use of com.tencent.angel.ml.math2.storage.LongLongSparseVectorStorage in project angel by Tencent.
the class RangeRouterUtils method splitLongLongVector.
public static KeyValuePart[] splitLongLongVector(MatrixMeta matrixMeta, LongLongVector vector) {
LongLongVectorStorage storage = vector.getStorage();
if (storage.isSparse()) {
// Get keys and values
LongLongSparseVectorStorage sparseStorage = (LongLongSparseVectorStorage) storage;
long[] keys = sparseStorage.getIndices();
long[] values = sparseStorage.getValues();
return split(matrixMeta, vector.getRowId(), keys, values, false);
} else {
// Key and value array pair
LongLongSortedVectorStorage sortStorage = (LongLongSortedVectorStorage) storage;
long[] keys = sortStorage.getIndices();
long[] values = sortStorage.getValues();
return split(matrixMeta, vector.getRowId(), keys, values, true);
}
}
use of com.tencent.angel.ml.math2.storage.LongLongSparseVectorStorage in project angel by Tencent.
the class MixedBinaryOutAllExecutor method apply.
private static Vector apply(CompLongLongVector v1, LongDummyVector v2, Binary op) {
LongLongVector[] parts = v1.getPartitions();
Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
if (!op.isKeepStorage()) {
for (int i = 0; i < parts.length; i++) {
if (parts[i].getStorage() instanceof LongLongSortedVectorStorage) {
resParts[i] = new LongLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
}
}
}
long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
for (int i = 0; i < v1.getDim(); i++) {
int pidx = (int) (i / subDim);
long subidx = i % subDim;
((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
}
LongLongVector[] res = new LongLongVector[parts.length];
int i = 0;
for (LongLongVector part : parts) {
res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
i++;
}
return new CompLongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}
use of com.tencent.angel.ml.math2.storage.LongLongSparseVectorStorage in project angel by Tencent.
the class MixedBinaryOutAllExecutor method apply.
private static Vector apply(CompLongLongVector v1, LongLongVector v2, Binary op) {
LongLongVector[] parts = v1.getPartitions();
Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
if (!op.isKeepStorage()) {
for (int i = 0; i < parts.length; i++) {
if (parts[i].getStorage() instanceof LongLongSortedVectorStorage) {
resParts[i] = new LongLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
}
}
}
long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
for (int i = 0; i < v1.getDim(); i++) {
int pidx = (int) (i / subDim);
long subidx = i % subDim;
if (v2.getStorage().hasKey(i)) {
((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
} else {
((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
}
}
LongLongVector[] res = new LongLongVector[parts.length];
int i = 0;
for (LongLongVector part : parts) {
res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
i++;
}
return new CompLongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}
use of com.tencent.angel.ml.math2.storage.LongLongSparseVectorStorage in project angel by Tencent.
the class MixedBinaryOutAllExecutor method apply.
private static Vector apply(CompLongLongVector v1, LongIntVector v2, Binary op) {
LongLongVector[] parts = v1.getPartitions();
Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
if (!op.isKeepStorage()) {
for (int i = 0; i < parts.length; i++) {
if (parts[i].getStorage() instanceof LongLongSortedVectorStorage) {
resParts[i] = new LongLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
}
}
}
long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
for (int i = 0; i < v1.getDim(); i++) {
int pidx = (int) (i / subDim);
long subidx = i % subDim;
if (v2.getStorage().hasKey(i)) {
((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
} else {
((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
}
}
LongLongVector[] res = new LongLongVector[parts.length];
int i = 0;
for (LongLongVector part : parts) {
res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
i++;
}
return new CompLongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}
use of com.tencent.angel.ml.math2.storage.LongLongSparseVectorStorage in project angel by Tencent.
the class SimpleBinaryInAllExecutor method apply.
public static Vector apply(LongLongVector v1, LongLongVector v2, Binary op) {
if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
// multi-rehash
LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongLongVectorStorage v1Storage = v1.getStorage();
LongLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < v1.getDim(); i++) {
if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
} else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), 0));
} else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(0, v2.get(i)));
} else {
newStorage.set(i, op.apply(0, 0));
}
}
v1.setStorage(newStorage);
}
} else if (v1.isSparse() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongLongVectorStorage v1Storage = v1.getStorage();
LongLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < v1.getDim(); i++) {
if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
} else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), 0));
} else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(0, v2.get(i)));
} else {
newStorage.set(i, op.apply(0, 0));
}
}
v1.setStorage(newStorage);
}
} else if (v1.isSorted() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
LongLongVectorStorage newStorage = new LongLongSparseVectorStorage(v1.getDim());
LongLongVectorStorage v1Storage = v1.getStorage();
LongLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < v1.getDim(); i++) {
if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
} else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), 0));
} else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
newStorage.set(i, op.apply(0, v2.get(i)));
} else {
newStorage.set(i, op.apply(0, 0));
}
}
v1.setStorage(newStorage);
}
} else if (v1.isSorted() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
LongLongVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
long[] resIndices = newStorage.getIndices();
long[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
long size1 = v1.size();
long size2 = v2.size();
long[] v1Indices = v1.getStorage().getIndices();
long[] v1Values = v1.getStorage().getValues();
long[] v2Indices = v2.getStorage().getIndices();
long[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
if (size1 != v1.getDim() && size2 != v2.getDim()) {
for (int i = 0; i < v1.getDim(); i++) {
resValues[i] = 0 / 0;
}
}
}
int globalPointor = 0;
while (v1Pointor < size1 && v2Pointor < size2) {
if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
resIndices[globalPointor] = v1Indices[v1Pointor];
resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
v1Pointor++;
v2Pointor++;
globalPointor++;
} else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
resIndices[globalPointor] = v1Indices[v1Pointor];
resValues[globalPointor] = op.apply(v2Values[v2Pointor], 0);
v1Pointor++;
globalPointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resIndices[globalPointor] = v2Indices[v2Pointor];
resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
v2Pointor++;
globalPointor++;
}
}
v1.setStorage(newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return v1;
}
Aggregations