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Example 56 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class RowSplitCombineUtils method combineIntDoubleIndexRowSplits.

// //////////////////////////////////////////////////////////////////////////////
// Combine Int key Double value vector
// //////////////////////////////////////////////////////////////////////////////
public static Vector combineIntDoubleIndexRowSplits(int matrixId, int rowId, int resultSize, KeyPart[] keyParts, ValuePart[] valueParts, MatrixMeta matrixMeta) {
    IntDoubleVector vector = VFactory.sparseDoubleVector((int) matrixMeta.getColNum(), resultSize);
    for (int i = 0; i < keyParts.length; i++) {
        mergeTo(vector, keyParts[i], (DoubleValuesPart) valueParts[i]);
    }
    vector.setRowId(rowId);
    vector.setMatrixId(matrixId);
    return vector;
}
Also used : IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)

Example 57 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class RowSplitCombineUtils method combineServerIntDoubleRowSplits.

private static Vector combineServerIntDoubleRowSplits(List<ServerRow> rowSplits, MatrixMeta matrixMeta, int rowIndex) {
    int colNum = (int) matrixMeta.getColNum();
    int elemNum = 0;
    int size = rowSplits.size();
    for (int i = 0; i < size; i++) {
        elemNum += rowSplits.get(i).size();
    }
    IntDoubleVector row;
    if (elemNum >= (int) (storageConvFactor * colNum)) {
        row = VFactory.denseDoubleVector(colNum);
    } else {
        row = VFactory.sparseDoubleVector(colNum, elemNum);
    }
    row.setMatrixId(matrixMeta.getId());
    row.setRowId(rowIndex);
    Collections.sort(rowSplits, serverRowComp);
    int clock = Integer.MAX_VALUE;
    for (int i = 0; i < size; i++) {
        if (rowSplits.get(i) == null) {
            continue;
        }
        if (rowSplits.get(i).getClock() < clock) {
            clock = rowSplits.get(i).getClock();
        }
        ((ServerIntDoubleRow) rowSplits.get(i)).mergeTo(row);
    }
    row.setClock(clock);
    return row;
}
Also used : ServerIntDoubleRow(com.tencent.angel.ps.storage.vector.ServerIntDoubleRow) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)

Example 58 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class CompIntDoubleVectorSplitter method split.

@Override
public Map<PartitionKey, RowUpdateSplit> split(Vector vector, List<PartitionKey> parts) {
    IntDoubleVector[] vecParts = ((CompIntDoubleVector) vector).getPartitions();
    assert vecParts.length == parts.size();
    Map<PartitionKey, RowUpdateSplit> updateSplitMap = new HashMap<>(parts.size());
    for (int i = 0; i < vecParts.length; i++) {
        updateSplitMap.put(parts.get(i), new CompIntDoubleRowUpdateSplit(vector.getRowId(), vecParts[i], (int) (parts.get(i).getEndCol() - parts.get(i).getStartCol())));
    }
    return updateSplitMap;
}
Also used : HashMap(java.util.HashMap) PartitionKey(com.tencent.angel.PartitionKey) CompIntDoubleRowUpdateSplit(com.tencent.angel.psagent.matrix.oplog.cache.CompIntDoubleRowUpdateSplit) RowUpdateSplit(com.tencent.angel.psagent.matrix.oplog.cache.RowUpdateSplit) CompIntDoubleVector(com.tencent.angel.ml.math2.vector.CompIntDoubleVector) CompIntDoubleRowUpdateSplit(com.tencent.angel.psagent.matrix.oplog.cache.CompIntDoubleRowUpdateSplit) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector) CompIntDoubleVector(com.tencent.angel.ml.math2.vector.CompIntDoubleVector)

Example 59 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class UpdatePSFTest method testDenseDoubleUDF.

