79 lines
3.6 KiB
Plaintext
79 lines
3.6 KiB
Plaintext
/*******************************************************************************
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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 <array/ResultSet.h>
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#include <helpers/ShapeUtils.h>
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#include <numeric>
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#include <NDArrayFactory.h>
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#include <helpers/TAD.h>
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#include <exceptions/cuda_exception.h>
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#include <PointersManager.h>
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#include <ConstantTadHelper.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename X, typename Y>
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static _CUDA_G void scatterSimpleKernel(void *vx, Nd4jLong *xTadShape, Nd4jLong *xTadOffsets, Nd4jLong xLength, Nd4jLong numTads, void *vi, Nd4jLong *iShapeInfo, Nd4jLong iLength, void *vu, Nd4jLong *uShapeInfo, Nd4jLong uLength) {
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auto u = reinterpret_cast<X*>(vu);
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auto indices = reinterpret_cast<Y*>(vi);
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auto tid = threadIdx.x + blockIdx.x * blockDim.x;
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for (int i = tid; i < iLength; i += blockDim.x * gridDim.x) {
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auto x = reinterpret_cast<X*>(vx) + xTadOffsets[i];
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auto idx = indices[shape::getIndexOffset(i, iShapeInfo)];
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x[shape::getIndexOffset(idx, xTadShape)] = u[shape::getIndexOffset(i, uShapeInfo)];
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}
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}
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template <typename X, typename Y>
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void scatterSimple_(nd4j::LaunchContext * context, const int opId, NDArray& input, const NDArray& updates, const NDArray& indices, const std::vector<int>& dimensions) {
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auto dims = ShapeUtils::evalDimsToExclude(input.rankOf(), dimensions);
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auto packX = ConstantTadHelper::getInstance()->tadForDimensions(input.getShapeInfo(), dims);
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auto xLength = shape::length(packX.primaryShapeInfo());
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auto iLength = indices.lengthOf();
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auto uLength = updates.lengthOf();
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scatterSimpleKernel<X,Y><<<256, 256, 1024, *context->getCudaStream()>>>(input.getSpecialBuffer(), packX.platformShapeInfo(), packX.platformOffsets(), xLength, packX.numberOfTads(), indices.getSpecialBuffer(), indices.getSpecialShapeInfo(), iLength, updates.getSpecialBuffer(), updates.getSpecialShapeInfo(), uLength);
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}
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void scatterSimple(nd4j::LaunchContext * context, const int opId, NDArray& input, const NDArray& updates, const NDArray& indices, const std::vector<int>& dimensions) {
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auto xType = input.dataType();
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auto yType = indices.dataType();
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if (opId != 6)
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throw std::runtime_error("scatterSimple: only copy op is supported");
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NDArray::prepareSpecialUse({&input}, {&updates, &indices});
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BUILD_DOUBLE_SELECTOR(xType, yType, scatterSimple_, (context, opId, input, updates, indices, dimensions), LIBND4J_TYPES, INDEXING_TYPES);
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NDArray::registerSpecialUse({&input}, {&updates, &indices});
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}
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}
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}
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} |