d52e67209e
* StringUtils for utf convertor raw implementation of all possible combinations, need to be add counter of bytes per symbol for any type and add api to call convertors and store data Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor more corrections to support convertors Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor some corrections and bug fixes, need review to discuss how to add multi-threading Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 some corrections to move to multi-threading, add one test need discussion data inputs/outputs array presentation, need discussion the way of multi-threading * StringUtils for utf convertor #8613 tests added some corrections to optimize build Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 some corrections and code clean up Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 code clean up and optimize usage, need update ndarray factory before replace std usage Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 some staff to integrate converters into NDArrayFactory, update tests and add some functionality Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 minor corrections and bug fix before discussion * StringUtils for utf convertor #8613 some fixes and tets * StringUtils for utf convertor #8613 some more staff to support different unicode Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 fix linking bug * StringUtils for utf convertor #8613 corrected several tests as defaults for string ndarray changed * StringUtils for utf convertor #8613 replace some incorrect implementation, revert some test changes, need sync before testing * StringUtils for utf convertor #8613 fixed several thing that were badly implemented yesterday, need optimization, testing (before testing have to be add support of u32 and u16 buffer visualization) * StringUtils for utf convertor #8613 fixed to support u16 and u32, and convertor in ndarray, fix buffer print, etc Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 merge master and sync with server Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 some correction for string cast, need print check only asci support Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 merge master, remove copies and add cast, need test, refactoring according review and clean up * StringUtils for utf convertor #8613 fixed cast and copy issues Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 fixed cuda and update tests * StringUtils for utf convertor #8613 integration into NdArray, fix several tests for build pass, refactoring, etc * - avoid ambiguity of NDArray ctrs overloading in some tests Signed-off-by: Yurii <iuriish@yahoo.com> * StringUtils for utf convertor #8613 NDArray string constructors added, updated NDArrayFactory, refactoring unicode and tests, etc Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 fixed cuda build and test, refactoring and void* added to some functions Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 void* integration, removed copy operation, refactoring, added tests for NDArray string constructors, etc Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 several more fixes, improvements and updates Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 master merge, code clean up and optimization before review Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 minor fixes string element size define Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 revert last changes as mistake Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 fixed NDArray constructor build problem, remove order from string factory, fixed order use for factory via project, added catch of incorrect sync in cast of arrays to data types, fixed e method for strings, etc Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 added javacpp hack, added multi-threading, minor corrections in license agreement Signed-off-by: Oleg <oleg.semeniv@gmail.com> * StringUtils for utf convertor #8613 windows builds fix, as "sting" is not treated as utf8 Signed-off-by: Oleg <oleg.semeniv@gmail.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
3350 lines
153 KiB
C++
3350 lines
153 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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* Copyright (c) 2019 Konduit K.K.
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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 raver on 8/4/2018.
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//
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#include "testlayers.h"
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#include <ops/declarable/CustomOperations.h>
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#include <NDArray.h>
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#include <ops/ops.h>
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#include <GradCheck.h>
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using namespace nd4j;
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class DeclarableOpsTests10 : public testing::Test {
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public:
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DeclarableOpsTests10() {