public void testDenseDoubleUDF() throws Exception {
    Worker worker = LocalClusterContext.get().getWorker(workerAttempt0Id).getWorker();
    MatrixClient client1 = worker.getPSAgent().getMatrixClient(DENSE_DOUBLE_MAT, 0);
    int matrixW1Id = client1.getMatrixId();
    int[] index = genIndexs(feaNum, nnz);
    IntDoubleVector deltaVec = new IntDoubleVector(feaNum, new IntDoubleDenseVectorStorage(feaNum));
    for (int i = 0; i < feaNum; i++) {
        deltaVec.set(i, i);
    }
    deltaVec.setRowId(0);
    Vector[] updates = new Vector[1];
    updates[0] = deltaVec;
    client1.asyncUpdate(new IncrementRows(new IncrementRowsParam(matrixW1Id, updates))).get();
    IntDoubleVector row = (IntDoubleVector) client1.getRow(0);
    for (int id : index) {
        Assert.assertEquals(row.get(id), deltaVec.get(id), 0);
    }
    Assert.assertEquals(feaNum, row.size());
}
Also used : IncrementRowsParam(com.tencent.angel.ml.matrix.psf.update.update.IncrementRowsParam) IntDoubleDenseVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleDenseVectorStorage) IncrementRows(com.tencent.angel.ml.matrix.psf.update.update.IncrementRows) Worker(com.tencent.angel.worker.Worker) MatrixClient(com.tencent.angel.psagent.matrix.MatrixClient) IntLongVector(com.tencent.angel.ml.math2.vector.IntLongVector) LongIntVector(com.tencent.angel.ml.math2.vector.LongIntVector) Vector(com.tencent.angel.ml.math2.vector.Vector) LongFloatVector(com.tencent.angel.ml.math2.vector.LongFloatVector) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector) IntFloatVector(com.tencent.angel.ml.math2.vector.IntFloatVector) LongDoubleVector(com.tencent.angel.ml.math2.vector.LongDoubleVector) LongLongVector(com.tencent.angel.ml.math2.vector.LongLongVector) IntIntVector(com.tencent.angel.ml.math2.vector.IntIntVector) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)

Example 60 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MatrixMetaManagerTest method testCreateMatrix.

