Example 41 with IntDoubleVector
use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(IntDoubleVector v1, IntDoubleVector v2, Binary op) {
IntDoubleVector res;
if (v1.isDense() && v2.isDense()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
double[] v2Values = v2.getStorage().getValues();
for (int idx = 0; idx < resValues.length; idx++) {
resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
}
} else if (v1.isDense() && v2.isSparse()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
}
} else {
IntDoubleVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isDense() && v2.isSorted()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
double[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
} else {
IntDoubleVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isSparse() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
double[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
}
} else {
for (int i = 0; i < resValues.length; i++) {
if (v1.getStorage().hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
double[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
}
} else {
IntDoubleVectorStorage v1Storage = v1.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v1Storage.hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
}
}
} else {
IntDoubleVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
double[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
}
} else {
IntDoubleVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = v1Values[i];
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
}
}
} else {
IntDoubleVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
int size1 = v1.size();
int size2 = v2.size();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int[] v2Indices = v2.getStorage().getIndices();
double[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Double.NaN;
}
}
while (v1Pointor < size1 && v2Pointor < size2) {
if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
v1Pointor++;
v2Pointor++;
} else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
v1Pointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
v2Pointor++;
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
Also used :
AngelException(com.tencent.angel.exception.AngelException)
IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)
Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap)
IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)
ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)
Example 42 with IntDoubleVector
use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(IntDoubleVector v1, IntLongVector v2, Binary op) {
IntDoubleVector res;
if (v1.isDense() && v2.isDense()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
long[] v2Values = v2.getStorage().getValues();
for (int idx = 0; idx < resValues.length; idx++) {
resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
}
} else if (v1.isDense() && v2.isSparse()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2LongMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
}
} else {
IntLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isDense() && v2.isSorted()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
long[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
} else {
IntLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isSparse() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
long[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
}
} else {
for (int i = 0; i < resValues.length; i++) {
if (v1.getStorage().hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
long[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
}
} else {
IntDoubleVectorStorage v1Storage = v1.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v1Storage.hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2LongMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
}
}
} else {
IntLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
long[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
}
} else {
IntLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = v1Values[i];
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2LongMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
}
}
} else {
IntLongVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
int size1 = v1.size();
int size2 = v2.size();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int[] v2Indices = v2.getStorage().getIndices();
long[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Double.NaN;
}
}
while (v1Pointor < size1 && v2Pointor < size2) {
if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
v1Pointor++;
v2Pointor++;
} else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
v1Pointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
v2Pointor++;
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
Also used :
AngelException(com.tencent.angel.exception.AngelException)
Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap)
IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)
ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)
IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)
IntLongVectorStorage(com.tencent.angel.ml.math2.storage.IntLongVectorStorage)
Int2LongMap(it.unimi.dsi.fastutil.ints.Int2LongMap)
Example 43 with IntDoubleVector
use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(IntDoubleVector v1, IntFloatVector v2, Binary op) {
IntDoubleVector res;
if (v1.isDense() && v2.isDense()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
float[] v2Values = v2.getStorage().getValues();
for (int idx = 0; idx < resValues.length; idx++) {
resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
}
} else if (v1.isDense() && v2.isSparse()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(v1.get(idx), entry.getFloatValue());
}
} else {
IntFloatVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isDense() && v2.isSorted()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
} else {
IntFloatVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
} else if (v1.isSparse() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
float[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
}
} else {
for (int i = 0; i < resValues.length; i++) {
if (v1.getStorage().hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isDense()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
float[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
}
} else {
IntDoubleVectorStorage v1Storage = v1.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v1Storage.hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getFloatValue());
}
}
} else {
IntFloatVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSparse() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
}
}
} else {
IntFloatVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = v1Values[i];
}
if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(resValues[i], 0);
}
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
if (v1.getStorage().hasKey(idx)) {
resValues[idx] = op.apply(v1.get(idx), entry.getFloatValue());
}
}
} else {
IntFloatVectorStorage v2Storage = v2.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v2Storage.hasKey(i)) {
resValues[i] = op.apply(resValues[i], v2.get(i));
} else {
resValues[i] = op.apply(resValues[i], 0);
}
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else if (v1.isSorted() && v2.isSorted()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
int size1 = v1.size();
int size2 = v2.size();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Double.NaN;
}
}
while (v1Pointor < size1 && v2Pointor < size2) {
if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
v1Pointor++;
v2Pointor++;
} else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
v1Pointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
v2Pointor++;
}
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
Also used :
AngelException(com.tencent.angel.exception.AngelException)
Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap)
IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)
ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)
IntFloatVectorStorage(com.tencent.angel.ml.math2.storage.IntFloatVectorStorage)
IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)
Int2FloatMap(it.unimi.dsi.fastutil.ints.Int2FloatMap)
Example 44 with IntDoubleVector
use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(IntDoubleVector v1, IntDummyVector v2, Binary op) {
IntDoubleVector res;
if (v1.isDense()) {
res = v1.copy();
double[] resValues = res.getStorage().getValues();
for (int i = 0; i < v1.getDim(); i++) {
resValues[i] = op.apply(resValues[i], v2.get(i));
}
} else if (v1.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
resValues[idx] = entry.getDoubleValue();
}
for (int i = 0; i < v1.getDim(); i++) {
resValues[i] = op.apply(resValues[i], v2.get(i));
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
// sorted
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
double[] resValues = newStorage.getValues();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = v1Values[i];
}
for (int i = 0; i < v1.getDim(); i++) {
resValues[i] = op.apply(resValues[i], v2.get(i));
}
res = new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
}
return res;
}
Also used :
AngelException(com.tencent.angel.exception.AngelException)
IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)
Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap)
IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)
ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)
Example 45 with IntDoubleVector
use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.