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printf("\n");
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fflush(stdout);
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}
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};
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template <typename T>
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class TypedDeclarableOpsTests10 : public testing::Test {
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public:
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TypedDeclarableOpsTests10() {
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printf("\n");
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fflush(stdout);
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}
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};
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typedef ::testing::Types<double, float> TestingTypes;
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TYPED_TEST_CASE(TypedDeclarableOpsTests10, TestingTypes);
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TEST_F(DeclarableOpsTests10, Test_ArgMax_1) {
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auto x = NDArrayFactory::create<double>('c', {3, 3});
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auto e = NDArrayFactory::create<Nd4jLong>(8);
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x.linspace(1.0);
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nd4j::ops::argmax op;
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auto result = op.evaluate({&x});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = *result->at(0);
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ASSERT_EQ(e, z);
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_ArgMax_2) {
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auto x = NDArrayFactory::create<double>('c', {3, 3});
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auto y = NDArrayFactory::create<int>('c', {1}, {1});
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auto e = NDArrayFactory::create<Nd4jLong>('c', {3}, {2, 2, 2});
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x.linspace(1.0);
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nd4j::ops::argmax op;
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auto result = op.evaluate({&x, &y});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = *result->at(0);
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//z.printIndexedBuffer("z");
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//z.printShapeInfo("z shape");
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ASSERT_EQ(e, z);
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_And_1) {
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auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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auto e = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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nd4j::ops::boolean_and op;
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auto result = op.evaluate({&x, &y});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Or_1) {
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auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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auto e = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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nd4j::ops::boolean_or op;
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auto result = op.evaluate({&x, &y});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Not_1) {
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auto x = NDArrayFactory::create<bool>('c', {4}, {true, true, false, true});
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auto y = NDArrayFactory::create<bool>('c', {4}, {false, false, false, true});
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// auto e = NDArrayFactory::create<bool>('c', {4}, {1, 1, 1, 0});
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auto e = NDArrayFactory::create<bool>('c', {4}, {false, false, true, false});
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nd4j::ops::boolean_not op;
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auto result = op.evaluate({&x, &y});
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ASSERT_EQ(Status::OK(), result->status());
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auto res = result->at(0);
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ASSERT_TRUE(e.equalsTo(res));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Size_at_1) {
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auto x = NDArrayFactory::create<double>('c', {10, 20, 30});
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auto e = NDArrayFactory::create<Nd4jLong>(20);
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nd4j::ops::size_at op;
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auto result = op.evaluate({&x}, {1});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, MirrorPad_SGO_Test_1) {
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auto in = NDArrayFactory::create<double>({1., 2., 3., 4., 5.});
