| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| */ |
| |
| package org.apache.sysds.runtime.compress.lib; |
| |
| import java.util.ArrayList; |
| import java.util.List; |
| import java.util.concurrent.Callable; |
| import java.util.concurrent.ExecutionException; |
| import java.util.concurrent.ExecutorService; |
| import java.util.concurrent.Future; |
| |
| import org.apache.sysds.runtime.DMLRuntimeException; |
| import org.apache.sysds.runtime.compress.CompressedMatrixBlock; |
| import org.apache.sysds.runtime.compress.CompressionSettings; |
| import org.apache.sysds.runtime.compress.colgroup.ColGroup; |
| import org.apache.sysds.runtime.compress.colgroup.ColGroupUncompressed; |
| import org.apache.sysds.runtime.functionobjects.Builtin; |
| import org.apache.sysds.runtime.functionobjects.Builtin.BuiltinCode; |
| import org.apache.sysds.runtime.functionobjects.IndexFunction; |
| import org.apache.sysds.runtime.functionobjects.KahanFunction; |
| import org.apache.sysds.runtime.functionobjects.KahanPlus; |
| import org.apache.sysds.runtime.functionobjects.KahanPlusSq; |
| import org.apache.sysds.runtime.functionobjects.Mean; |
| import org.apache.sysds.runtime.functionobjects.Plus; |
| import org.apache.sysds.runtime.functionobjects.ReduceAll; |
| import org.apache.sysds.runtime.functionobjects.ReduceCol; |
| import org.apache.sysds.runtime.functionobjects.ReduceRow; |
| import org.apache.sysds.runtime.instructions.cp.KahanObject; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixAgg; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixBincell; |
| import org.apache.sysds.runtime.matrix.data.MatrixBlock; |
| import org.apache.sysds.runtime.matrix.data.MatrixIndexes; |
| import org.apache.sysds.runtime.matrix.operators.AggregateUnaryOperator; |
| import org.apache.sysds.runtime.matrix.operators.BinaryOperator; |
| import org.apache.sysds.runtime.util.CommonThreadPool; |
| |
| public class LibCompAgg { |
| |
| // private static final Log LOG = LogFactory.getLog(LibCompAgg.class.getName()); |
| |
| // private static final long MIN_PAR_AGG_THRESHOLD = 8 * 1024 * 1024; |
| private static final long MIN_PAR_AGG_THRESHOLD = 8; |
| |
| private static ThreadLocal<MatrixBlock> memPool = new ThreadLocal<MatrixBlock>() { |
| @Override |
| protected MatrixBlock initialValue() { |
| return null; |
| } |
| }; |
| |
| public static MatrixBlock aggregateUnary(CompressedMatrixBlock inputMatrix, MatrixBlock outputMatrix, |
| AggregateUnaryOperator op, int blen, MatrixIndexes indexesIn, boolean inCP) { |
| if(inputMatrix.getColGroups() != null) { |
| fillStart(outputMatrix, op); |
| |
| if(inputMatrix.isOverlapping() && |
| (op.aggOp.increOp.fn instanceof KahanPlusSq || (op.aggOp.increOp.fn instanceof Builtin && |
| (((Builtin) op.aggOp.increOp.fn).getBuiltinCode() == BuiltinCode.MIN || |
| ((Builtin) op.aggOp.increOp.fn).getBuiltinCode() == BuiltinCode.MAX)))) |
| aggregateUnaryOverlapping(inputMatrix, outputMatrix, op, indexesIn, inCP); |
| else |
| aggregateUnaryNormalCompressedMatrixBlock(inputMatrix, outputMatrix, op, blen, indexesIn, inCP); |
| } |
| |
| if(op.aggOp.existsCorrection() && inCP) |
| outputMatrix.dropLastRowsOrColumns(op.aggOp.correction); |
| |
| outputMatrix.recomputeNonZeros(); |
| |
| return outputMatrix; |
| } |
| |
