cavis/libnd4j/include/ops/declarable/helpers/cpu/stack.cpp

124 lines
4.8 KiB
C++

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