use of com.tencent.angel.ml.math2.vector.IntLongVector in project angel by Tencent.
the class RowSplitCombineUtils method combineIntLongIndexRowSplits.
// //////////////////////////////////////////////////////////////////////////////
// Combine Int key Long value vector
// //////////////////////////////////////////////////////////////////////////////
public static Vector combineIntLongIndexRowSplits(int matrixId, int rowId, int resultSize, KeyPart[] keyParts, ValuePart[] valueParts, MatrixMeta matrixMeta) {
IntLongVector vector = VFactory.sparseLongVector((int) matrixMeta.getColNum(), resultSize);
for (int i = 0; i < keyParts.length; i++) {
mergeTo(vector, keyParts[i], (LongValuesPart) valueParts[i]);
}
vector.setRowId(rowId);
vector.setMatrixId(matrixId);
return vector;
}
use of com.tencent.angel.ml.math2.vector.IntLongVector in project angel by Tencent.
the class MergeUtils method combineServerIntLongRowSplits.
private static Vector combineServerIntLongRowSplits(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();
}
IntLongVector row;
if (matrixMeta.isHash()) {
row = VFactory.sparseLongVector(colNum, elemNum);
} else {
if (elemNum >= (int) (storageConvFactor * colNum)) {
row = VFactory.denseLongVector(colNum);
} else {
row = VFactory.sparseLongVector(colNum, elemNum);
}
}
row.setMatrixId(matrixMeta.getId());
row.setRowId(rowIndex);
Collections.sort(rowSplits, serverRowComp);
for (int i = 0; i < size; i++) {
if (rowSplits.get(i) == null) {
continue;
}
((ServerIntLongRow) rowSplits.get(i)).mergeTo(row);
}
return row;
}
use of com.tencent.angel.ml.math2.vector.IntLongVector in project angel by Tencent.
the class CompIntLongVectorSplitter method split.
@Override
public Map<PartitionKey, RowUpdateSplit> split(Vector vector, List<PartitionKey> parts) {
IntLongVector[] vecParts = ((CompIntLongVector) 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 CompIntLongRowUpdateSplit(vector.getRowId(), vecParts[i], (int) (parts.get(i).getEndCol() - parts.get(i).getStartCol())));
}
return updateSplitMap;
}
use of com.tencent.angel.ml.math2.vector.IntLongVector in project angel by Tencent.
the class RowSplitCombineUtils method combineServerIntLongRowSplits.
private static Vector combineServerIntLongRowSplits(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();
}
IntLongVector row;
if (elemNum >= (int) (storageConvFactor * colNum)) {
row = VFactory.denseLongVector(colNum);
} else {
row = VFactory.sparseLongVector(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();
}
((ServerIntLongRow) rowSplits.get(i)).mergeTo(row);
}
row.setClock(clock);
return row;
}
use of com.tencent.angel.ml.math2.vector.IntLongVector in project angel by Tencent.
the class MixedBinaryOutNonZAExecutor method apply.
private static Vector apply(CompIntFloatVector v1, IntLongVector v2, Binary op) {
IntFloatVector[] parts = v1.getPartitions();
Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
if (v2.isDense()) {
long[] v2Values = v2.getStorage().getValues();
int base = 0, k = 0;
for (IntFloatVector part : parts) {
IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[k];
float[] newValues = resPart.getValues();
if (part.isDense()) {
float[] partValue = part.getStorage().getValues();
for (int i = 0; i < partValue.length; i++) {
int idx = i + base;
newValues[i] = op.apply(partValue[i], v2Values[idx]);
}
} else if (part.isSparse()) {
if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
for (int i = 0; i < part.getDim(); i++) {
resPart.set(i, op.apply(0, v2Values[i + base]));
}
ObjectIterator<Int2FloatMap.Entry> iter = part.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resPart.set(idx, op.apply(entry.getFloatValue(), v2Values[idx + base]));
}
} else {
for (int i = 0; i < newValues.length; i++) {
if (part.getStorage().hasKey(i)) {
resPart.set(i, op.apply(part.get(i), v2Values[i + base]));
} else {
resPart.set(i, op.apply(0, v2Values[i + base]));
}
}
}
} else {
// sorted
if (op.isKeepStorage()) {
int dim = part.getDim();
int[] resIndices = resPart.getIndices();
float[] resValues = resPart.getValues();
int[] partIndices = part.getStorage().getIndices();
float[] partValues = part.getStorage().getValues();
for (int i = 0; i < dim; i++) {
resIndices[i] = i;
resValues[i] = op.apply(0, v2Values[i + base]);
}
int size = part.size();
for (int i = 0; i < size; i++) {
int idx = partIndices[i];
resValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
}
} else {
if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
int[] partIndices = part.getStorage().getIndices();
float[] partValues = part.getStorage().getValues();
for (int i = 0; i < part.getDim(); i++) {
newValues[i] = op.apply(0, v2Values[i + base]);
}
int size = part.size();
for (int i = 0; i < size; i++) {
int idx = partIndices[i];
newValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
}
} else {
IntFloatVectorStorage partStorage = part.getStorage();
for (int i = 0; i < newValues.length; i++) {
if (partStorage.hasKey(i)) {
newValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
} else {
newValues[i] = op.apply(0, v2Values[i + base]);
}
}
}
}
}
base += part.getDim();
k++;
}
} else {
if (v2.isSparse()) {
if (!op.isKeepStorage()) {
for (int i = 0; i < parts.length; i++) {
if (parts[i].getStorage() instanceof IntFloatSortedVectorStorage) {
resParts[i] = new IntFloatSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
}
}
}
int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2LongMap.Entry entry = iter.next();
int gidx = entry.getIntKey();
int pidx = (int) (gidx / subDim);
int subidx = gidx % subDim;
((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getLongValue()));
}
} else {
// sorted
if (!op.isKeepStorage()) {
for (int i = 0; i < parts.length; i++) {
if (parts[i].getStorage() instanceof IntFloatSortedVectorStorage) {
resParts[i] = new IntFloatSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
}
}
}
int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
int[] v2Indices = v2.getStorage().getIndices();
long[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < v2Indices.length; i++) {
int gidx = v2Indices[i];
int pidx = (int) (gidx / subDim);
int subidx = gidx % subDim;
((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
}
}
}
IntFloatVector[] res = new IntFloatVector[parts.length];
int i = 0;
for (IntFloatVector part : parts) {
res[i] = new IntFloatVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntFloatVectorStorage) resParts[i]);
i++;
}
return new CompIntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}
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