| private static void aggregateUnaryNormalCompressedMatrixBlock(CompressedMatrixBlock inputMatrix, |
| MatrixBlock outputMatrix, AggregateUnaryOperator op, int blen, MatrixIndexes indexesIn, boolean inCP) { |
| |
| aggregateUncompressedColGroups(inputMatrix, outputMatrix, op); |
| |
| if(isValidForParallelProcessing(inputMatrix, op)) |
| tryToAggregateInParallel(inputMatrix, outputMatrix, op); |
| else |
| aggregateSingleThreaded(inputMatrix, outputMatrix, op); |
| |
| postProcessAggregate(inputMatrix, outputMatrix, op); |
| |
| } |
| |
| private static boolean isValidForParallelProcessing(CompressedMatrixBlock m1, AggregateUnaryOperator op) { |
| return op.getNumThreads() > 1 && m1.getExactSizeOnDisk() > MIN_PAR_AGG_THRESHOLD; |
| } |
| |
| private static void aggregateUncompressedColGroups(CompressedMatrixBlock m1, MatrixBlock ret, |
| AggregateUnaryOperator op) { |
| ColGroupUncompressed uc = m1.getUncompressedColGroup(); |
| if(uc != null) |
| uc.unaryAggregateOperations(op, ret); |
| } |
| |
| private static void tryToAggregateInParallel(CompressedMatrixBlock m1, MatrixBlock ret, AggregateUnaryOperator op) { |
| int k = op.getNumThreads(); |
| if(k == 1) |
| aggregateUnaryOperations(op, m1.getColGroups(), ret, 0, m1.getNumRows(), m1.getNumColumns()); |
| else |
| aggregateInParallel(m1, ret, op, k); |
| |
| } |
| |
| private static void aggregateInParallel(CompressedMatrixBlock m1, MatrixBlock ret, AggregateUnaryOperator op, |
| int k) { |
| |
| ExecutorService pool = CommonThreadPool.get(op.getNumThreads()); |
| ArrayList<UnaryAggregateTask> tasks = new ArrayList<>(); |
| try { |
| // compute all compressed column groups |
| if(op.indexFn instanceof ReduceCol) { |
| final int blkz = CompressionSettings.BITMAP_BLOCK_SZ; |
| // int blklen = Math.max((int) Math.ceil((double) m1.getNumRows() / (op.getNumThreads() * 2)), blkz); |
| // blklen += (blklen % blkz != 0) ? blkz - blklen % blkz : 0; |
| int blklen = blkz * 4; |
| for(int i = 0; i * blklen < m1.getNumRows(); i++) |
| tasks.add(new UnaryAggregateTask(m1.getColGroups(), ret, i * blklen, |
| Math.min((i + 1) * blklen, m1.getNumRows()), op, m1.getNumColumns())); |
| |
| } |
| else { |
| List<List<ColGroup>> grpParts = createTaskPartitionNotIncludingUncompressable(m1.getColGroups(), k); |
| for(List<ColGroup> grp : grpParts) |
| tasks.add(new UnaryAggregateTask(grp, ret, 0, m1.getNumRows(), op, m1.getNumColumns(), |
| m1.isOverlapping())); |
| } |
| |
| List<Future<MatrixBlock>> futures = pool.invokeAll(tasks); |
| pool.shutdown(); |
| |
| // aggregate partial results |
| if(op.indexFn instanceof ReduceAll) |
| if(op.aggOp.increOp.fn instanceof Builtin) |
| aggregateResults(ret, futures, op); |
| else |
| sumResults(ret, futures); |
| else if(op.indexFn instanceof ReduceRow && m1.isOverlapping()) { |
| if(op.aggOp.increOp.fn instanceof Builtin) |
| aggregateResultVectors(ret, futures, op); |
| else |
| sumResultVectors(ret, futures); |
| } |
| else |
| for(Future<MatrixBlock> f : futures) |
| f.get(); |
| } |
| catch(InterruptedException | ExecutionException e) { |
| throw new DMLRuntimeException(e); |
| } |
| } |
| |
| private static void sumResults(MatrixBlock ret, List<Future<MatrixBlock>> futures) |
| throws InterruptedException, ExecutionException { |