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// auto pad('c', {1, 2}, {1., 1.});// = Nd4j.create(new double[]{1, 1}, new long[]{1, 2});
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auto pad = NDArrayFactory::create<int>('c', {1, 2}, {1, 1});
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// auto value(10.0);
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auto exp = NDArrayFactory::create<double>({2., 1., 2., 3., 4., 5., 4.});
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nd4j::ops::mirror_pad op;
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auto res = op.evaluate({&in, &pad}, {10.0}, {0});
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ASSERT_EQ(res->status(), ND4J_STATUS_OK);
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ASSERT_TRUE(exp.equalsTo(res->at(0)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Unique_SGO_Test_1) {
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auto input = NDArrayFactory::create<double>({3., 4., 3., 1., 3., 0., 2., 4., 2., 4.});
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auto expIdx = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
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auto exp = NDArrayFactory::create<double>({3., 4., 1., 0., 2.});
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nd4j::ops::unique op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_EQ(res->status(), ND4J_STATUS_OK);
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auto res1 = res->at(0);
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auto res2 = res->at(1);
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ASSERT_TRUE(exp.equalsTo(res1));
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ASSERT_TRUE(expIdx.equalsTo(res2));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_1) {
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auto input = NDArrayFactory::create<bool>('c', {3, 3}, {true, false, false, true, true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {6, 2}, {0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 2LL, 0LL, 2LL, 1LL, 2LL, 2LL});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(exp.isSameShape(resA));
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ASSERT_TRUE(exp.equalsTo(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_02) {
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auto input = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {5, 3}, {0LL, 0LL, 0LL, 0LL, 1LL, 1LL, 1LL, 0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 1LL, 0LL});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_1) {
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auto cond3d = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
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// auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 1, 1, 1});
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auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 0, 1});
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auto exp3 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 1, 0});
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nd4j::ops::where_np op;
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auto res = op.evaluate({&cond3d}, {}, {});
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ASSERT_TRUE(res->size() == 3);
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ASSERT_EQ(res->status(), ND4J_STATUS_OK);
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auto res1 = res->at(0);
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auto res2 = res->at(1);
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auto res3 = res->at(2);
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// res1->printShapeInfo("Res1 shape"); res1->printBuffer("Res1");
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// res2->printShapeInfo("Res2 shape"); res2->printBuffer("Res2");
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// res3->printShapeInfo("Res3 shape"); res3->printBuffer("Res3");
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ASSERT_TRUE(exp1.equalsTo(res1));
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ASSERT_TRUE(exp2.equalsTo(res2));
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ASSERT_TRUE(exp3.equalsTo(res3));
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//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_2) {
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auto cond2d = NDArrayFactory::create<bool>('c', {3, 5}, {true, true, false, false, true, true, true,
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true, true, true, false, true, true, true, true});
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// auto expIdx({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
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auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2});
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auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 4, 0, 1, 2, 3, 4, 1, 2, 3, 4});
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nd4j::ops::where_np op;
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auto res = op.evaluate({&cond2d}, {}, {});
