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

88 lines
3.2 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), created on 07.03.2019
//
#include <ops/declarable/helpers/gather.h>
#include <numeric>
namespace nd4j {
namespace ops {
namespace helpers {
////////////////////////////////////////////////////////////////////////
void gather(nd4j::LaunchContext * context, const NDArray* input, const NDArray* indices, NDArray* output, const std::vector<int>& intArgs) {
int axis = intArgs.size() > 0 ? intArgs[0] : 0;
const int inputRank = input->rankOf();
if(axis < 0)
axis += inputRank;
const int numOfIntArgs = intArgs.size();
if (indices != nullptr) {
// first case: indices consist of only one scalar
if(indices->isScalar()) {
if(input->rankOf() <= 1){
//For scalar indices, rank 0 or 1 input: can't do tensor along dimension 0 as this is whole array... instead, we want to get a scalar
auto idx = indices->e<Nd4jLong>(0);
auto scalarNDArray = input->e(idx);
output->assign(scalarNDArray);
}
else {
NDArray inSubArr = (*input)(indices->e<Nd4jLong>(0), {axis});
output->assign(inSubArr);
}
}
else {
std::vector<int> dimsOut(indices->rankOf());
std::iota(dimsOut.begin(), dimsOut.end(), axis); // fill with axis, axis+1, ... axis+indices->rankOf()-1
const Nd4jLong numOfSubArrs = indices->lengthOf();
#pragma omp parallel for if(numOfSubArrs > Environment::getInstance()->elementwiseThreshold()) schedule(guided)
for(int i = 0; i < numOfSubArrs; ++i) {
NDArray subArrOut = (*output)(i, dimsOut);
NDArray subArrIn = (*input)(indices->e<Nd4jLong>(i), {axis});
subArrOut.assign(subArrIn);
}
}
}
else {
// we only allow scalar/vector case here
if (numOfIntArgs == 2) { // scalar case
output->assign((*input)(intArgs[1], {axis}));
}
else { // vector case
const Nd4jLong numOfSubArrs = intArgs.size() - 1;
#pragma omp parallel for if(numOfSubArrs > Environment::getInstance()->elementwiseThreshold()) schedule(guided)
for(int i = 0; i < numOfSubArrs; ++i) {
NDArray subArrOut = (*output)(i, {axis});
NDArray subArrIn = (*input)(intArgs[i+1], {axis});
subArrOut.assign(subArrIn);
}
}
}
}
}
}
}