| double val = ret.quickGetValue(0, 0); |
| for(Future<MatrixBlock> rtask : futures) { |
| double tmp = rtask.get().quickGetValue(0, 0); |
| val = val + tmp; |
| } |
| ret.quickSetValue(0, 0, val); |
| |
| } |
| |
| private static void sumResultVectors(MatrixBlock ret, List<Future<MatrixBlock>> futures) |
| throws InterruptedException, ExecutionException { |
| |
| double[] retVals = ret.getDenseBlockValues(); |
| for(Future<MatrixBlock> rtask : futures) { |
| double[] taskResult = rtask.get().getDenseBlockValues(); |
| for(int i = 0; i < retVals.length; i++) { |
| retVals[i] += taskResult[i]; |
| } |
| } |
| ret.setNonZeros(ret.getNumColumns()); |
| } |
| |
| private static void aggregateResults(MatrixBlock ret, List<Future<MatrixBlock>> futures, AggregateUnaryOperator op) |
| throws InterruptedException, ExecutionException { |
| double val = ret.quickGetValue(0, 0); |
| for(Future<MatrixBlock> rtask : futures) { |
| double tmp = rtask.get().quickGetValue(0, 0); |
| val = op.aggOp.increOp.fn.execute(val, tmp); |
| } |
| ret.quickSetValue(0, 0, val); |
| } |
| |
| private static void aggregateResultVectors(MatrixBlock ret, List<Future<MatrixBlock>> futures, |
| AggregateUnaryOperator op) throws InterruptedException, ExecutionException { |
| double[] retVals = ret.getDenseBlockValues(); |
| for(Future<MatrixBlock> rtask : futures) { |
| double[] taskResult = rtask.get().getDenseBlockValues(); |
| for(int i = 0; i < retVals.length; i++) { |
| retVals[i] = op.aggOp.increOp.fn.execute(retVals[i] , taskResult[i]); |
| } |
| } |
| ret.setNonZeros(ret.getNumColumns()); |
| } |
| |
| private static void aggregateSingleThreaded(CompressedMatrixBlock m1, MatrixBlock ret, AggregateUnaryOperator op) { |
| aggregateUnaryOperations(op, m1.getColGroups(), ret, 0, m1.getNumRows(), m1.getNumColumns()); |
| } |
| |
| private static void divideByNumberOfCellsForMean(CompressedMatrixBlock m1, MatrixBlock ret, IndexFunction idxFn) { |
| if(idxFn instanceof ReduceAll) |
| divideByNumberOfCellsForMeanAll(m1, ret); |
| else if(idxFn instanceof ReduceCol) |
| divideByNumberOfCellsForMeanRows(m1, ret); |
| else if(idxFn instanceof ReduceRow) |
| divideByNumberOfCellsForMeanCols(m1, ret); |
| } |
| |
| private static void divideByNumberOfCellsForMeanRows(CompressedMatrixBlock m1, MatrixBlock ret) { |
| for(int i = 0; i < m1.getNumRows(); i++) { |
| ret.quickSetValue(i, 0, ret.quickGetValue(i, 0) / m1.getNumColumns()); |
| } |
| } |
| |
| private static void divideByNumberOfCellsForMeanCols(CompressedMatrixBlock m1, MatrixBlock ret) { |
| for(int i = 0; i < m1.getNumColumns(); i++) { |
| ret.quickSetValue(0, i, ret.quickGetValue(0, i) / m1.getNumRows()); |
| } |
| } |
| |
| private static void divideByNumberOfCellsForMeanAll(CompressedMatrixBlock m1, MatrixBlock ret) { |
| ret.quickSetValue(0, 0, ret.quickGetValue(0, 0) / (m1.getNumColumns() * m1.getNumRows())); |
| } |
| |
| private static void postProcessAggregate(CompressedMatrixBlock m1, MatrixBlock ret, AggregateUnaryOperator op) { |
| if(op.aggOp.increOp.fn instanceof Mean) |
| divideByNumberOfCellsForMean(m1, ret, op.indexFn); |
| |
| } |
| |
| private static void aggregateUnaryOverlapping(CompressedMatrixBlock m1, MatrixBlock ret, AggregateUnaryOperator op, |
| MatrixIndexes indexesIn, boolean inCP) { |
| try { |