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ASSERT_TRUE(res->size() == 2);
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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ASSERT_TRUE(exp1.equalsTo(res->at(0)));
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ASSERT_TRUE(exp2.equalsTo(res->at(1)));
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//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_2) {
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auto input = NDArrayFactory::create<bool>({true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4,1}, {0, 2, 3, 4});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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// resA->printIndexedBuffer("Result A");
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// resA->printShapeInfo("ShapeA");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_3) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_4) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(resA->isEmpty());
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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//ASSERT_TRUE(exp.equalsTo(resA));
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//ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_5) {
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auto input = NDArrayFactory::create<float>('c', {5}, {1, 0, 0, 2, 3});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {3, 1}, {0, 3, 4});
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nd4j::ops::Where op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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//ASSERT_TRUE(resA->isEmpty());
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_4) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::where_np op;
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auto res = op.evaluate({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(resA->isEmpty());
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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//ASSERT_TRUE(exp.equalsTo(resA));
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//ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_1) {
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auto labels = NDArrayFactory::create<double>('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto predictions = NDArrayFactory::create<double>('c', {2, 3}, {-0.3, -0.2, -0.1, 0, 0.1, 0.2});
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auto weights = NDArrayFactory::create<double>('c', {2, 1}, {0., 1.});
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auto exp = NDArrayFactory::create<double>(0.6);
|
|
|
|
nd4j::ops::cosine_distance_loss op;
|
|
auto res = op.evaluate({&predictions, &weights, &labels}, {}, {3, 1});
|
|
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
|
|
auto resA = res->at(0);
|
|
|
|
ASSERT_TRUE(exp.equalsTo(resA));
|
|
|
|
delete res;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_2) {
|
|
auto labels = NDArrayFactory::create<double>('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
|
|
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
|
|
auto predictions = NDArrayFactory::create<double>('c', {2, 3}, {-0.3, -0.2, -0.1, 0, 0.1, 0.2});
|
|
auto weights = NDArrayFactory::create<double>('c', {2, 1}, {0., 1.});
|
|
auto exp = NDArrayFactory::create<double>(0.6);
|
|
|
|
nd4j::ops::cosine_distance_loss op;
|
|
auto res = op.evaluate({&predictions, &weights, &labels}, {}, {2, 1});
|
|
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
|
|
auto resA = res->at(0);
|
|
|
|
ASSERT_TRUE(exp.equalsTo(resA));
|
|
|
|
delete res;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, TestMarixBandPart_Test_1) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 3});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2, 3, 3});
|
|
x.linspace(1);
|
|
exp.linspace(1);
|
|
exp.p(0, 0, 2, 0.);
|
|
exp.p(1, 0, 2, 0.);
|
|
exp.p(0, 2, 0, 0.);
|
|
exp.p(1, 2, 0, 0.);
|
|
|
|
nd4j::ops::matrix_band_part op;
|
|
auto results = op.evaluate({&x}, {}, {1, 1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
//results->at(0)->printIndexedBuffer("MBP Test1");
|
|
//exp.printIndexedBuffer("MBP Expec");
|
|
ASSERT_TRUE(exp.equalsTo(results->at(0)));
|
|
|
|
delete results;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test1) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {-0.51, -0.46, -0.41, -0.36, -0.31, -0.26, -0.21, -0.16, -0.11, -0.06, -0.01, 0.04, 0.09, 0.14, 0.19, 0.24, 0.29, 0.34, 0.39, 0.44, 0.49, 0.54, 0.59, 0.61});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.04201, -2.03663, -2.03009, -2.02199,-2.01166, -1.99808, -1.97941, -1.95217,-1.90875, -1.8292 , -1.6416 , -0.942 ,
|
|
0.33172, 0.69614, 0.81846, 0.87776, 0.91253, 0.93533, 0.95141, 0.96336, 0.97259, 0.97993, 0.98591, 1.01266,});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&y, &x}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test2) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
|
|
auto x = NDArrayFactory::create<double>('c', { 3, 4}, {-1.05, -0.82, -0.639, -0.458, -0.277, -0.096, 0.085, 0.266, 0.447, 0.628, 0.809, 0.99});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.38008, -2.30149, -2.22748, -2.1232 ,-1.96979, -1.73736, -1.3973 , -0.98279,-0.61088, -0.34685, -0.17256, -0.0555 ,
