2019-06-06 14:21:15 +02:00
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/*******************************************************************************
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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 "../ConstantTadHelper.h"
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2020-03-02 10:49:41 +01:00
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#include <helpers/TAD.h>
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#include <helpers/ShapeUtils.h>
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2019-06-06 14:21:15 +02:00
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#ifndef __CUDABLAS__
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2020-02-24 05:51:01 +01:00
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2020-03-02 10:49:41 +01:00
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namespace sd {
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ConstantTadHelper::ConstantTadHelper() {
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MAP_IMPL<TadDescriptor, TadPack> pack;
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_cache.emplace_back(pack);
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}
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ConstantTadHelper* ConstantTadHelper::getInstance() {
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if (!_INSTANCE)
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_INSTANCE = new ConstantTadHelper();
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return _INSTANCE;
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}
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2019-09-03 21:02:02 +02:00
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TadPack ConstantTadHelper::tadForDimensions(const Nd4jLong *originalShape, int dimension, const bool keepUnitiesInShape) {
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return tadForDimensions(originalShape, &dimension, 1, keepUnitiesInShape);
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}
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2019-09-03 21:02:02 +02:00
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TadPack ConstantTadHelper::tadForDimensions(const Nd4jLong *originalShape, const std::vector<int> &dimensions, const bool keepUnitiesInShape) {
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return tadForDimensions(originalShape, const_cast<int *>(dimensions.data()), dimensions.size(), keepUnitiesInShape);
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}
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2019-09-03 21:02:02 +02:00
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TadPack ConstantTadHelper::tadForDimensions(const Nd4jLong *originalShape, int* dimensions, int dimLength, const bool keepUnitiesInShape) {
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TadDescriptor tadDescriptor(originalShape, dimensions, dimLength, keepUnitiesInShape);
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return tadForDimensions(tadDescriptor);
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}
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2019-09-03 21:02:02 +02:00
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TadPack ConstantTadHelper::tadForDimensions(ShapeDescriptor &descriptor, std::vector<int> &dimensions, const bool keepUnitiesInShape) {
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TadDescriptor tadDescriptor(descriptor, dimensions, keepUnitiesInShape);
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return tadForDimensions(tadDescriptor);
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}
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TadPack ConstantTadHelper::tadForDimensions(TadDescriptor &descriptor) {
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const int deviceId = 0;
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_mutex.lock();
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if (_cache[deviceId].count(descriptor) == 0) {
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const auto shapeInfo = descriptor.originalShape().toShapeInfo();
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const int rank = shape::rank(shapeInfo);
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const std::vector<int> dimsToExclude = ShapeUtils::evalDimsToExclude(rank, descriptor.axis());
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const Nd4jLong numOfSubArrs = ShapeUtils::getNumOfSubArrs(shapeInfo, dimsToExclude);
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const int subArrRank = (rank == dimsToExclude.size() || descriptor.areUnitiesinShape()) ? rank : rank - dimsToExclude.size();
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Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
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auto sPtr = new Nd4jLong[shape::shapeInfoLength(subArrRank)]; // shape of sub-arrays (same for all for them)
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auto oPtr = new Nd4jLong[numOfSubArrs];
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2019-06-15 13:34:34 +02:00
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if (numOfSubArrs > 0)
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shape::calcSubArrsShapeInfoAndOffsets(shapeInfo, numOfSubArrs, dimsToExclude.size(), dimsToExclude.data(), sPtr, oPtr, descriptor.areUnitiesinShape());
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2019-06-06 14:21:15 +02:00
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ConstantDataBuffer shapesBuffer(sPtr, nullptr, shape::shapeInfoLength(subArrRank)*sizeof(Nd4jLong), DataType::INT64);
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ConstantDataBuffer offsetsBuffer(oPtr, nullptr, numOfSubArrs*sizeof(Nd4jLong), DataType::INT64);
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TadPack t(shapesBuffer, offsetsBuffer, numOfSubArrs);
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// auto shapeInfo = descriptor.originalShape().toShapeInfo();
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// shape::TAD tad;
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// tad.init(shapeInfo, descriptor.axis().data(), descriptor.axis().size());
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// tad.createTadOnlyShapeInfo();
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// tad.createOffsets();
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// auto sPtr = new Nd4jLong[shape::shapeInfoLength(tad.tadOnlyShapeInfo)];
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// auto oPtr = new Nd4jLong[tad.numTads];
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// memcpy(sPtr, tad.tadOnlyShapeInfo, shape::shapeInfoByteLength(tad.tadOnlyShapeInfo));
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// memcpy(oPtr, tad.tadOffsets, tad.numTads * sizeof(Nd4jLong));
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// TadPack t(shapesBuffer, offsetsBuffer, tad.numTads);
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_cache[deviceId][descriptor] = t;
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TadPack &r = _cache[deviceId][descriptor];
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_mutex.unlock();
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delete[] shapeInfo;
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return r;
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} else {
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TadPack r = _cache[deviceId][descriptor];
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_mutex.unlock();
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return r;
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}
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}
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2020-03-02 10:49:41 +01:00
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sd::ConstantTadHelper* sd::ConstantTadHelper::_INSTANCE = 0;
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2019-06-06 14:21:15 +02:00
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}
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#endif
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