfo) StringObject(org.apache.sysml.runtime.instructions.cp.StringObject) DataType(org.apache.sysml.parser.Expression.DataType) MatrixObject(org.apache.sysml.runtime.controlprogram.caching.MatrixObject) ScalarObject(org.apache.sysml.runtime.instructions.cp.ScalarObject) DoubleObject(org.apache.sysml.runtime.instructions.cp.DoubleObject) BooleanObject(org.apache.sysml.runtime.instructions.cp.BooleanObject) IntObject(org.apache.sysml.runtime.instructions.cp.IntObject) StringObject(org.apache.sysml.runtime.instructions.cp.StringObject) BooleanObject(org.apache.sysml.runtime.instructions.cp.BooleanObject)

Example 30 with IntObject

use of org.apache.sysml.runtime.instructions.cp.IntObject in project incubator-systemml by apache.

the class Task method toCompactString.

public String toCompactString(int maxDigits) {
    StringBuilder sb = new StringBuilder();
    sb.append(_type);
    if (size() > 0) {
        sb.append(".");
        sb.append(_iterVar);
        sb.append(".{");
        int count = 0;
        for (IntObject dat : _iterations) {
            if (count != 0)
                sb.append(",");
            String tmp = String.valueOf(dat.getLongValue());
            for (int k = tmp.length(); k < maxDigits; k++) sb.append("0");
            sb.append(tmp);
            count++;
        }
        sb.append("}");
    }
    return sb.toString();
}
Also used : IntObject(org.apache.sysml.runtime.instructions.cp.IntObject)

Aggregations

IntObject (org.apache.sysml.runtime.instructions.cp.IntObject)47 DMLRuntimeException (org.apache.sysml.runtime.DMLRuntimeException)19 MatrixObject (org.apache.sysml.runtime.controlprogram.caching.MatrixObject)15 BooleanObject (org.apache.sysml.runtime.instructions.cp.BooleanObject)11 DoubleObject (org.apache.sysml.runtime.instructions.cp.DoubleObject)11 ScalarObject (org.apache.sysml.runtime.instructions.cp.ScalarObject)11 StringObject (org.apache.sysml.runtime.instructions.cp.StringObject)11 TaskType (org.apache.sysml.runtime.controlprogram.parfor.Task.TaskType)8 Timing (org.apache.sysml.runtime.controlprogram.parfor.stat.Timing)6 Data (org.apache.sysml.runtime.instructions.cp.Data)6 StringTokenizer (java.util.StringTokenizer)5 IOException (java.io.IOException)4 LinkedList (java.util.LinkedList)4 DataType (org.apache.sysml.parser.Expression.DataType)4 ValueType (org.apache.sysml.parser.Expression.ValueType)4 DMLScriptException (org.apache.sysml.runtime.DMLScriptException)4 ProgramBlock (org.apache.sysml.runtime.controlprogram.ProgramBlock)4 UpdateType (org.apache.sysml.runtime.controlprogram.caching.MatrixObject.UpdateType)4 MatrixCharacteristics (org.apache.sysml.runtime.matrix.MatrixCharacteristics)4 MetaDataFormat (org.apache.sysml.runtime.matrix.MetaDataFormat)4