|
|
3.11208, 2.99987, 2.83399, 2.57869, 2.207 , 1.77611, 1.41664, 1.17298, 1.01458, 0.90829, 0.8336 , 0.77879});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&y, &x}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printIndexedBuffer();
|
|
|
|
// x.applyTrueBroadcast(nd4j::BroadcastOpsTuple::custom(scalar::Atan2, pairwise::Atan2, broadcast::Atan2), &y, &z, true);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test3) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
|
|
auto x = NDArrayFactory::create<double>('c', { 3, 4}, {-1.05, -0.82, -0.639, -0.458, -0.277, -0.096, 0.085, 0.266, 0.447, 0.628, 0.809, 0.99});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.33231, -2.41089, -2.48491, -2.58919,-2.74259, -2.97502, 2.9681 , 2.55359, 2.18167, 1.91765, 1.74335, 1.62629,
|
|
-1.54128, -1.42907, -1.2632 , -1.00789,-0.63621, -0.20531, 0.15416, 0.39782, 0.55622, 0.6625 , 0.7372 , 0.79201});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&x, &y}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test4) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 1}, {-0.82, -0.458, -0.096, 0.085, 0.447, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.45527, -2.36165, -2.24628, -2.10492,-2.1703 , -1.86945, -1.50321, -1.15359,-0.25062, -0.17373, -0.13273, -0.10733,
|
|
3.05688, 3.03942, 3.01293, 2.9681 , 2.18167, 1.87635, 1.50156, 1.14451, 1.13674, 0.97626, 0.84423, 0.7372 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&x, &y}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test5) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 1}, {-0.82, -0.458, -0.096, 0.085, 0.447, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.25712, -2.35074, -2.46611, -2.60747,-2.54209, -2.84294, 3.07401, 2.72438, 1.82141, 1.74453, 1.70353, 1.67813,
|
|
-1.48608, -1.46862, -1.44214, -1.3973 ,-0.61088, -0.30556, 0.06924, 0.42629, 0.43405, 0.59453, 0.72657, 0.8336 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test6) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {-0.82, -0.096, 0.085, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {-2.25712, -1.68608, -1.44214, -0.54006,-2.77695, -2.16855, 0.34972, 0.24585, 2.71267, 1.74453, 1.45312, 0.8336 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.evaluate({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, IGamma_Test1) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {1.1 , 2.1 , 3.1 ,4.1 , 5.1 , 6.1 ,7.1 ,8.1 ,9.1 ,10.1,11.1 ,12.1});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {1.2, 2.2, 3.2, 4.2});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {
|
|
0.659917, 0.61757898, 0.59726304, 0.58478117,
|
|
0.0066205109, 0.022211598, 0.040677428, 0.059117373,
|
|
0.0000039433403, 0.000086064574, 0.000436067, 0.0012273735});
|
|
|
|
nd4j::ops::igamma op;
|
|
auto result = op.evaluate({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printBuffer("OUtput");
|
|
// exp.printBuffer("EXpect");
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, IGamma_Test2) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {1.1 , 2.1 , 3.1 ,4.1 , 5.1 , 6.1 ,
|
|
7.1 ,8.1 ,9.1 ,10.1,11.1 ,12.1});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {1.2, 2.2, 3.2, 4.2});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {0.340083, 0.382421, 0.402737, 0.415221,
|
|
0.993379, 0.977788, 0.959323, 0.940883,
|
|
0.999996, 0.999914, 0.999564, 0.998773});
|
|
|
|
nd4j::ops::igammac op;
|
|
auto result = op.evaluate({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printBuffer("OUtput");
|
|
// exp.printBuffer("EXpect");
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, LGamma_Test1) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {3, 3}, {0.1, 0.5, 0.7, 1.5, 1.7, 2.0, 2.5, 2.7, 3.});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {
|
|
2.2527127 , 0.5723649 , 0.26086727,
|
|
-0.12078223, -0.09580769, 0.,
|
|
0.28468287, 0.4348206 , 0.6931472
|
|
});
|
|
|
|
nd4j::ops::lgamma op;
|
|
auto result = op.evaluate({&x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printBuffer("OUtput");
|
|
// exp.printBuffer("EXpect");
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test10) {
|
|
|
|
auto limit = NDArrayFactory::create<double>('c', {1, 3, 4});
|
|
limit = 5.;
|
|
auto exp = NDArrayFactory::create<double>('c', {5}, {0.,1.,2.,3.,4.});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.evaluate({&limit}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test11) {
|
|
|
|
auto limit = NDArrayFactory::create<double>('c', {1, 3, 4});
|
|
auto start = NDArrayFactory::create<double>('c', {2, 4});
|
|
limit = 5.;
|
|
start = 0.5;
|
|
auto exp = NDArrayFactory::create<double>('c', {5}, {0.5,1.5,2.5,3.5,4.5});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.evaluate({&start, &limit}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test12) {
|
|
|
|
auto exp = NDArrayFactory::create<float>('c', {9}, {0.5f, 1.f , 1.5f, 2.f , 2.5f, 3.f , 3.5f, 4.f , 4.5f});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.evaluate({}, {0.5, 5, 0.5}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, top_k_permuted_test1) {
