* RL4J: Add generic update rule (#502) Signed-off-by: Alexandre Boulanger <aboulang2002@yahoo.com> * Shyrma reduce (#481) * - start working on improving of cpu legacy code for reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on improving legacy loops Signed-off-by: Yurii <iuriish@yahoo.com> * - still working on improving reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on improving reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - testing speed run of new reduce op Signed-off-by: Yurii <iuriish@yahoo.com> * - working on improvement of default loop for reduce op Signed-off-by: Yurii <iuriish@yahoo.com> * - update signatures of stuff which calls reduce ops Signed-off-by: Yurii <iuriish@yahoo.com> * - make corrections in cuda reduce kernels Signed-off-by: Yurii <iuriish@yahoo.com> * - change loop for default case in broadcast legacy ops Signed-off-by: Yurii <iuriish@yahoo.com> * - comment some shape stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - comment unnecessary prints in RNGtests Signed-off-by: Yurii <iuriish@yahoo.com> * - finish to resolve conflicts after master has been merged Signed-off-by: Yurii <iuriish@yahoo.com> * - get rid of some compilation mistakes of cuda stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - minor changes Signed-off-by: Yurii <iuriish@yahoo.com> * - further search for bug causing crash on java test Signed-off-by: Yurii <iuriish@yahoo.com> * - add scalar case in reduce_ ... exec stuff Signed-off-by: Yurii <iuriish@yahoo.com> * - minor corrections in NAtiveOps.cu Signed-off-by: Yurii <iuriish@yahoo.com> * - add switch to scalar case execReduceXD functions Signed-off-by: Yurii <iuriish@yahoo.com> * - add support for vectors old shape in ConstantShapeHelper::createShapeInfoWithNoUnitiesForReduce Signed-off-by: Yurii <iuriish@yahoo.com> * - correct cuda mirrorPad Signed-off-by: Yurii <iuriish@yahoo.com> * - add support for vectors old shape in cuda createShapeInfoWithNoUnitiesForReduce Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: raver119 <raver119@gmail.com> * Add support for CUDA 11.0 (#492) * Add support for CUDA 11.0 * libnd4j tweaks for CUDA 11 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * bindings update, again? Signed-off-by: raver119@gmail.com <raver119@gmail.com> * * Update versions of JavaCPP Presets for FFmpeg, OpenBLAS, and NumPy * update API to match CUDA 8 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * * Update version of JavaCPP Presets for CPython * C++ updated for cuDNN 8.0 Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * 128-bit alignment for workspaces Signed-off-by: raver119@gmail.com <raver119@gmail.com> * change seed in 1 test Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fix dependecy duplication in python4j-parent pom * Fix group id for in python4j-numpy * few tests tweaked Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Remove macosx-x86_64-gpu from nd4j-tests-tensorflow * few minor tweaks for IndexReduce Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one test removed Signed-off-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: Serhii Shepel <9946053+sshepel@users.noreply.github.com> * RL4J: Add SyncTrainer and AgentLearnerBuilder for a few algorithms (#504) Signed-off-by: Alexandre Boulanger <aboulang2002@yahoo.com> Co-authored-by: Alexandre Boulanger <44292157+aboulang2002@users.noreply.github.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com> Co-authored-by: raver119 <raver119@gmail.com> Co-authored-by: Serhii Shepel <9946053+sshepel@users.noreply.github.com>
225 lines
9.1 KiB
Plaintext
225 lines
9.1 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 raver119@gmail.com
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//
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#include "../ConstantShapeHelper.h"
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#include <exceptions/cuda_exception.h>
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#include <array/ShapeDescriptor.h>
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#include <helpers/ShapeBuilders.h>
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#include <execution/AffinityManager.h>
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#include <helpers/ConstantHelper.h>
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#include <helpers/ShapeUtils.h>
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#include <array/PrimaryPointerDeallocator.h>
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#include <array/CudaPointerDeallocator.h>
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namespace sd {
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ConstantShapeHelper::ConstantShapeHelper() {
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auto numDevices = AffinityManager::numberOfDevices();
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_cache.resize(numDevices);
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for (int e = 0; e < numDevices; e++) {
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MAP_IMPL<ShapeDescriptor, ConstantShapeBuffer> cache;
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_cache[e] = cache;
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}
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}
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ConstantShapeHelper& ConstantShapeHelper::getInstance() {
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static ConstantShapeHelper instance;
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return instance;
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}
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ConstantShapeBuffer& ConstantShapeHelper::bufferForShapeInfo(sd::DataType dataType, char order, const std::vector<Nd4jLong> &shape) {
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ShapeDescriptor descriptor(dataType, order, shape);
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return bufferForShapeInfo(descriptor);
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}
