112 lines
4.4 KiB
Plaintext
112 lines
4.4 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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// Created by Yurii Shyrma on 02.01.2018
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//
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#include <ops/declarable/helpers/stack.h>
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#include <helpers/ShapeUtils.h>
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#include <array/ResultSet.h>
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#include <cuda_exception.h>
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#include <TAD.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 T>
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static __global__ void stackKernel(void** inputList, void** inputShapeList, int inputListLength, Nd4jLong arrLen, void* vz, const Nd4jLong* zShapeInfo, Nd4jLong* tadShape, Nd4jLong *tadOffsets) {
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T* z = reinterpret_cast<T*>(vz);
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if(tadShape == nullptr) { // scalar case
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for (Nd4jLong i = blockIdx.x * blockDim.x + threadIdx.x; i < inputListLength; i += gridDim.x * blockDim.x)
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z[shape::getIndexOffset(i, zShapeInfo, inputListLength)] = reinterpret_cast<T*>(inputList[i])[0];
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}
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else {
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for (int t = blockIdx.x; t < inputListLength; t += gridDim.x) {
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auto tZ = z + tadOffsets[t];
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auto tX = reinterpret_cast<T*>(inputList[t]);
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auto xShapeInfo = reinterpret_cast<Nd4jLong*>(inputShapeList[t]);
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for (int e = threadIdx.x; e < arrLen; e += blockDim.x)
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tZ[shape::getIndexOffset(e, tadShape, arrLen)] = tX[shape::getIndexOffset(e, xShapeInfo, arrLen)];
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}
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}
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}
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///////////////////////////////////////////////////////////////////
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template <typename T>
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static void stack_(nd4j::LaunchContext * context, const std::vector<const NDArray*>& inArrs, NDArray* outArr, const int dim) {
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const bool scalarCase = inArrs[0]->isScalar();
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const int threadsPerBlock = MAX_NUM_THREADS / 2;
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const int blocksPerGrid = scalarCase ? (outArr->lengthOf() + threadsPerBlock - 1) / threadsPerBlock : inArrs.size();
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NDArray::prepareSpecialUse({outArr}, {});
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// FIXME: !!!
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for (auto v:inArrs)
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NDArray::prepareSpecialUse({}, {v});
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std::vector<void const*> inputList(inArrs.size());
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std::vector<Nd4jLong const*> inputShapeList(inArrs.size());
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for (size_t i = 0; i < inputList.size(); ++i) {
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inputList[i] = inArrs[i]->getSpecialBuffer();
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inputShapeList[i] = inArrs[i]->getSpecialShapeInfo();
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}
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PointersManager manager(context, "helpers::stack");
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auto dInBuffers = (void **) manager.replicatePointer(inputList.data(), inputList.size() * sizeof(Nd4jLong*));
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auto dInShapeInfo = (void **) manager.replicatePointer(inputShapeList.data(), inputShapeList.size() * sizeof(Nd4jLong*));
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if(scalarCase) {
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stackKernel<T><<<blocksPerGrid, threadsPerBlock, 1024, *context->getCudaStream()>>>((void**)dInBuffers, (void**)dInShapeInfo, inputList.size(), inArrs[0]->lengthOf(), outArr->specialBuffer(), outArr->getSpecialShapeInfo(), nullptr, nullptr);
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}
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else {
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std::vector<int> axis = ShapeUtils::evalDimsToExclude(outArr->rankOf(), {dim});
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auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(outArr->getShapeInfo(), axis);
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stackKernel<T><<<blocksPerGrid, threadsPerBlock, 1024, *context->getCudaStream()>>>((void**)dInBuffers, (void**)dInShapeInfo, inputList.size(), inArrs[0]->lengthOf(), outArr->specialBuffer(), nullptr, packZ.specialShapeInfo(), packZ.specialOffsets());
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}
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manager.synchronize();
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NDArray::registerSpecialUse({outArr}, {});
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// FIXME: !!!
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for (auto v:inArrs)
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NDArray::registerSpecialUse({}, {v});
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}
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void stack(nd4j::LaunchContext * context, const std::vector<const NDArray*>& inArrs, NDArray* outArr, const int dim) {
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BUILD_SINGLE_SELECTOR(outArr->dataType(), stack_, (context, inArrs, outArr, dim), LIBND4J_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void stack_ , (nd4j::LaunchContext * context, const std::vector<const NDArray*>& inArrs, NDArray* outArr, const int dim), LIBND4J_TYPES);
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}
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}
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}
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