124 lines
4.8 KiB
C++
124 lines
4.8 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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 <ops/declarable/helpers/stack.h>
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#include <helpers/ShapeUtils.h>
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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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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_(const std::vector<const NDArray*>& inArrs, NDArray& output, const int dim) {
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const int numOfSubArrs = inArrs.size();
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if(inArrs[0]->rankOf() == 0) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++)
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output.p<T>(i, inArrs[i]->t<T>(0));
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};
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sd::Threads::parallel_for(func, 0, numOfSubArrs);
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}
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else {
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auto zTadPack = ConstantTadHelper::getInstance()->tadForDimensions(output.getShapeInfo(), ShapeUtils::evalDimsToExclude(output.rankOf(), {dim}));
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Nd4jLong* zTadShapeInfo = zTadPack.primaryShapeInfo();
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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(inArrs[0]->getContext(), transform::Assign,
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inArrs[i]->getBuffer(), inArrs[i]->getShapeInfo(), nullptr/*input specialBuffer*/, nullptr/*input specialShapeInfo*/,
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zBuff, zTadShapeInfo, nullptr/*output specialBuffer*/, nullptr/*output specialShapeInfo*/,
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nullptr, nullptr, nullptr, false/*allowParallelism*/);
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}
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};
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sd::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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////////////////////////////////////////////////////////////////////////
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void stack(sd::LaunchContext * context, const std::vector<const NDArray*>& inArrs, NDArray& output, const int dim) {
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BUILD_SINGLE_SELECTOR(output.dataType(), stack_, (inArrs, output, dim), LIBND4J_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void stack_ , (const std::vector<const NDArray*>& inArrs, NDArray& output, const int dim), LIBND4J_TYPES);
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///////////////////////////////////////////////////////////////////
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template <typename T>
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static void unstack_(const 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++)
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outArrs[i]->p<T>(0, input.t<T>(i));
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};
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sd::Threads::parallel_for(func, 0, numOfSubArrs);
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}
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else {
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auto xTadPack = ConstantTadHelper::getInstance()->tadForDimensions(input.getShapeInfo(), ShapeUtils::evalDimsToExclude(input.rankOf(), {dim}));
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Nd4jLong* xTadShapeInfo = xTadPack.primaryShapeInfo();
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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* xBuff = input.bufferWithOffset(xTadPack.primaryOffsets()[i]);
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NativeOpExecutioner::execTransformAny(input.getContext(), transform::Assign,
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xBuff, xTadShapeInfo, nullptr/*input specialBuffer*/, nullptr/*input specialShapeInfo*/,
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outArrs[i]->getBuffer(), outArrs[i]->getShapeInfo(), nullptr/*output specialBuffer*/, nullptr/*output specialShapeInfo*/,
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nullptr, nullptr, nullptr, false/*allowParallelism*/);
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}
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};
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sd::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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////////////////////////////////////////////////////////////////////////
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void unstack(sd::LaunchContext* context, const NDArray& input, const std::vector<NDArray*>& outArrs, const int dim) {
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BUILD_SINGLE_SELECTOR(input.dataType(), unstack_, (input, outArrs, dim), LIBND4J_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void unstack_, (const NDArray& input, const std::vector<NDArray*>& outArrs, const int dim), LIBND4J_TYPES);
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}
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}
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}
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