* 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>
154 lines
5.1 KiB
C++
154 lines
5.1 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 raver119@gmail.com
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_squeeze)
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#include <ops/declarable/CustomOperations.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(squeeze, 1, 1, true, 0, -2) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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std::vector<int> axis;
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if (block.numI() > 0)
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for (int e = 0; e < block.numI(); e++) {
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int _a = INT_ARG(e);
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if (_a < 0)
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_a += input->rankOf();
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axis.emplace_back(_a);
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}
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else if (block.width() > 1) {
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auto a = INPUT_VARIABLE(1);
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for (Nd4jLong e = 0; e < a->lengthOf(); e++) {
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int _a = a->e<int>(e);
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if (_a < 0)
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_a += input->rankOf();
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axis.emplace_back(_a);
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}
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}
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if (input->rankOf() == 0 || (input->rankOf() == 1 && input->lengthOf() == 1)) {
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output->assign(input);
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return Status::OK();
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}
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std::vector<Nd4jLong> shape;
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if (axis.size() == 0) {
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for (int d = 0; d < input->rankOf(); d++)
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if (input->sizeAt(d) > 1)
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shape.emplace_back(input->sizeAt(d));
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} else {
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for (int d = 0; d < input->rankOf(); d++) {
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if (input->sizeAt(d) == 1) {
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if (std::find(axis.begin(), axis.end(), d) == axis.end())
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shape.emplace_back(input->sizeAt(d));
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} else shape.emplace_back(input->sizeAt(d));
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}
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}
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if (block.isInplace()) {
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output->reshapei(input->ordering(), shape, false);
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} else {
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auto tmp = input->reshape(input->ordering(), shape);
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output->assign(tmp);
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}
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return Status::OK();
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}
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DECLARE_TYPES(squeeze) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setSameMode(true);
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}
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DECLARE_SHAPE_FN(squeeze) {
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auto shapeList = SHAPELIST();
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Nd4jLong* newShape;
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auto in = inputShape->at(0);
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auto rank = shape::rank(in);
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auto length = shape::length(in);
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if (rank == 0 || (rank == 1 && length == 1)) {
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shapeList->push_back(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(in)));
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return shapeList;
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}
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std::vector<int> axis;
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if (block.numI() > 0)
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for (int e = 0; e < block.numI(); e++) {
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int _a = INT_ARG(e);
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if (_a < 0)
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_a += rank;
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axis.emplace_back(_a);
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}
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else if (block.width() > 1) {
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auto a = INPUT_VARIABLE(1);
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for (int e = 0; e < a->lengthOf(); e++) {
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int _a = a->e<int>(e);
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if (_a < 0)
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_a += rank;
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axis.emplace_back(_a);
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}
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}
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auto order = shape::order(in);
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auto oldShape = shape::shapeOf(in);
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std::vector<Nd4jLong> shape;
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if (axis.size() == 0) {
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for (int d = 0; d < rank; d++)
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if (oldShape[d] > 1)
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shape.emplace_back(oldShape[d]);
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} else {
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for (int d = 0; d < rank; d++) {
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if (oldShape[d] == 1) {
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if (std::find(axis.begin(), axis.end(), d) == axis.end())
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shape.emplace_back(oldShape[d]);
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} else shape.emplace_back(oldShape[d]);
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}
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}
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if (shape.size() == 0) {
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shapeList->push_back(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(in)));
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return shapeList;
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}
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newShape = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(in), order, shape);
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shapeList->push_back(newShape);
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return shapeList;
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}
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}
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}
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#endif |