| List<Future<MatrixBlock>> rtasks = generateUnaryAggregateOverlappingFutures(m1, ret, op); |
| reduceOverlappingFutures(rtasks, ret, op); |
| } |
| catch(InterruptedException | ExecutionException e) { |
| throw new DMLRuntimeException(e); |
| } |
| |
| } |
| |
| private static void reduceOverlappingFutures(List<Future<MatrixBlock>> rtasks, MatrixBlock ret, |
| AggregateUnaryOperator op) throws InterruptedException, ExecutionException { |
| if(isReduceAll(ret, op.indexFn)) |
| reduceAllOverlappingFutures(rtasks, ret, op); |
| else if(op.indexFn instanceof ReduceRow) |
| reduceColOverlappingFutures(rtasks, ret, op); |
| else |
| reduceRowOverlappingFutures(rtasks, ret, op); |
| } |
| |
| private static void reduceColOverlappingFutures(List<Future<MatrixBlock>> rtasks, MatrixBlock ret, |
| AggregateUnaryOperator op) throws InterruptedException, ExecutionException { |
| for(Future<MatrixBlock> rtask : rtasks) { |
| LibMatrixBincell.bincellOp(rtask.get(), |
| ret, |
| ret, |
| (op.aggOp.increOp.fn instanceof KahanFunction) ? new BinaryOperator( |
| Plus.getPlusFnObject()) : op.aggOp.increOp); |
| } |
| } |
| |
| private static void reduceRowOverlappingFutures(List<Future<MatrixBlock>> rtasks, MatrixBlock ret, |
| AggregateUnaryOperator op) throws InterruptedException, ExecutionException { |
| for(Future<MatrixBlock> rtask : rtasks) { |
| rtask.get(); |
| } |
| } |
| |
| private static boolean isReduceAll(MatrixBlock ret, IndexFunction idxFn) { |
| return idxFn instanceof ReduceAll || (ret.getNumColumns() == 1 && ret.getNumRows() == 1); |
| } |
| |
| private static void reduceAllOverlappingFutures(List<Future<MatrixBlock>> rtasks, MatrixBlock ret, |
| AggregateUnaryOperator op) throws InterruptedException, ExecutionException { |
| |
| if(op.aggOp.increOp.fn instanceof KahanFunction) { |
| KahanObject kbuff = new KahanObject(ret.quickGetValue(0, 0), 0); |
| KahanPlus kplus = KahanPlus.getKahanPlusFnObject(); |
| for(Future<MatrixBlock> rtask : rtasks) { |
| double tmp = rtask.get().quickGetValue(0, 0); |
| |
| kplus.execute2(kbuff, tmp); |
| } |
| ret.quickSetValue(0, 0, kbuff._sum); |
| } |
| else { |
| double val = ret.quickGetValue(0, 0); |
| for(Future<MatrixBlock> rtask : rtasks) { |
| double tmp = rtask.get().quickGetValue(0, 0); |
| val = op.aggOp.increOp.fn.execute(val, tmp); |
| |
| } |
| ret.quickSetValue(0, 0, val); |
| } |
| } |
| |
| private static List<Future<MatrixBlock>> generateUnaryAggregateOverlappingFutures(CompressedMatrixBlock m1, |
| MatrixBlock ret, AggregateUnaryOperator op) throws InterruptedException { |
| |
| ExecutorService pool = CommonThreadPool.get(op.getNumThreads()); |
| ArrayList<UnaryAggregateOverlappingTask> tasks = new ArrayList<>(); |
| |
| final int blklen = Math.min(m1.getNumRows() / op.getNumThreads(), CompressionSettings.BITMAP_BLOCK_SZ); |
| |
| for(int i = 0; i * blklen < m1.getNumRows(); i++) |
| tasks.add(new UnaryAggregateOverlappingTask(m1, ret, i * blklen, |
| Math.min((i + 1) * blklen, m1.getNumRows()), op)); |
| |
| List<Future<MatrixBlock>> futures = pool.invokeAll(tasks); |
| pool.shutdown(); |
| return futures; |
| } |
| |
| private static List<List<ColGroup>> createTaskPartitionNotIncludingUncompressable(List<ColGroup> colGroups, int k) { |
| int numTasks = Math.min(k, colGroups.size()); |