@Test
public void testCreateMatrix() throws Exception {
    try {
        LOG.info("===========================testCreateMatrix===============================");
        Worker worker = LocalClusterContext.get().getWorker(worker0Attempt0Id).getWorker();
        MasterClient masterClient = worker.getPSAgent().getMasterClient();
        int w3Id = -1;
        int w4Id = -1;
        // add matrix
        MatrixContext mMatrix = new MatrixContext();
        mMatrix.setName("w3");
        mMatrix.setRowNum(1);
        mMatrix.setColNum(100000);
        mMatrix.setMaxRowNumInBlock(1);
        mMatrix.setMaxColNumInBlock(50000);
        mMatrix.setRowType(RowType.T_DOUBLE_DENSE);
        mMatrix.set(MatrixConf.MATRIX_OPLOG_ENABLEFILTER, "false");
        mMatrix.set(MatrixConf.MATRIX_HOGWILD, "true");
        mMatrix.set(MatrixConf.MATRIX_AVERAGE, "false");
        mMatrix.set(MatrixConf.MATRIX_OPLOG_TYPE, RowType.T_DOUBLE_DENSE.name());
        masterClient.createMatrix(mMatrix, 10000);
        mMatrix.setName("w4");
        mMatrix.setRowNum(1);
        mMatrix.setColNum(100000);
        mMatrix.setMaxRowNumInBlock(1);
        mMatrix.setMaxColNumInBlock(50000);
        mMatrix.setRowType(RowType.T_DOUBLE_DENSE);
        mMatrix.set(MatrixConf.MATRIX_OPLOG_ENABLEFILTER, "false");
        mMatrix.set(MatrixConf.MATRIX_HOGWILD, "true");
        mMatrix.set(MatrixConf.MATRIX_AVERAGE, "false");
        mMatrix.set(MatrixConf.MATRIX_OPLOG_TYPE, RowType.T_DOUBLE_DENSE.name());
        masterClient.createMatrix(mMatrix, 10000);
        MatrixMeta w3Meta = worker.getPSAgent().getMatrixMetaManager().getMatrixMeta("w3");
        MatrixMeta w4Meta = worker.getPSAgent().getMatrixMetaManager().getMatrixMeta("w4");
        assertEquals(w3Meta.getRowNum(), 1);
        assertEquals(w3Meta.getColNum(), 100000);
        assertEquals(w3Meta.getRowType(), RowType.T_DOUBLE_DENSE);
        assertEquals(w4Meta.getRowNum(), 1);
        assertEquals(w4Meta.getColNum(), 100000);
        assertEquals(w4Meta.getRowType(), RowType.T_DOUBLE_DENSE);
        w3Id = w3Meta.getId();
        w4Id = w4Meta.getId();
        AngelApplicationMaster angelAppMaster = LocalClusterContext.get().getMaster().getAppMaster();
        assertTrue(angelAppMaster != null);
        AMMatrixMetaManager matrixMetaManager = angelAppMaster.getAppContext().getMatrixMetaManager();
        MatrixMeta matrixw3Proto = matrixMetaManager.getMatrix("w3");
        MatrixMeta matrixw4Proto = matrixMetaManager.getMatrix("w4");
        assertNotNull(matrixw3Proto);
        assertNotNull(matrixw4Proto);
        assertEquals(matrixw3Proto.getRowNum(), 1);
        assertEquals(matrixw3Proto.getColNum(), 100000);
        assertEquals(matrixw3Proto.getPartitionMetas().size(), 2);
        Map<Integer, PartitionMeta> w3Parts = matrixw3Proto.getPartitionMetas();
        assertEquals(w3Parts.get(0).getPss().get(0), psId);
        assertEquals(w3Parts.get(0).getPartId(), 0);
        assertEquals(w3Parts.get(0).getStartRow(), 0);
        assertEquals(w3Parts.get(0).getEndRow(), 1);
        assertEquals(w3Parts.get(0).getStartCol(), 0);
        assertEquals(w3Parts.get(0).getEndCol(), 50000);
        assertEquals(w3Parts.get(1).getPartId(), 1);
        assertEquals(w3Parts.get(1).getStartRow(), 0);
        assertEquals(w3Parts.get(1).getEndRow(), 1);
        assertEquals(w3Parts.get(1).getStartCol(), 50000);
        assertEquals(w3Parts.get(1).getEndCol(), 100000);
        Map<Integer, PartitionMeta> w4Parts = matrixw4Proto.getPartitionMetas();
        assertEquals(w4Parts.get(0).getPss().get(0), psId);
        assertEquals(w4Parts.get(0).getPartId(), 0);
        assertEquals(w4Parts.get(0).getStartRow(), 0);
        assertEquals(w4Parts.get(0).getEndRow(), 1);
        assertEquals(w4Parts.get(0).getStartCol(), 0);
        assertEquals(w4Parts.get(0).getEndCol(), 50000);
        assertEquals(w4Parts.get(1).getPartId(), 1);
        assertEquals(w4Parts.get(1).getStartRow(), 0);
        assertEquals(w4Parts.get(1).getEndRow(), 1);
        assertEquals(w4Parts.get(1).getStartCol(), 50000);
        assertEquals(w4Parts.get(1).getEndCol(), 100000);
        ParameterServer ps = LocalClusterContext.get().getPS(psAttempt0Id).getPS();
        PSMatrixMetaManager matrixPartManager = ps.getMatrixMetaManager();
        PartitionMeta w3Part0 = matrixPartManager.getPartMeta(w3Id, 0);
        PartitionMeta w3Part1 = matrixPartManager.getPartMeta(w3Id, 1);
        assertTrue(w3Part0 != null);
        assertTrue(w3Part1 != null);
        assertEquals(w3Part0.getPartitionKey().getStartRow(), 0);
        assertEquals(w3Part0.getPartitionKey().getEndRow(), 1);
        assertEquals(w3Part0.getPartitionKey().getStartCol(), 0);
        assertEquals(w3Part0.getPartitionKey().getEndCol(), 50000);
        assertEquals(w3Part1.getPartitionKey().getStartRow(), 0);
        assertEquals(w3Part1.getPartitionKey().getEndRow(), 1);
        assertEquals(w3Part1.getPartitionKey().getStartCol(), 50000);
        assertEquals(w3Part1.getPartitionKey().getEndCol(), 100000);
        PartitionMeta w4Part0 = matrixPartManager.getPartMeta(w4Id, 0);
        PartitionMeta w4Part1 = matrixPartManager.getPartMeta(w4Id, 1);
        assertTrue(w4Part0 != null);
        assertTrue(w4Part1 != null);
