249 lines
6.7 KiB
C++
249 lines
6.7 KiB
C++
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 raver119 on 04.08.17.
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//
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#include "testlayers.h"
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#include <memory>
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#include <array/NDArray.h>
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#include "ops/specials_sparse.h"
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using namespace sd;
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//////////////////////////////////////////////////////////////////////
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class SparseUtilsTest : public testing::Test {
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public:
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static const Nd4jLong nnz = 40;
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static const int rank = 3;
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};
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//////////////////////////////////////////////////////////////////////
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TEST_F(SparseUtilsTest, SortCOOindices_Test) {
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#ifndef __CUDABLAS__
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Nd4jLong * indicesArr = new Nd4jLong[nnz * rank]{
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0,2,7,
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2,36,35,
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3,30,17,
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5,12,22,
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5,43,45,
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6,32,11,
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8,8,32,
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9,29,11,
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5,11,22,
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15,26,16,
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17,48,49,
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24,28,31,
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26,6,23,
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31,21,31,
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35,46,45,
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37,13,14,
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6,38,18,
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7,28,20,
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8,29,39,
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8,32,30,
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9,42,43,
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11,15,18,
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13,18,45,
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29,26,39,
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30,8,25,
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42,31,24,
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28,33,5,
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31,27,1,
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35,43,26,
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36,8,37,
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39,22,14,
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39,24,42,
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42,48,2,
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43,26,48,
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44,23,49,
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45,18,34,
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46,28,5,
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46,32,17,
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48,34,44,
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49,38,39,
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};
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Nd4jLong * expIndicesArr = new Nd4jLong[nnz * rank]{
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0, 2, 7,
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2, 36, 35,
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3, 30, 17,
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5, 11, 22,
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5, 12, 22,
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5, 43, 45,
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6, 32, 11,
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6, 38, 18,
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7, 28, 20,
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8, 8, 32,
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8, 29, 39,
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8, 32, 30,
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9, 29, 11,
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9, 42, 43,
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11, 15, 18,
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13, 18, 45,
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15, 26, 16,
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17, 48, 49,
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24, 28, 31,
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26, 6, 23,
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28, 33, 5,
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29, 26, 39,
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30, 8, 25,
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31, 21, 31,
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31, 27, 1,
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35, 43, 26,
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35, 46, 45,
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36, 8, 37,
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37, 13, 14,
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39, 22, 14,
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39, 24, 42,
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42, 31, 24,
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42, 48, 2,
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43, 26, 48,
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44, 23, 49,
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45, 18, 34,
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46, 28, 5,
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46, 32, 17,
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48, 34, 44,
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49, 38, 39,
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};
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auto values = NDArrayFactory::create<float>('c', {40}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
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22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39});
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auto expValues = NDArrayFactory::create<float>('c', {40}, {0, 1, 2, 8, 3, 4, 5, 16, 17, 6, 18, 19, 7, 20, 21, 22, 9,
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10, 11, 12, 26, 23, 24, 13, 27, 28, 14, 29, 15, 30, 31, 25, 32, 33,
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34, 35, 36, 37, 38, 39
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});
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sd::sparse::SparseUtils<float >::sortCooIndicesGeneric(indicesArr, reinterpret_cast<float*>(values.buffer()), nnz, rank);
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for ( int i = 0; i < rank * nnz; ++i){
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ASSERT_EQ(expIndicesArr[i], indicesArr[i]);
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}
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ASSERT_TRUE(expValues.equalsTo(values));
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delete[] indicesArr;
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delete[] expIndicesArr;
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#endif
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}
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//////////////////////////////////////////////////////////////////////
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TEST_F(SparseUtilsTest, RavelIndices_Test) {
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#ifndef __CUDABLAS__
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Nd4jLong * indicesArrExp = new Nd4jLong[nnz * rank]{
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0,2,7,
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2,36,35,
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3,30,17,
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5,12,22,
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5,43,45,
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6,32,11,
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8,8,32,
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9,29,11,
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5,11,22,
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15,26,16,
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17,48,49,
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24,28,31,
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26,6,23,
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31,21,31,
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35,46,45,
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37,13,14,
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6,38,18,
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7,28,20,
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8,29,39,
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8,32,30,
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9,42,43,
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11,15,18,
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13,18,45,
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29,26,39,
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30,8,25,
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42,31,24,
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28,33,5,
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31,27,1,
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35,43,26,
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36,8,37,
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39,22,14,
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39,24,42,
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42,48,2,
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43,26,48,
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44,23,49,
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45,18,34,
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46,28,5,
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46,32,17,
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48,34,44,
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49,38,39,
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};
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Nd4jLong * indicesArr = new Nd4jLong[nnz * rank];
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Nd4jLong * flatIndicesExp = new Nd4jLong[nnz]{
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147, 10955, 14717, 21862, 24055, 27451, 34192, 39841,
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21792, 64836, 74809, 102791, 109643, 131701, 150265, 156324,
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27878, 31380, 35669, 35870, 40783, 47268, 55905, 123659,
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126585, 178594, 119915, 132091, 150036, 151797, 165354, 165522,
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179762, 182468, 186459, 190294, 195165, 195457, 204024, 208499
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};
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Nd4jLong * flatIndices = new Nd4jLong[nnz];
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Nd4jLong * shape = new Nd4jLong[rank]{50, 60, 70};
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Nd4jLong * shapeInfoBuffer = shape::shapeBuffer(rank, sd::DataType::INT64, shape);
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sd::sparse::IndexUtils::ravelMultiIndex(indicesArrExp, flatIndices, nnz, shapeInfoBuffer, ND4J_CLIPMODE_THROW);
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for ( int i = 0; i < nnz; ++i){
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ASSERT_EQ(flatIndicesExp[i], flatIndices[i]);
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}
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sd::sparse::IndexUtils::unravelIndex(indicesArr, flatIndices, nnz, shapeInfoBuffer);
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for ( int i = 0; i < nnz * rank; ++i){
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ASSERT_EQ(indicesArrExp[i], indicesArr[i]);
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}
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shape[2] = 30;
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delete[] shapeInfoBuffer;
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shapeInfoBuffer = shape::shapeBuffer(rank, sd::DataType::INT64, shape);
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try {
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sd::sparse::IndexUtils::ravelMultiIndex(indicesArrExp, flatIndices, nnz, shapeInfoBuffer, ND4J_CLIPMODE_THROW);
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FAIL();
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} catch (const std::runtime_error& e) {
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// pass
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}
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delete[] indicesArrExp;
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delete[] indicesArr;
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delete[] flatIndicesExp;
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delete[] flatIndices;
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delete[] shape;
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delete[] shapeInfoBuffer;
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#endif
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}
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