| List<List<ColGroup>> grpParts = new ArrayList<>(); |
| for(int i = 0; i < numTasks; i++) { |
| grpParts.add(new ArrayList<>()); |
| } |
| int pos = 0; |
| for(ColGroup grp : colGroups) { |
| if(!(grp instanceof ColGroupUncompressed)) { |
| List<ColGroup> g = grpParts.get(pos); |
| g.add(grp); |
| pos = (pos + 1) % numTasks; |
| } |
| } |
| |
| return grpParts; |
| } |
| |
| private static void aggregateUnaryOperations(AggregateUnaryOperator op, List<ColGroup> groups, MatrixBlock ret, |
| int rl, int ru, int numColumns) { |
| if(op.indexFn instanceof ReduceCol && op.aggOp.increOp.fn instanceof Builtin) |
| aggregateUnaryBuiltinRowOperation(op, groups, ret, rl, ru, numColumns); |
| else |
| aggregateUnaryNormalOperation(op, groups, ret, rl, ru, numColumns); |
| } |
| |
| private static void aggregateUnaryNormalOperation(AggregateUnaryOperator op, List<ColGroup> groups, MatrixBlock ret, |
| int rl, int ru, int numColumns) { |
| for(ColGroup grp : groups) |
| grp.unaryAggregateOperations(op, ret, rl, ru); |
| |
| } |
| |
| private static void aggregateUnaryBuiltinRowOperation(AggregateUnaryOperator op, List<ColGroup> groups, |
| MatrixBlock ret, int rl, int ru, int numColumns) { |
| |
| int[] rnnz = null; |
| int numberDenseColumns = 0; |
| for(ColGroup grp : groups) { |
| grp.unaryAggregateOperations(op, ret, rl, ru); |
| if(grp.isDense()) |
| numberDenseColumns += grp.getNumCols(); |
| else{ |
| if (rnnz == null) |
| rnnz = new int[ru - rl]; |
| grp.countNonZerosPerRow(rnnz, rl, ru); |
| } |
| } |
| if(rnnz != null) |
| for(int row = rl; row < ru; row++) |
| if(rnnz[row-rl] + numberDenseColumns < numColumns) |
| ret.quickSetValue(row, 0, op.aggOp.increOp.fn.execute(ret.quickGetValue(row, 0), 0.0)); |
| |
| } |
| |
| private static void fillStart(MatrixBlock ret, AggregateUnaryOperator op) { |
| if(op.aggOp.increOp.fn instanceof Builtin) { |
| Double val = null; |
| switch(((Builtin) op.aggOp.increOp.fn).getBuiltinCode()) { |
| case MAX: |
| val = Double.NEGATIVE_INFINITY; |
| break; |
| case MIN: |
| val = Double.POSITIVE_INFINITY; |
| break; |
| default: |
| break; |
| } |
| if(val != null) { |
| ret.getDenseBlock().set(val); |
| } |
| } |
| } |
| |
| private static class UnaryAggregateTask implements Callable<MatrixBlock> { |
| private final List<ColGroup> _groups; |
| private final int _rl; |
| private final int _ru; |
| private final MatrixBlock _ret; |
| private final int _numColumns; |
| private final AggregateUnaryOperator _op; |
| |
| protected UnaryAggregateTask(List<ColGroup> groups, MatrixBlock ret, int rl, int ru, AggregateUnaryOperator op, |
| int numColumns) { |
| _groups = groups; |
| _op = op; |
| _rl = rl; |
| _ru = ru; |
| _numColumns = numColumns; |
| |
| if(_op.indexFn instanceof ReduceAll) { // sum |
| _ret = new MatrixBlock(1, 1, false); |
| _ret.allocateDenseBlock(); |
| if(_op.aggOp.increOp.fn instanceof Builtin) |
| System.arraycopy(ret.getDenseBlockValues(), |
| 0, |
| _ret.getDenseBlockValues(), |
| 0, |
| ret.getNumRows() * ret.getNumColumns()); |
| } |
| else // colSums / rowSums |
| _ret = ret; |
| |
| } |
| |
| protected UnaryAggregateTask(List<ColGroup> groups, MatrixBlock ret, int rl, int ru, AggregateUnaryOperator op, |
| int numColumns, boolean overlapping) { |
| _groups = groups; |
| _op = op; |