        assertEquals(w4Part0.getPartitionKey().getStartRow(), 0);
        assertEquals(w4Part0.getPartitionKey().getEndRow(), 1);
        assertEquals(w4Part0.getPartitionKey().getStartCol(), 0);
        assertEquals(w4Part0.getPartitionKey().getEndCol(), 50000);
        assertEquals(w4Part1.getPartitionKey().getStartRow(), 0);
        assertEquals(w4Part1.getPartitionKey().getEndRow(), 1);
        assertEquals(w4Part1.getPartitionKey().getStartCol(), 50000);
        assertEquals(w4Part1.getPartitionKey().getEndCol(), 100000);
        MatrixClient w4ClientForTask0 = worker.getPSAgent().getMatrixClient("w4", 0);
        MatrixClient w4ClientForTask1 = worker.getPSAgent().getMatrixClient("w4", 1);
        TaskContext task0Context = w4ClientForTask0.getTaskContext();
        TaskContext task1Context = w4ClientForTask1.getTaskContext();
        double[] delta = new double[100000];
        for (int i = 0; i < delta.length; i++) {
            delta[i] = 1.0;
        }
        int iterIndex = 0;
        while (iterIndex < 5) {
            IntDoubleVector row1 = (IntDoubleVector) w4ClientForTask0.getRow(0);
            double sum1 = sum(row1.getStorage().getValues());
            LOG.info("taskid=" + task0Context.getIndex() + ", matrixId=" + w4ClientForTask0.getMatrixId() + ", rowIndex=0, local row sum=" + sum1);
            IntDoubleVector deltaRow1 = new IntDoubleVector(delta.length, new IntDoubleDenseVectorStorage(delta));
            deltaRow1.setMatrixId(w4ClientForTask0.getMatrixId());
            deltaRow1.setRowId(0);
            w4ClientForTask0.increment(deltaRow1);
            w4ClientForTask0.clock().get();
            task0Context.increaseEpoch();
            IntDoubleVector row2 = (IntDoubleVector) w4ClientForTask1.getRow(0);
            double sum2 = sum(row2.getStorage().getValues());
            LOG.info("taskid=" + task1Context.getIndex() + ", matrixId=" + w4ClientForTask1.getMatrixId() + ", rowIndex=1, local row sum=" + sum2);
            IntDoubleVector deltaRow2 = new IntDoubleVector(delta.length, new IntDoubleDenseVectorStorage(delta));
            deltaRow2.setMatrixId(w4ClientForTask1.getMatrixId());
            deltaRow2.setRowId(0);
            w4ClientForTask1.increment(deltaRow2);
            w4ClientForTask1.clock().get();
            task1Context.increaseEpoch();
            iterIndex++;
        }
        AMTaskManager amTaskManager = angelAppMaster.getAppContext().getTaskManager();
        AMTask amTask0 = amTaskManager.getTask(task0Id);
        AMTask amTask1 = amTaskManager.getTask(task1Id);
        assertEquals(amTask0.getIteration(), 5);
        assertEquals(amTask1.getIteration(), 5);
        Int2IntOpenHashMap task0MatrixClocks = amTask0.getMatrixClocks();
        assertEquals(task0MatrixClocks.size(), 1);
        assertEquals(task0MatrixClocks.get(w4Id), 5);
        Int2IntOpenHashMap task1MatrixClocks = amTask1.getMatrixClocks();
        assertEquals(task1MatrixClocks.size(), 1);
        assertEquals(task1MatrixClocks.get(w4Id), 5);
        IntDoubleVector row1 = (IntDoubleVector) w4ClientForTask0.getRow(0);
        double sum1 = sum(row1.getStorage().getValues());
        assertEquals(sum1, 1000000.0, 0.000001);
        IntDoubleVector row2 = (IntDoubleVector) w4ClientForTask1.getRow(0);
        double sum2 = sum(row2.getStorage().getValues());
        assertEquals(sum2, 1000000.0, 0.000001);
        masterClient.releaseMatrix(w3Meta.getName());
        Thread.sleep(10000);
        matrixw3Proto = matrixMetaManager.getMatrix("w3");
        assertTrue(matrixw3Proto == null);
        MatrixStorageManager matrixStorageManager = LocalClusterContext.get().getPS(psAttempt0Id).getPS().getMatrixStorageManager();
        ServerMatrix sw3 = matrixStorageManager.getMatrix(w3Id);
        assertTrue(sw3 == null);
        w4ClientForTask0.clock().get();
        w4ClientForTask1.clock().get();
        row1 = (IntDoubleVector) w4ClientForTask0.getRow(0);
        sum1 = sum(row1.getStorage().getValues());
        assertEquals(sum1, 1000000.0, 0.000001);
        row2 = (IntDoubleVector) w4ClientForTask1.getRow(0);
        sum2 = sum(row2.getStorage().getValues());
        assertEquals(sum2, 1000000.0, 0.000001);
    } catch (Exception x) {
        LOG.error("run testCreateMatrix failed ", x);
        throw x;
    }
}
Also used : TaskContext(com.tencent.angel.psagent.task.TaskContext) MasterClient(com.tencent.angel.psagent.client.MasterClient) ServerMatrix(com.tencent.angel.ps.storage.matrix.ServerMatrix) Int2IntOpenHashMap(it.unimi.dsi.fastutil.ints.Int2IntOpenHashMap) AngelException(com.tencent.angel.exception.AngelException) ParameterServer(com.tencent.angel.ps.ParameterServer) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector) PSMatrixMetaManager(com.tencent.angel.ps.meta.PSMatrixMetaManager) IntDoubleDenseVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleDenseVectorStorage) AMTaskManager(com.tencent.angel.master.task.AMTaskManager) AMMatrixMetaManager(com.tencent.angel.master.matrixmeta.AMMatrixMetaManager) MatrixStorageManager(com.tencent.angel.ps.storage.MatrixStorageManager) Worker(com.tencent.angel.worker.Worker) MatrixClient(com.tencent.angel.psagent.matrix.MatrixClient) AMTask(com.tencent.angel.master.task.AMTask) Test(org.junit.Test)

