wehub-resource-sync
259 lines
8.6 KiB
C++
259 lines
8.6 KiB
C++
/*
|
|
* ******************************************************************************
|
|
* *
|
|
* *
|
|
* * This program and the accompanying materials are made available under the
|
|
* * terms of the Apache License, Version 2.0 which is available at
|
|
* * https://www.apache.org/licenses/LICENSE-2.0.
|
|
* *
|
|
* * See the NOTICE file distributed with this work for additional
|
|
* * information regarding copyright ownership.
|
|
* * 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.
|
|
* *
|
|
* * SPDX-License-Identifier: Apache-2.0
|
|
* *****************************************************************************
|
|
*/
|
|
|
|
//
|
|
// @author Yurii Shyrma (iuriish@yahoo.com), created on 20.04.2018
|
|
// @author Oleh Semeniv (oleg.semeniv@gmail.com)
|
|
//
|
|
#include <helpers/Loops.h>
|
|
#include <ops/declarable/helpers/transforms.h>
|
|
#if NOT_EXCLUDED(OP_merge)
|
|
namespace sd {
|
|
namespace ops {
|
|
namespace helpers {
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename X, typename Z>
|
|
static void mergeMaxIndex_(const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
const sd::LongType numArgs = inArrs.size();
|
|
auto x = inArrs[0];
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
X max = -DataTypeUtils::max<X>();
|
|
Z idx = static_cast<Z>(0);
|
|
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
X v = inArrs[i]->t<X>(e);
|
|
if (v > max) {
|
|
max = v;
|
|
idx = static_cast<Z>(i);
|
|
}
|
|
}
|
|
|
|
output.r<Z>(e) = static_cast<Z>(idx);
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, x->lengthOf());
|
|
}
|
|
|
|
void mergeMaxIndex(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
BUILD_DOUBLE_SELECTOR(inArrs[0]->dataType(), output.dataType(), mergeMaxIndex_, (inArrs, output), SD_NUMERIC_TYPES,
|
|
SD_INDEXING_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeMax_(const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
const sd::LongType numArgs = inArrs.size();
|
|
auto x = inArrs[0];
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
T max = -DataTypeUtils::max<T>();
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
T v = inArrs[i]->e<T>(e);
|
|
if (v > max) max = v;
|
|
}
|
|
output.p(e, max);
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, x->lengthOf());
|
|
}
|
|
|
|
void mergeMax(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
BUILD_SINGLE_SELECTOR(output.dataType(), mergeMax_, (inArrs, output), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeMaxBp_(const std::vector<NDArray*>& inArrs, std::vector<NDArray*>& outArrs) {
|
|
// outArrs.size() == inArrs.size() - 1
|
|
const sd::LongType numArgs = outArrs.size();
|
|
// last array is gradient
|
|
const auto gradient = inArrs[numArgs]->bufferAsT<T>();
|
|
auto length = inArrs[numArgs]->lengthOf();
|
|
|
|
auto gradShape = inArrs[numArgs]->shapeInfo();
|
|
std::vector<bool> vbSameShaepeAndStrides(numArgs);
|
|
std::vector<sd::LongType*> vShapePtrs(numArgs);
|
|
std::vector<sd::LongType*> vStridePtrs(numArgs);
|
|
std::vector<sd::LongType> vRanks(numArgs);
|
|
for (int i = 0; i < numArgs; ++i) {
|
|
vbSameShaepeAndStrides[i] = shape::haveSameShapeAndStrides(gradShape, inArrs[i]->shapeInfo());
|
|
vShapePtrs[i] = shape::shapeOf(inArrs[i]->shapeInfo());
|
|
vStridePtrs[i] = shape::stride(inArrs[i]->shapeInfo());
|
|
vRanks[i] = shape::rank(inArrs[i]->shapeInfo());
|
|
}
|
|
|
|
|
|
std::vector<sd::LongType *> outShapePtrs(numArgs);
|
|
std::vector<sd::LongType *> outStridePtrs(numArgs);
|
|
std::vector<sd::LongType> outRanks(numArgs);
|
|
for (int i = 0; i < numArgs; ++i) {
|
|
outShapePtrs[i] = shape::shapeOf(outArrs[i]->shapeInfo());
|
|
outStridePtrs[i] = shape::stride(outArrs[i]->shapeInfo());
|
|
outRanks[i] = shape::rank(outArrs[i]->shapeInfo());
|
|
}
|
|
|
|
sd::LongType gradRank = shape::rank(gradShape);
|
|
sd::LongType *gradShapeOf = shape::shapeOf(gradShape);
