cavis/libnd4j/include/loops/cpu/indexreduce.cpp

158 lines
5.8 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
******************************************************************************/
//
// Created by raver on 4/9/2018.
//
#include "../indexreduce.h"
#include <op_boilerplate.h>
#include <Loops.h>
#include <types/types.h>
#include <helpers/ConstantTadHelper.h>
#include "../legacy_ops.h"
using namespace simdOps;
namespace functions {
namespace indexreduce {
////////////////////////////////////////////////////////////////////////
template <typename X, typename Y>
Nd4jLong IndexReduce<X,Y>::execScalar( const int opNum, void *x, Nd4jLong *xShapeInfo, void *extraParams) {
RETURNING_DISPATCH_BY_OPNUM_TT(execScalar, PARAMS(x, xShapeInfo, extraParams), INDEX_REDUCE_OPS);
}
////////////////////////////////////////////////////////////////////////
template <typename X, typename Y>
void IndexReduce<X,Y>::exec(const int opNum,
void *x, Nd4jLong *xShapeInfo,
void *extraParams,
void *z, Nd4jLong *zShapeInfo,
int *dimension, int dimensionLength,
Nd4jLong *tadShapeInfo, Nd4jLong *tadOffset) {
DISPATCH_BY_OPNUM_TT(exec, PARAMS(x, xShapeInfo, extraParams, z, zShapeInfo, dimension, dimensionLength, tadShapeInfo, tadOffset), INDEX_REDUCE_OPS);
}
////////////////////////////////////////////////////////////////////////
template <typename X, typename Y>
template<typename OpType>
Nd4jLong IndexReduce<X, Y>::execScalar(void *vx, Nd4jLong *xShapeInfo, void *vextraParams) {
auto x = reinterpret_cast<X *>(vx);
auto extraParams = reinterpret_cast<X *>(vextraParams);
//T startingVal = OpType::startingValue(x);
auto startingIndex = OpType::startingIndexValue(x);
auto len = shape::length(xShapeInfo);
auto xEws = shape::elementWiseStride(xShapeInfo);
nd4j::OmpLaunchHelper info(len);
uint xShapeInfoCast[MAX_RANK];
bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
if (xEws == 1) {
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto local = OpType::startingIndexValue(x);
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = info.getItersPerThread(threadNum);
for (Nd4jLong i = 0; i < ulen; i++) {
IndexValue<X> curr(x[i + threadOffset], i + threadOffset);
local = OpType::update(local, curr, extraParams);
}
PRAGMA_OMP_CRITICAL
startingIndex = OpType::update(startingIndex, local, extraParams);
}
} else {
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto local = OpType::startingIndexValue(x);
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = info.getItersPerThread(threadNum);
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(threadOffset + i, xShapeInfo, xShapeInfoCast, len, canCastX);
IndexValue<X> curr(x[offset], threadOffset + i);
local = OpType::update(local, curr, extraParams);
}
PRAGMA_OMP_CRITICAL
startingIndex = OpType::update(startingIndex, local, extraParams);
}
}
return startingIndex.index;
}
////////////////////////////////////////////////////////////////////////
template <typename X, typename Z>
template<typename OpType>
void IndexReduce<X, Z>::exec(void *vx, Nd4jLong *xShapeInfo,
void *vextraParams,
void *vz, Nd4jLong *zShapeInfo,
int *dimension, int dimensionLength,
Nd4jLong *tadShapeInfo, Nd4jLong *tadOffset) {
auto x = reinterpret_cast<X *>(vx);
auto z = reinterpret_cast<Z *>(vz);
auto extraParams = reinterpret_cast<X *>(vextraParams);
const Nd4jLong zLen = shape::length(zShapeInfo);
if(nd4j::ArrayOptions::arrayType(xShapeInfo) == nd4j::ArrayType::EMPTY) {
if(nd4j::ArrayOptions::arrayType(zShapeInfo) == nd4j::ArrayType::EMPTY)
return;
const auto indexValue = OpType::startingIndexValue(x);
PRAGMA_OMP_PARALLEL_FOR_IF(zLen > nd4j::Environment::getInstance()->elementwiseThreshold())
for (uint i = 0; i < zLen; i++)
z[i] = (Z) indexValue.index;;
return;
}
if(shape::isScalar(zShapeInfo)) {
z[0] = (Z) execScalar<OpType>(x,xShapeInfo,extraParams);
return;
}
auto tadOnlyShapeInfo = tadShapeInfo;
Nd4jLong *tadOffsets = tadOffset;
if (tadOnlyShapeInfo == nullptr || tadOffsets == nullptr) {
if (dimensionLength < 1)
return;
auto tadPack = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(xShapeInfo, dimension, dimensionLength);
tadOnlyShapeInfo = tadPack.primaryShapeInfo();
tadOffsets = tadPack.primaryOffsets();
}
nd4j::IndexReductionLoops<X,Z>::template loopIndexReduce<OpType>(x, xShapeInfo, z, zShapeInfo, tadOnlyShapeInfo, tadOffsets, extraParams);
}
BUILD_DOUBLE_TEMPLATE(template class ND4J_EXPORT IndexReduce, , LIBND4J_TYPES, INDEXING_TYPES);
}
}