116 lines
4.0 KiB
C++
116 lines
4.0 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 20.04.2018
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//
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#include <ops/declarable/helpers/transforms.h>
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#include <helpers/ShapeUtils.h>
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#include <helpers/Loops.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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//////////////////////////////////////////////////////////////////////////
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void scatterUpdate(sd::LaunchContext * context, NDArray& input, NDArray& updates, const std::vector<int>* intArgs) {
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int opCode = (*intArgs)[0];
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int dimSize = (*intArgs)[1];
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Nd4jLong e;
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Nd4jLong limg = 2 + dimSize;
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std::vector<int> tadDimensions(dimSize);
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for (e = 2; e < limg; e++)
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tadDimensions[e-2] = (*intArgs)[e];
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std::vector<int> dimsToExclude = ShapeUtils::evalDimsToExclude(input.rankOf(), tadDimensions);
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// increasing counter to skip numIndices
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e++;
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std::vector<int> indices;
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for (; e < static_cast<Nd4jLong>(intArgs->size()); e++)
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indices.push_back((*intArgs)[e]);
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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auto inSubArr = input(indices[i], dimsToExclude, true);
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auto updSubArr = updates(i, dimsToExclude, true);
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if (inSubArr.lengthOf() != updSubArr.lengthOf())
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continue;
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switch (opCode) {
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case 0:
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inSubArr.applyPairwiseTransform(pairwise::Add, updSubArr, inSubArr);
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break;
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case 1:
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inSubArr.applyPairwiseTransform(pairwise::Subtract, updSubArr, inSubArr);
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break;
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case 2:
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inSubArr.applyPairwiseTransform(pairwise::Multiply, updSubArr, inSubArr);
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break;
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case 3:
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inSubArr.applyPairwiseTransform(pairwise::Divide, updSubArr, inSubArr);
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break;
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case 4:
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inSubArr.applyPairwiseTransform(pairwise::ReverseSubtract, updSubArr, inSubArr);
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break;
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case 5:
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inSubArr.applyPairwiseTransform(pairwise::ReverseDivide, updSubArr, inSubArr);
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break;
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case 6:
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inSubArr.applyPairwiseTransform(pairwise::CopyPws, updSubArr, inSubArr);
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break;
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default:
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continue;
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}
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}
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};
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samediff::Threads::parallel_tad(func, 0, indices.size());
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}
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//////////////////////////////////////////////////////////////////////////
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void scatterSimple(sd::LaunchContext * context, const int opId, NDArray& input, const NDArray& updates, const NDArray& indices, const std::vector<int>& dimensions) {
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// updates and indices have same length
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const Nd4jLong len = indices.lengthOf();
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switch (opId) {
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case 6: { // copy
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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auto inSubArr = input(i, dimensions);
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inSubArr.p(indices.t<Nd4jLong>(i), updates.e(i));
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}
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};
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samediff::Threads::parallel_for(func, 0, len);
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}
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break;
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default:
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throw std::invalid_argument("helpers::scatterSimple: operation is not implemented for given id !");
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}
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}
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}
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}
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}
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