wehub-resource-sync
120 lines
4.9 KiB
C++
120 lines
4.9 KiB
C++
/* ******************************************************************************
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*
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#include <array/ResultSet.h>
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#include <execution/Threads.h>
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#include <helpers/ConstantTadHelper.h>
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#include <helpers/ShapeUtils.h>
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#include <ops/declarable/helpers/stack.h>
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#include <legacy/NativeOpExecutioner.h>
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#if NOT_EXCLUDED(OP_stack)
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namespace sd {
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namespace ops {
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namespace helpers {
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///////////////////////////////////////////////////////////////////
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template <typename T>
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static void stack_(LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output, const int dim) {
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const int numOfSubArrs = inArrs.size();
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//no op on empty
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if (inArrs[0]->rankOf() == 0 && !inArrs[0]->isEmpty()) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) if(!output.isEmpty() && !inArrs[i]->isEmpty()) output.p<T>(i, inArrs[i]->t<T>(0));
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};
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samediff::Threads::parallel_for(func, 0, numOfSubArrs);
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} else if(!output.isEmpty()) {
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std::vector<sd::LongType> dimVec = {dim};
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auto vec = ShapeUtils::evalDimsToExclude(output.rankOf(),1,dimVec.data());
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auto zTadPack = ConstantTadHelper::getInstance().tadForDimensions(
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output.shapeInfo(), vec);
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auto zTadShapeInfo = zTadPack->primaryShapeInfo();
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delete vec;
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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void* zBuff = output.bufferWithOffset(zTadPack->primaryOffsets()[i]);
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NativeOpExecutioner::execTransformAny(
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inArrs[0]->getContext(), transform::Assign, inArrs[i]->buffer(), inArrs[i]->shapeInfo(),
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nullptr /*input specialBuffer*/, nullptr /*input special*/, zBuff, zTadShapeInfo,
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nullptr /*output specialBuffer*/, nullptr /*output special*/, nullptr, false /*allowParallelism*/);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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////////////////////////////////////////////////////////////////////////
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void stack(LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output, const int dim) {
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BUILD_SINGLE_SELECTOR(output.dataType(), stack_, (context, inArrs, output, dim), SD_COMMON_TYPES);
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}
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BUILD_SINGLE_TEMPLATE( void stack_,
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(LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output, const int dim),
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SD_COMMON_TYPES);
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///////////////////////////////////////////////////////////////////
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template <typename T>
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static void unstack_(LaunchContext* context, NDArray& input, const std::vector<NDArray*>& outArrs, const int dim) {
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const int numOfSubArrs = outArrs.size();
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if (outArrs[0]->rankOf() == 0) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) outArrs[i]->p<T>(0, input.t<T>(i));
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};
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samediff::Threads::parallel_for(func, 0, numOfSubArrs);
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} else {
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std::vector<sd::LongType> dimVec = {dim};
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auto vec = ShapeUtils::evalDimsToExclude(input.rankOf(), 1,dimVec.data());
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auto xTadPack = ConstantTadHelper::getInstance().tadForDimensions(
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input.shapeInfo(), vec);
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auto xTadShapeInfo = xTadPack->primaryShapeInfo();
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delete vec;
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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auto xBuff = input.bufferWithOffset(xTadPack->primaryOffsets()[i]);
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NativeOpExecutioner::execTransformAny(
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input.getContext(), transform::Assign, xBuff, xTadShapeInfo, nullptr /*input specialBuffer*/,
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nullptr /*input special*/, outArrs[i]->buffer(), outArrs[i]->shapeInfo(), nullptr /*output specialBuffer*/,
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nullptr /*output special*/, nullptr, false /*allowParallelism*/);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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////////////////////////////////////////////////////////////////////////
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void unstack(LaunchContext* context, NDArray& input, const std::vector<NDArray*>& outArrs, const int dim) {
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BUILD_SINGLE_SELECTOR(input.dataType(), unstack_, (context, input, outArrs, dim), SD_COMMON_TYPES);
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}
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BUILD_SINGLE_TEMPLATE( void unstack_,
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(LaunchContext* context, NDArray& input, const std::vector<NDArray*>& outArrs, const int dim),
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SD_COMMON_TYPES);
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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#endif |