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ConstantShapeBuffer& ConstantShapeHelper::bufferForShapeInfo(const sd::DataType dataType, const char order, const int rank, const Nd4jLong* shape) {
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ShapeDescriptor descriptor(dataType, order, shape, rank);
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return bufferForShapeInfo(descriptor);
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}
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ConstantShapeBuffer& ConstantShapeHelper::bufferForShapeInfo(const ShapeDescriptor &descriptor) {
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int deviceId = AffinityManager::currentDeviceId();
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std::lock_guard<std::mutex> lock(_mutex);
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if (_cache[deviceId].count(descriptor) == 0) {
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auto hPtr = std::make_shared<PointerWrapper>(descriptor.toShapeInfo(), std::make_shared<PrimaryPointerDeallocator>());
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auto dPtr = std::make_shared<PointerWrapper>(ConstantHelper::getInstance().replicatePointer(hPtr->pointer(), shape::shapeInfoByteLength(hPtr->pointerAsT<Nd4jLong>())), std::make_shared<CudaPointerDeallocator>());
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ConstantShapeBuffer buffer(hPtr, dPtr);
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ShapeDescriptor descriptor1(descriptor);
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_cache[deviceId][descriptor1] = buffer;
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return _cache[deviceId][descriptor1];
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} else {
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return _cache[deviceId].at(descriptor);
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}
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}
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ConstantShapeBuffer& ConstantShapeHelper::bufferForShapeInfo(const Nd4jLong *shapeInfo) {
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ShapeDescriptor descriptor(shapeInfo);
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return bufferForShapeInfo(descriptor);
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}
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bool ConstantShapeHelper::checkBufferExistenceForShapeInfo(ShapeDescriptor &descriptor) {
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auto deviceId = AffinityManager::currentDeviceId();
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std::lock_guard<std::mutex> lock(_mutex);
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return _cache[deviceId].count(descriptor) != 0;
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}
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Nd4jLong const* ConstantShapeHelper::createShapeInfo(const sd::DataType dataType, const char order, const int rank, const Nd4jLong* shape) {
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ShapeDescriptor descriptor(dataType, order, shape, rank);
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::createShapeInfo(const sd::DataType dataType, const Nd4jLong* shapeInfo) {
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return ConstantShapeHelper::createShapeInfo(dataType, shape::order(shapeInfo), shape::rank(shapeInfo), shape::shapeOf(const_cast<Nd4jLong*>(shapeInfo)));
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}
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Nd4jLong const* ConstantShapeHelper::emptyShapeInfo(const sd::DataType dataType) {
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auto descriptor = ShapeDescriptor::emptyDescriptor(dataType);
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::scalarShapeInfo(const sd::DataType dataType) {
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auto descriptor = ShapeDescriptor::scalarDescriptor(dataType);
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::vectorShapeInfo(const Nd4jLong length, const sd::DataType dataType) {
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auto descriptor = ShapeDescriptor::vectorDescriptor(length, dataType);
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::createShapeInfo(const sd::DataType dataType, const char order, const std::vector<Nd4jLong> &shape) {
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ShapeDescriptor descriptor(dataType, order, shape);
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::createShapeInfo(const ShapeDescriptor &descriptor) {
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return bufferForShapeInfo(descriptor).primary();
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}
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Nd4jLong const* ConstantShapeHelper::createFromExisting(Nd4jLong *shapeInfo, bool destroyOriginal) {
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ShapeDescriptor descriptor(shapeInfo);
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auto result = createShapeInfo(descriptor);
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if (destroyOriginal)
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RELEASE(shapeInfo, nullptr);
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return result;
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}
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Nd4jLong const* ConstantShapeHelper::createFromExisting(Nd4jLong *shapeInfo, sd::memory::Workspace *workspace) {
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ShapeDescriptor descriptor(shapeInfo);
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auto result = createShapeInfo(descriptor);
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RELEASE(shapeInfo, workspace);
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return result;
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}
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////////////////////////////////////////////////////////////////////////