| _rl = rl; |
| _ru = ru; |
| _numColumns = numColumns; |
| |
| if(_op.indexFn instanceof ReduceAll || (_op.indexFn instanceof ReduceRow && overlapping)) { |
| _ret = new MatrixBlock(ret.getNumRows(), ret.getNumColumns(), false); |
| _ret.allocateDenseBlock(); |
| if(_op.aggOp.increOp.fn instanceof Builtin) |
| System.arraycopy(ret.getDenseBlockValues(), |
| 0, |
| _ret.getDenseBlockValues(), |
| 0, |
| ret.getNumRows() * ret.getNumColumns()); |
| } |
| else // colSums / rowSums |
| _ret = ret; |
| } |
| |
| @Override |
| public MatrixBlock call() { |
| aggregateUnaryOperations(_op, _groups, _ret, _rl, _ru, _numColumns); |
| return _ret; |
| } |
| } |
| |
| private static class UnaryAggregateOverlappingTask implements Callable<MatrixBlock> { |
| private final CompressedMatrixBlock _m1; |
| private final int _rl; |
| private final int _ru; |
| private final MatrixBlock _ret; |
| private final AggregateUnaryOperator _op; |
| |
| protected UnaryAggregateOverlappingTask(CompressedMatrixBlock m1, MatrixBlock ret, int rl, int ru, |
| AggregateUnaryOperator op) { |
| _m1 = m1; |
| _op = op; |
| _rl = rl; |
| _ru = ru; |
| _ret = ret; |
| |
| } |
| |
| private MatrixBlock setupOutputMatrix() { |
| MatrixBlock outputBlock; |
| if(_op.indexFn instanceof ReduceAll) |
| outputBlock = new MatrixBlock(_ret.getNumRows(), _ret.getNumColumns(), false).allocateDenseBlock(); |
| else if(_op.indexFn instanceof ReduceCol) |
| outputBlock = new MatrixBlock(_ru - _rl, _ret.getNumColumns(), false).allocateDenseBlock(); |
| else |
| outputBlock = new MatrixBlock(_ret.getNumRows(), _ret.getNumColumns(), false).allocateDenseBlock(); |
| |
| if(_op.aggOp.increOp.fn instanceof Builtin) |
| if(_op.indexFn instanceof ReduceCol) |
| System.arraycopy(_ret.getDenseBlockValues(), |
| _rl * _ret.getNumColumns(), |
| outputBlock.getDenseBlockValues(), |
| 0, |
| outputBlock.getDenseBlockValues().length); |
| else |
| System.arraycopy(_ret.getDenseBlockValues(), |
| 0, |
| outputBlock.getDenseBlockValues(), |
| 0, |
| _ret.getDenseBlockValues().length); |
| |
| return outputBlock; |
| } |
| |
| private MatrixBlock getTmp() { |
| MatrixBlock tmp = memPool.get(); |
| if(tmp == null) { |
| memPool.set(new MatrixBlock(_ru - _rl, _m1.getNumColumns(), false, -1).allocateBlock()); |
| tmp = memPool.get(); |
| } |
| else { |
| tmp = memPool.get(); |
| tmp.reset(_ru - _rl, _m1.getNumColumns(), false, -1); |
| } |
| return tmp; |
| } |
| |
| private MatrixBlock decompressToTemp() { |
| MatrixBlock tmp = getTmp(); |
| for(ColGroup g : _m1.getColGroups()) |
| g.decompressToBlockSafe(tmp, _rl, _ru, 0, g.getValues(), false); |
| tmp.setNonZeros(_rl + _ru); |
| return tmp; |
| } |
| |
| @Override |
| public MatrixBlock call() { |
| MatrixBlock tmp = decompressToTemp(); |
| |
| MatrixBlock outputBlock = setupOutputMatrix(); |
| LibMatrixAgg.aggregateUnaryMatrix(tmp, outputBlock, _op); |
| |
| if(_op.indexFn instanceof ReduceCol) { |
| double[] retValues = _ret.getDenseBlockValues(); |
| int currentIndex = _rl * _ret.getNumColumns(); |
| double[] outputBlockValues = outputBlock.getDenseBlockValues(); |
| System.arraycopy(outputBlockValues, 0, retValues, currentIndex, outputBlockValues.length); |
| |
| return null; |
| } |
| else { |
| |
| return outputBlock; |
| } |
| } |
| } |
| } |