the class SimpleBinaryOutNonZAExecutor method apply.
public static Vector apply(IntDoubleVector v1, IntFloatVector v2, Binary op) {
IntDoubleVectorStorage newStorage = (IntDoubleVectorStorage) StorageSwitch.apply(v1, v2, op);
if (v1.isDense() && v2.isDense()) {
double[] resValues = newStorage.getValues();
double[] v1Values = v1.getStorage().getValues();
float[] v2Values = v2.getStorage().getValues();
for (int idx = 0; idx < resValues.length; idx++) {
resValues[idx] = op.apply(v1Values[idx], v2Values[idx]);
}
} else if (v1.isDense() && v2.isSparse()) {
double[] resValues = newStorage.getValues();
double[] v1Values = v1.getStorage().getValues();
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(v1Values[idx], entry.getFloatValue());
}
} else if (v1.isDense() && v2.isSorted()) {
double[] resValues = newStorage.getValues();
double[] v1Values = v1.getStorage().getValues();
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
resValues[idx] = op.apply(v1Values[idx], v2Values[i]);
}
} else if (v1.isSparse() && v2.isDense()) {
if (op.isKeepStorage()) {
int dim = v1.getDim();
float[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
for (int i = 0; i < dim; i++) {
newStorage.set(i, op.apply(0, v2Values[i]));
}
ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx]));
}
} else {
for (int i = 0; i < dim; i++) {
if (v1.getStorage().hasKey(i)) {
newStorage.set(i, op.apply(v1.get(i), v2Values[i]));
} else {
newStorage.set(i, op.apply(0, v2Values[i]));
}
}
}
} else {
double[] resValues = newStorage.getValues();
float[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
while (iter.hasNext()) {
Int2DoubleMap.Entry entry = iter.next();
int idx = entry.getIntKey();
resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
}
} else {
for (int i = 0; i < resValues.length; i++) {
if (v1.getStorage().hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
}
} else if (v1.isSorted() && v2.isDense()) {
if (op.isKeepStorage()) {
int dim = v1.getDim();
int[] resIndices = newStorage.getIndices();
double[] resValues = newStorage.getValues();
float[] v2Values = v2.getStorage().getValues();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
for (int i = 0; i < dim; i++) {
resIndices[i] = i;
resValues[i] = op.apply(0, v2Values[i]);
}
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
}
} else {
double[] resValues = newStorage.getValues();
float[] v2Values = v2.getStorage().getValues();
if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
for (int i = 0; i < resValues.length; i++) {
resValues[i] = op.apply(0, v2Values[i]);
}
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
}
} else {
IntDoubleVectorStorage v1Storage = v1.getStorage();
for (int i = 0; i < resValues.length; i++) {
if (v1Storage.hasKey(i)) {
resValues[i] = op.apply(v1.get(i), v2Values[i]);
} else {
resValues[i] = op.apply(0, v2Values[i]);
}
}
}
}
} else if (v1.isSparse() && v2.isSparse()) {
int v1Size = v1.size();
int v2Size = v2.size();
if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
// we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
}
} else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
// we gauss dense storage is more efficient
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
newStorage.set(idx, entry.getDoubleValue());
}
ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
while (iter2.hasNext()) {
Int2FloatMap.Entry entry = iter2.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
}
} else {
// to avoid multi-rehash
int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
if (v1.size() + v2.size() <= 1.5 * capacity) {
// no rehashor one onle rehash is required, nothing to optimization
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
}
} else {
// multi-rehash
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
newStorage.set(idx, entry.getDoubleValue());
}
ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
while (iter2.hasNext()) {
Int2FloatMap.Entry entry = iter2.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
}
}
}
} else if (v1.isSparse() && v2.isSorted()) {
int v1Size = v1.size();
int v2Size = v2.size();
if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
// we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < v2.size(); i++) {
int idx = v2Indices[i];
newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
}
} else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
newStorage.set(idx, entry.getDoubleValue());
}
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
}
} else {
// to avoid multi-rehash
int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
if (v1.size() + v2.size() <= 1.5 * capacity) {
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
for (int i = 0; i < v2.size(); i++) {
int idx = v2Indices[i];
newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
}
} else {
ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
while (iter1.hasNext()) {
Int2DoubleMap.Entry entry = iter1.next();
int idx = entry.getIntKey();