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ConstantShapeBuffer& ConstantShapeHelper::createShapeInfoWithUnitiesForBroadcast(const Nd4jLong* maxShapeInfo, const Nd4jLong* minShapeInfo, sd::memory::Workspace* workspace, const std::vector<int>& dimensions) {
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Nd4jLong* newShapeInfo = nullptr;
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ALLOCATE(newShapeInfo, workspace, shape::shapeInfoLength(shape::rank(maxShapeInfo)), Nd4jLong);
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newShapeInfo[0] = shape::rank(maxShapeInfo);
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sd::ArrayOptions::copyDataType(newShapeInfo, minShapeInfo); // type
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newShapeInfo[2 * newShapeInfo[0] + 2] = shape::elementWiseStride(minShapeInfo); // ews
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newShapeInfo[2 * newShapeInfo[0] + 3] = shape::order(minShapeInfo); // order
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if(!dimensions.empty()) {
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for(uint k = 0, j = 0, i = 0; i < shape::rank(maxShapeInfo); ++i) {
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if(j < dimensions.size() && dimensions[j] == i) {
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shape::shapeOf(newShapeInfo)[i] = shape::shapeOf(minShapeInfo)[k];
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shape::stride(newShapeInfo)[i] = shape::stride(minShapeInfo)[k++];
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++j;
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}
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else{
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shape::shapeOf(newShapeInfo)[i] = 1;
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shape::stride(newShapeInfo)[i] = 0;
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if(shape::sizeAt(minShapeInfo, k) == 1 && dimensions.size() != shape::rank(minShapeInfo))
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++k;
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}
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}
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}
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else{
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for(int j = shape::rank(minShapeInfo) - 1, i = shape::rank(maxShapeInfo) - 1; i >=0 ; --i) {
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if(j >= 0) {
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shape::shapeOf(newShapeInfo)[i] = shape::shapeOf(minShapeInfo)[j];
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shape::stride(newShapeInfo)[i] = shape::shapeOf(minShapeInfo)[j] == 1 ? 0 : shape::stride(minShapeInfo)[j];
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--j;
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}
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else {
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shape::shapeOf(newShapeInfo)[i] = 1;
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shape::stride(newShapeInfo)[i] = 0;
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}
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}
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}
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ShapeDescriptor descriptor(newShapeInfo);
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RELEASE(newShapeInfo, workspace);
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return bufferForShapeInfo(descriptor);
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}
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////////////////////////////////////////////////////////////////////////
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ConstantShapeBuffer& ConstantShapeHelper::createShapeInfoWithNoUnitiesForReduce(const Nd4jLong* inShapeInfo, const std::vector<int> &dimsWithUnities, sd::memory::Workspace* workspace) {
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Nd4jLong* newShapeInfo = nullptr;
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ALLOCATE(newShapeInfo, workspace, shape::shapeInfoLength(shape::rank(inShapeInfo) - dimsWithUnities.size()), Nd4jLong);
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int temp;
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if(dimsWithUnities.size() == 1 && shape::isCommonVector(inShapeInfo, temp) && temp == dimsWithUnities[0]) {
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auto dims = ShapeUtils::evalDimsToExclude(shape::rank(inShapeInfo), {temp});
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shape::excludeUnitiesFromShapeInfo(inShapeInfo, dims.data(), dims.size(), newShapeInfo);
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} else {
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shape::excludeUnitiesFromShapeInfo(inShapeInfo, dimsWithUnities.data(), dimsWithUnities.size(), newShapeInfo);
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}
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ShapeDescriptor descriptor(newShapeInfo);
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RELEASE(newShapeInfo, workspace);
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return bufferForShapeInfo(descriptor);
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}
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////////////////////////////////////////////////////////////////////////
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ConstantShapeBuffer& ConstantShapeHelper::createSubArrShapeInfo(const Nd4jLong* inShapeInfo, const int* dims, const int dimsSize, sd::memory::Workspace* workspace) {
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Nd4jLong* newShapeInfo = ShapeBuilders::createSubArrShapeInfo(inShapeInfo, dims, dimsSize, workspace);
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ShapeDescriptor descriptor(newShapeInfo);
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RELEASE(newShapeInfo, workspace);
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return bufferForShapeInfo(descriptor);
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}
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} |