|
|
|
|
auto x = NDArrayFactory::create<double>({7., 3., 1., 2., 5., 0., 4., 6., 9., 8.});
|
|
auto expUnsorted = NDArrayFactory::create<double>({7., 6., 9., 8.}); // Sorted = False
|
|
auto expSorted = NDArrayFactory::create<double>({9., 8., 7., 6., 5.}); // Sorted = False
|
|
|
|
|
|
nd4j::ops::top_k op;
|
|
auto result = op.evaluate({&x}, {}, {4}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
auto zI = result->at(1);
|
|
|
|
ASSERT_TRUE(expUnsorted.isSameShape(z));
|
|
ASSERT_TRUE(expUnsorted.equalsTo(z));
|
|
|
|
auto result2 = op.evaluate({&x}, {}, {5}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result2->status());
|
|
|
|
z = result2->at(0);
|
|
zI = result2->at(1);
|
|
|
|
ASSERT_TRUE(expSorted.isSameShape(z));
|
|
ASSERT_TRUE(expSorted.equalsTo(z));
|
|
|
|
delete result;
|
|
delete result2;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, top_k_permuted_test2) {
|
|
|
|
auto x = NDArrayFactory::create<double>({7., 3., 1., 2., 5., 0., 4., 6., 9., 8.});
|
|
auto expUnsorted = NDArrayFactory::create<double>({7., 5., 6., 9., 8.}); // Sorted = False
|
|
auto expSorted = NDArrayFactory::create<double>({9., 8., 7., 6., 5.}); // Sorted = False
|
|
|
|
|
|
nd4j::ops::top_k op;
|
|
auto result = op.evaluate({&x}, {}, {5}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
auto zI = result->at(1);
|
|
|
|
ASSERT_TRUE(expUnsorted.isSameShape(z));
|
|
ASSERT_TRUE(expUnsorted.equalsTo(z));
|
|
|
|
auto result2 = op.evaluate({&x}, {}, {5}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result2->status());
|
|
|
|
z = result2->at(0);
|
|
zI = result2->at(1);
|
|
|
|
ASSERT_TRUE(expSorted.isSameShape(z));
|
|
ASSERT_TRUE(expSorted.equalsTo(z));
|
|
|
|
delete result;
|
|
delete result2;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test1) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2,3},{3, 2, 1, 0, 1, 2});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,3,4});
|
|
auto expected = NDArrayFactory::create<double>('c', {2,3}, {1.24254, 1.34254, 1.44254, 1.54254, 1.44254, 1.34254});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.evaluate({&labels, &logits});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test2) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2},{1, 0});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,3});
|
|
auto expected = NDArrayFactory::create<double>('c', {2}, {1.10194, 1.20194});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.evaluate({&labels, &logits});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test3) {
|
|
|
|
NDArray labels('c', {1}, std::vector<double>{0}, nd4j::DataType::INT32);
|
|
auto logits = NDArrayFactory::create<double>('c', {1,3});
|
|
auto expected = NDArrayFactory::create<double>('c', {1}, {1.20194});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.evaluate({&labels, &logits});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test4) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2},{0, 0});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,1});
|
|
auto expected = NDArrayFactory::create<double>('c', {2}, {0., 0.});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.evaluate({&labels, &logits});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, split_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {10},{1.f,2.f,3.f,4.f,5.f,6.f,7.f,8.f,9.f,10.f});
|
|
auto axis = NDArrayFactory::create<double>(-1);
|
|
auto exp1 = NDArrayFactory::create<double>('c', {5}, {1.f,2.f,3.f,4.f,5.f});
|
|
auto exp2 = NDArrayFactory::create<double>('c', {5}, {6.f,7.f,8.f,9.f,10.f});
|
|
|
|
nd4j::ops::split op;
|
|
auto results = op.evaluate({&input, &axis}, {}, {2}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out1 = results->at(0);
|
|
auto out2 = results->at(1);
|
|
|
|
ASSERT_TRUE(exp1.isSameShape(out1));
|
|
ASSERT_TRUE(exp2.isSameShape(out2));
|
|
ASSERT_TRUE(exp1.equalsTo(out1));
|
|
ASSERT_TRUE(exp2.equalsTo(out2));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, split_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3,8},{1.f,2.f,3.f,4.f,5.f,6.f,7.f,8.f,9.f,10.f,11.f,12.f,13.f,14.f,15.f,16.f,17.f,18.f,19.f,20.f,21.f,22.f,23.f,24.f});
|
|
auto exp1 = NDArrayFactory::create<double>('c', {3,4}, {1.f,2.f,3.f,4.f, 9.f,10.f,11.f,12.f, 17.f,18.f,19.f,20.f});
|
|
auto exp2 = NDArrayFactory::create<double>('c', {3,4}, {5.f,6.f,7.f,8.f, 13.f,14.f,15.f,16.f, 21.f,22.f,23.f,24.f});
|
|
|
|
nd4j::ops::split op;
|
|
auto results = op.evaluate({&input}, {}, {2,-1},{});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out1 = results->at(0);
|
|
auto out2 = results->at(1);
|
|
|
|
ASSERT_TRUE(exp1.isSameShape(out1));
|
|
ASSERT_TRUE(exp2.isSameShape(out2));
|
|
ASSERT_TRUE(exp1.equalsTo(out1));
|
|
