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

127 lines
4.6 KiB
C++
Raw Normal View History

Backpropagation implementation of mergemax, mergeadd and mergeavg ops (#343) * libnd4j: first step of merge_max implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed typos Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some corrections for mergeMaxBp Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some minor corrections Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j test added for mergemax_bp Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed several problems tests added, check with gradCheck Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j remove duplicated tests Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j split implementation of transforms ops into separate file implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j code clean up, added mergeavg_bp and mergeadd_bp, need testing Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j merge master, fixed typos and added tests Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some minor fixes Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j added helper for mergeAddBp operation, this permits to skip nullify Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j file renaming changes and cuda some corrections, need some additional corrections Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some additional corrections for merge ops Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j more corrections per request for cuda more proper usage Signed-off-by: Oleg <oleg.semeniv@gmail.com>
2020-03-25 06:40:30 +01:00
/*******************************************************************************
* 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), created on 20.04.2018
//
#include <ops/declarable/helpers/transforms.h>
#include <helpers/Loops.h>
#include <graph/RandomGenerator.h>
#include <numeric>
#include <helpers/ShapeUtils.h>
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
template <typename T>
void randomShuffle_(NDArray& input, NDArray& output, sd::graph::RandomGenerator& rng, const bool isInplace) {
// check edge cases first
int temp;
const int firstDim = input.sizeAt(0);
if(input.lengthOf() == 1 || firstDim == 1) {
if(!isInplace)
output.assign(input);
}
else if (input.isVector() || shape::isLikeVector(input.getShapeInfo(), temp)) {
// apply Fisher-Yates shuffle
if(isInplace) {
//PRAGMA_OMP_PARALLEL_FOR_IF((firstDim-1) > Environment::getInstance()->tadThreshold())
for(int i = firstDim-1; i > 0; --i) {
int r = rng.relativeInt(i) % i;
if(i == r)
continue;
T t0 = input.t<T>(i);
T t1 = input.t<T>(r);
//math::nd4j_swap<T>(input(i), input(r));
input.t<T>(i) = t1;
input.t<T>(r) = t0;
}
}
else {
std::vector<int> indices(firstDim);
std::iota(indices.begin(), indices.end(), 0);
output.p<T>(Nd4jLong(0), input.e<T>(0));
// FIXME: parallelism!!
for(int i = firstDim-1; i > 0; --i) {
int r = rng.relativeInt(i) % i;
output.t<T>(i) = input.t<T>(indices[r]);
if(i == r)
continue;
output.t<T>(r) = input.t<T>(indices[i]);
math::nd4j_swap<int>(indices[i], indices[r]);
}
rng.rewindH(firstDim-1);
}
}
else {
// evaluate sub-arrays list of input array through all dimensions excluding first one
std::vector<int> dimensions = ShapeUtils::evalDimsToExclude(input.rankOf(), {0});
auto subArrsListIn = input.allTensorsAlongDimension(dimensions);
// apply Fisher-Yates shuffle
if(isInplace) {
//PRAGMA_OMP_PARALLEL_FOR_IF((firstDim-1) > Environment::getInstance()->elementwiseThreshold())
for(int i = firstDim - 1; i > 0; --i) {
int r = rng.relativeInt(i) % i;
if(i == r)
continue;
subArrsListIn.at(i)->swapUnsafe(*subArrsListIn.at(r));
}
}
else {
// evaluate sub-arrays list of output array through all dimensions excluding first one
auto subArrsListOut = output.allTensorsAlongDimension(dimensions);
std::vector<int> indices(firstDim);
std::iota(indices.begin(), indices.end(), 0);
bool isZeroShuffled = false;
//PRAGMA_OMP_PARALLEL_FOR_IF((firstDim-1) > Environment::getInstance()->tadThreshold())
for(int i = firstDim - 1; i > 0; --i) {
int r = rng.relativeInt(i) % i;
subArrsListOut.at(i)->assign(subArrsListIn.at(indices[r]));
if(r == 0)
isZeroShuffled = true;
if(i == r)
continue;
subArrsListOut.at(r)->assign(subArrsListIn.at(indices[i]));
math::nd4j_swap<int>(indices[i], indices[r]);
}
if(!isZeroShuffled)
subArrsListOut.at(0)->assign(subArrsListIn.at(0));
}
rng.rewindH(firstDim-1);
}
}
void randomShuffle(sd::LaunchContext * context, NDArray& input, NDArray& output, sd::graph::RandomGenerator& rng, const bool isInplace) {
BUILD_SINGLE_SELECTOR(input.dataType(), randomShuffle_, (input, output, rng, isInplace), LIBND4J_TYPES);
}
}
}
}