Aggregations

IntDoubleVector (com.tencent.angel.ml.math2.vector.IntDoubleVector)95 ObjectIterator (it.unimi.dsi.fastutil.objects.ObjectIterator)55 IntDoubleVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)51 Int2DoubleMap (it.unimi.dsi.fastutil.ints.Int2DoubleMap)51 CompIntDoubleVector (com.tencent.angel.ml.math2.vector.CompIntDoubleVector)40 IntDoubleSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage)32 IntFloatVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatVectorStorage)32 IntIntVectorStorage (com.tencent.angel.ml.math2.storage.IntIntVectorStorage)32 IntLongVectorStorage (com.tencent.angel.ml.math2.storage.IntLongVectorStorage)32 LongDoubleVectorStorage (com.tencent.angel.ml.math2.storage.LongDoubleVectorStorage)30 LongFloatVectorStorage (com.tencent.angel.ml.math2.storage.LongFloatVectorStorage)30 LongIntVectorStorage (com.tencent.angel.ml.math2.storage.LongIntVectorStorage)30 LongLongVectorStorage (com.tencent.angel.ml.math2.storage.LongLongVectorStorage)30 Storage (com.tencent.angel.ml.math2.storage.Storage)30 IntDoubleSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage)26 IntDoubleDenseVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleDenseVectorStorage)23 IntFloatSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatSortedVectorStorage)20 IntFloatSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatSparseVectorStorage)20 IntIntSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntIntSortedVectorStorage)20 IntIntSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntIntSparseVectorStorage)20