98 lines
3.3 KiB
C++
98 lines
3.3 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), created on 07.03.2019
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//
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#include <ops/declarable/helpers/gather.h>
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#include <numeric>
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#include <execution/Threads.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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////////////////////////////////////////////////////////////////////////
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void gather(nd4j::LaunchContext * context, const NDArray* input, const NDArray* indices, NDArray* output, const std::vector<int>& intArgs) {
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int axis = intArgs.size() > 0 ? intArgs[0] : 0;
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const int inputRank = input->rankOf();
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if(axis < 0)
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axis += inputRank;
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const int numOfIntArgs = intArgs.size();
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if (indices != nullptr) {
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// first case: indices consist of only one scalar
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if(indices->isScalar()) {
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if(input->rankOf() <= 1){
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//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
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auto idx = indices->e<Nd4jLong>(0);
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auto scalarNDArray = input->e(idx);
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output->assign(scalarNDArray);
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}
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else {
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NDArray inSubArr = (*input)(indices->e<Nd4jLong>(0), {axis});
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output->assign(inSubArr);
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}
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}
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else {
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std::vector<int> dimsOut(indices->rankOf());
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std::iota(dimsOut.begin(), dimsOut.end(), axis); // fill with axis, axis+1, ... axis+indices->rankOf()-1
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const Nd4jLong numOfSubArrs = indices->lengthOf();
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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NDArray subArrOut = (*output)(i, dimsOut);
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NDArray subArrIn = (*input)(indices->e<Nd4jLong>(i), {axis});
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subArrOut.assign(subArrIn);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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else {
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// we only allow scalar/vector case here
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if (numOfIntArgs == 2) { // scalar case
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output->assign((*input)(intArgs[1], {axis}));
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}
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else { // vector case
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const Nd4jLong numOfSubArrs = intArgs.size() - 1;
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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NDArray subArrOut = (*output)(i, {axis});
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NDArray subArrIn = (*input)(intArgs[i + 1], {axis});
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subArrOut.assign(subArrIn);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfSubArrs);
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}
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}
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}
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}
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}
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}
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