|
|
sd::LongType *gradStride = shape::stride(gradShape);
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
sd::LongType coords[SD_MAX_RANK];
|
|
for (auto e = start; e < stop; e++) {
|
|
INDEX2COORDS(e, gradRank, gradShapeOf, coords);
|
|
|
|
sd::LongType gradOffset;
|
|
COORDS2INDEX(gradRank,gradStride, coords, gradOffset);
|
|
|
|
T max = -DataTypeUtils::max<T>();
|
|
sd::LongType nMaxIndex = 0;
|
|
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
sd::LongType xOffset;
|
|
if (vbSameShaepeAndStrides[i]) {
|
|
xOffset = gradOffset;
|
|
} else {
|
|
COORDS2INDEX(vRanks[i],vStridePtrs[i], coords, xOffset);
|
|
}
|
|
const T* v = inArrs[i]->bufferAsT<T>();
|
|
if (v[xOffset] > max) {
|
|
max = v[xOffset];
|
|
nMaxIndex = i;
|
|
}
|
|
}
|
|
|
|
sd::LongType zOffset;
|
|
if (vbSameShaepeAndStrides[nMaxIndex]) {
|
|
zOffset = gradOffset;
|
|
} else {
|
|
COORDS2INDEX(outRanks[nMaxIndex],outStridePtrs[nMaxIndex], coords, zOffset);
|
|
}
|
|
|
|
T* z = outArrs[nMaxIndex]->bufferAsT<T>();
|
|
z[zOffset] = gradient[gradOffset];
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, length);
|
|
return;
|
|
}
|
|
|
|
void mergeMaxBp(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, std::vector<NDArray*>& outArrs) {
|
|
BUILD_SINGLE_SELECTOR(outArrs[0]->dataType(), mergeMaxBp_, (inArrs, outArrs), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeAvg_(const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
const sd::LongType numArgs = inArrs.size();
|
|
const T factor = static_cast<T>(1.f / numArgs);
|
|
auto x = inArrs[0];
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
T sum = static_cast<T>(0);
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
T v = inArrs[i]->e<T>(e);
|
|
sum += v;
|
|
}
|
|
output.p<T>(e, sum * factor);
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, x->lengthOf());
|
|
}
|
|
|
|
void mergeAvg(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
BUILD_SINGLE_SELECTOR(output.dataType(), mergeAvg_, (inArrs, output), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeAvgBp_(NDArray& gradient, std::vector<NDArray*>& outArrs) {
|
|
const sd::LongType numArgs = outArrs.size();
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
T v = gradient.e<T>(e) / numArgs;
|
|
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
outArrs[i]->p<T>(e, v);
|
|
}
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, gradient.lengthOf());
|
|
}
|
|
|
|
void mergeAvgBp(sd::LaunchContext* context, NDArray& gradient, std::vector<NDArray*>& outArrs) {
|
|
BUILD_SINGLE_SELECTOR(gradient.dataType(), mergeAvgBp_, (gradient, outArrs), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeAdd_(const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
const sd::LongType numArgs = inArrs.size();
|
|
auto x = inArrs[0];
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
T sum = (T)0.f;
|
|
for (sd::LongType i = 0; i < numArgs; i++) sum += inArrs[i]->e<T>(e);
|
|
|
|
output.p(e, sum);
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, x->lengthOf());
|
|
}
|
|
void mergeAdd(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output) {
|
|
BUILD_SINGLE_SELECTOR(output.dataType(), mergeAdd_, (inArrs, output), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void mergeAddBp_(NDArray& gradient, std::vector<NDArray*>& outArrs) {
|
|
const sd::LongType numArgs = outArrs.size();
|
|
|
|
auto func = PRAGMA_THREADS_FOR {
|
|
for (auto e = start; e < stop; e++) {
|
|
T v = gradient.e<T>(e);
|
|
|
|
for (sd::LongType i = 0; i < numArgs; i++) {
|
|
outArrs[i]->p<T>(e, v);
|
|
}
|
|
}
|
|
};
|
|
|
|
samediff::Threads::parallel_for(func, 0, gradient.lengthOf());
|
|
}
|
|
|
|
void mergeAddBp(sd::LaunchContext* context, NDArray& gradient, std::vector<NDArray*>& outArrs) {
|
|
BUILD_SINGLE_SELECTOR(gradient.dataType(), mergeAddBp_, (gradient, outArrs), SD_NUMERIC_TYPES);
|
|
}
|
|
|
|
} // namespace helpers
|
|
} // namespace ops
|
|
} // namespace sd
|
|
#endif |