use of com.tencent.angel.ml.math2.storage.LongFloatVectorStorage in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(LongFloatVector v1, LongFloatVector v2, Binary op) {
LongFloatVector res;
if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
// multi-rehash
LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongFloatVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongFloatVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = new LongFloatSparseVectorStorage(v1.getDim());
LongFloatVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
long[] resIndices = newStorage.getIndices();
float[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
long size1 = v1.size();
long size2 = v2.size();
long[] v1Indices = v1.getStorage().getIndices();
float[] v1Values = v1.getStorage().getValues();
long[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Float.NaN;
}
}
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++;
}
}
res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
use of com.tencent.angel.ml.math2.storage.LongFloatVectorStorage in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(LongDoubleVector v1, LongFloatVector v2, Binary op) {
LongDoubleVector res;
if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
// multi-rehash
LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongDoubleVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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, 0));
}
}
res = new LongDoubleVector(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 {
LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongDoubleVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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, 0));
}
}
res = new LongDoubleVector(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 {
LongDoubleVectorStorage newStorage = new LongDoubleSparseVectorStorage(v1.getDim());
LongDoubleVectorStorage v1Storage = v1.getStorage();
LongFloatVectorStorage 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, 0));
}
}
res = new LongDoubleVector(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 {
LongDoubleVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
long[] resIndices = newStorage.getIndices();
double[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
long size1 = v1.size();
long size2 = v2.size();
long[] v1Indices = v1.getStorage().getIndices();
double[] v1Values = v1.getStorage().getValues();
long[] v2Indices = v2.getStorage().getIndices();
float[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Double.NaN;
}
}
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++;
}
}
res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
use of com.tencent.angel.ml.math2.storage.LongFloatVectorStorage in project angel by Tencent.
the class SimpleBinaryOutAllExecutor method apply.
public static Vector apply(LongFloatVector v1, LongIntVector v2, Binary op) {
LongFloatVector res;
if (v1.isSparse() && v2.isSparse()) {
if (op.isKeepStorage()) {
throw new AngelException("operation is not support!");
} else {
// multi-rehash
LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongFloatVectorStorage v1Storage = v1.getStorage();
LongIntVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
LongFloatVectorStorage v1Storage = v1.getStorage();
LongIntVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = new LongFloatSparseVectorStorage(v1.getDim());
LongFloatVectorStorage v1Storage = v1.getStorage();
LongIntVectorStorage 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(0.0f, 0));
}
}
res = new LongFloatVector(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 {
LongFloatVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
long[] resIndices = newStorage.getIndices();
float[] resValues = newStorage.getValues();
int v1Pointor = 0;
int v2Pointor = 0;
long size1 = v1.size();
long size2 = v2.size();
long[] v1Indices = v1.getStorage().getIndices();
float[] v1Values = v1.getStorage().getValues();
long[] v2Indices = v2.getStorage().getIndices();
int[] v2Values = v2.getStorage().getValues();
if (!op.isCompare()) {
for (int i = 0; i < resValues.length; i++) {
resValues[i] = Float.NaN;
}
}
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++;
}
}
res = new LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
} else {
throw new AngelException("The operation is not support!");
}
return res;
}
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