newStorage.set(idx, entry.getDoubleValue());
}
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
int size = v2.size();
for (int i = 0; i < size; i++) {
int idx = v2Indices[i];
newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
}
}
}
} else if (v1.isSorted() && v2.isSparse()) {
int v1Size = v1.size();
int v2Size = v2.size();
if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
if (op.isKeepStorage()) {
int[] v1Indices = v1.getStorage().getIndices();
int[] idxiter = v2.getStorage().indexIterator().toIntArray();
int[] indices = new int[(int) (v1Size + v2Size)];
System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
IntAVLTreeSet avl = new IntAVLTreeSet(indices);
IntBidirectionalIterator iter = avl.iterator();
double[] values = new double[indices.length];
int i = 0;
while (iter.hasNext()) {
int idx = iter.nextInt();
indices[i] = idx;
values[i] = op.apply(v1.get(idx), v2.get(idx));
i++;
}
while (i < indices.length) {
indices[i] = 0;
i++;
}
newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
} else {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
newStorage.set(idx, v1Values[i]);
}
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
}
}
} else {
if (op.isKeepStorage()) {
int[] v1Indices = v1.getStorage().getIndices();
int[] idxiter = v2.getStorage().indexIterator().toIntArray();
int[] indices = new int[(int) (v1Size + v2Size)];
System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
IntAVLTreeSet avl = new IntAVLTreeSet(indices);
IntBidirectionalIterator iter = avl.iterator();
double[] values = new double[indices.length];
int i = 0;
while (iter.hasNext()) {
int idx = iter.nextInt();
indices[i] = idx;
values[i] = op.apply(v1.get(idx), v2.get(idx));
i++;
}
while (i < indices.length) {
indices[i] = 0;
i++;
}
newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
} else {
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int size = v1.size();
for (int i = 0; i < size; i++) {
int idx = v1Indices[i];
newStorage.set(idx, v1Values[i]);
}
ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
while (iter.hasNext()) {
Int2FloatMap.Entry entry = iter.next();
int idx = entry.getIntKey();
newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
}
}
}
} else if (v1.isSorted() && v2.isSorted()) {
int v1Pointor = 0;
int v2Pointor = 0;
int size1 = v1.size();
int size2 = v2.size();
int[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
int[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
if (op.isKeepStorage()) {
// sorted
int[] resIndices = newStorage.getIndices();
double[] resValues = newStorage.getValues();
int global = 0;
while (v1Pointor < size1 && v2Pointor < size2) {
if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
resIndices[global] = v1Indices[v1Pointor];
resValues[global] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
global++;
v1Pointor++;
v2Pointor++;
} else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
resIndices[global] = v1Indices[v1Pointor];
resValues[global] = v1Values[v1Pointor];
global++;
v1Pointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resIndices[global] = v2Indices[v2Pointor];
resValues[global] = op.apply(0, v2Values[v2Pointor]);
global++;
v2Pointor++;
}
}
} else {
// dense
while (v1Pointor < size1 || v2Pointor < size2) {
if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
v1Pointor++;
v2Pointor++;
} else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
v1Pointor++;
} else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
v2Pointor++;
}
}
}
} else {
if (op.isKeepStorage()) {
int[] resIndices = newStorage.getIndices();
double[] resValues = newStorage.getValues();
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] = v1Values[v1Pointor];
v1Pointor++;
globalPointor++;
} else {
// v1Indices[v1Pointor] > v2Indices[v2Pointor]
resIndices[globalPointor] = v2Indices[v2Pointor];
resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
v2Pointor++;
globalPointor++;
}
}
} else {
while (v1Pointor < size1 || v2Pointor < size2) {
if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
v1Pointor++;
v2Pointor++;
} else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
v1Pointor++;
} else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
v2Pointor++;
}
}
}
}
} else {
throw new AngelException("The operation is not support!");
}
return new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
Also used :
AngelException(com.tencent.angel.exception.AngelException)
Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap)
IntBidirectionalIterator(it.unimi.dsi.fastutil.ints.IntBidirectionalIterator)
ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)
IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector)
IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)
Int2FloatMap(it.unimi.dsi.fastutil.ints.Int2FloatMap)
IntAVLTreeSet(it.unimi.dsi.fastutil.ints.IntAVLTreeSet)
IntDoubleSortedVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage)
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