ASSERT_TRUE(exp2.equalsTo(out2));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test1) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3},{-1.f, 0.f, 1.5f, 2.f, 5.f, 15.f});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {2, 1, 1, 0, 2});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test2) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3,4},{0.f, 5.f, 2.f, 1.f, -1.f, 2.f, 5.f, 3.f, 2.f, 3.f, -1.f, 5.f, 3.f, 2.f, 1.f, 4.f, 2.f, 5.f, 5.f, 5.f, 6.f, 6.f, -1.f, 0.f});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {5, 2, 5, 3, 9});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test3) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3,1,4,1},{0.f, 5.f, 2.001f, 1.f, -1.f, 2.f, 5.f, 3.f, 2.999f, 3.00001f, -1.f, 3.99999f, 3.f, 2.f, 1.f, 4.f, 2.f, 5.f, 5.f, 5.f, 6.f, 6.f, -1.f, 0.00001f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2,1}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {5, 2, 5, 4, 8});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {20,5},{13.8387f,0.1509f,50.39f,30.403f,13.5174f,9.7351f,37.6652f,28.9215f,22.7011f,45.2834f,40.7628f,50.4995f,26.8003f,27.479f,44.633f,6.9109f,48.5004f,
|
|
46.5971f,1.6203f,23.6381f,38.9661f,50.8146f,17.2482f,8.0429f,7.5666f,7.9709f,21.8403f,20.1694f,23.3004f,50.9151f,46.239f,38.7323f,29.6946f,32.9876f,
|
|
23.0013f,39.7318f,19.4486f,37.6147f,-0.1506f,5.3246f,3.6173f,24.2573f,4.3941f,9.7105f,24.0364f,35.3681f,17.7805f,35.7681f,16.4144f,17.4362f,8.4987f,
|
|
26.8108f,36.2937f,31.6442f,29.7221f,8.7445f,33.3301f,4.0939f,13.078f,45.1481f,29.0172f,21.6548f,35.408f,27.1861f,2.2576f,40.6804f,36.2201f,29.7352f,
|
|
29.1244f,38.7444f,5.8721f,33.5983f,48.2694f,34.4161f,19.7148f,13.8085f,13.6075f,22.5042f,37.8002f,50.0543f,48.5314f,20.3694f,28.5042f,-0.4679f,4.4245f,
|
|
18.9837f,40.7724f,2.7611f,44.0431f,37.186f,27.7361f,14.6001f,9.1721f,14.6087f,21.4072f,49.3344f,11.4668f,14.6171f,15.2502f,5.244f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2}, {0, 50});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {22, 17, 24, 19, 18});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,20},{20.f, 0.f, 60.f, 40.f, 20.f, 0.f, 40.f, 0.f, 40.f, 40.f,40.f,60.f, 20.f, 20.f, 60.f, 0.f, 40.f,
|
|
46.5971f,1.6203f,23.6381f,38.9661f,50.8146f,17.2482f,8.0429f,7.5666f,7.9709f,21.8403f,20.1694f,23.3004f,50.9151f,46.239f,38.7323f,29.6946f,32.9876f,
|
|
23.0013f,39.7318f,19.4486f,37.6147f,-0.1506f,5.3246f,3.6173f,24.2573f,4.3941f,9.7105f,24.0364f,35.3681f,17.7805f,35.7681f,16.4144f,17.4362f,8.4987f,
|
|
26.8108f,36.2937f,31.6442f,29.7221f,8.7445f,33.3301f,4.0939f,13.078f,45.1481f,29.0172f,21.6548f,35.408f,27.1861f,2.2576f,40.6804f,36.2201f,29.7352f,
|
|
29.1244f,38.7444f,5.8721f,33.5983f,48.2694f,34.4161f,19.7148f,13.8085f,13.6075f,22.5042f,37.8002f,50.0543f,48.5314f,20.3694f,28.5042f,-0.4679f,4.4245f,
|
|
18.9837f,40.7724f,2.7611f,44.0431f,37.186f,27.7361f,14.6001f,9.1721f,14.6087f,21.4072f,49.3344f,11.4668f,14.6171f,15.2502f,5.244f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2}, {0, 50});
|
|
// auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {23, 19, 20, 23, 15}); // 23, 15, 24, 17, 21
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {23, 15, 24, 17, 21});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
// out->printBuffer("5HIST");
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test6) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {7},{0.0, 0.1, 0.1, 0.3, 0.5, 0.5, 0.9});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 1});
|
|
auto bins = NDArrayFactory::create<int>(5);
|
|
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {3, 1, 2, 0, 1});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.evaluate({&input, &range, &bins}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
// out->printShapeInfo();
|
|
// out->printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<float>(4.f);
|
|
NDArray exp = NDArrayFactory::create<float>(5.f);
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_2) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3, 4}, {10, 11, 9, 12, 8, 7, 6, 5, 1, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(3);
|
|
NDArray exp = NDArrayFactory::create<float>({12.f, 8.f, 4.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_3) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3,4}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(3);
|
|
NDArray exp = NDArrayFactory::create<float>({1.f, 5.f, 2.f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {1}); // with reverse = true
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_4) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 2, 3}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,2}, {10.f, 11.f, 12.f, 4.f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_04) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {6, 15});
|
|
NDArray n = NDArrayFactory::create<int>(4);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {6}, {5.f, 20.f, 35.f, 50.f, 65.f, 80.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_5) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 2, 3}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,2}, {1.f, 7.f, 5.f, 2.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_6) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(0);
|
|
NDArray exp = NDArrayFactory::create(1.f);//NDArrayFactory::create<float>('c', {2,2}, {1.f, 4.f, 7.f, 10.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_06) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(4);
|
|
NDArray exp = NDArrayFactory::create(8.f);//NDArrayFactory::create<float>('c', {2,2}, {1.f, 4.f, 7.f, 10.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_7) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2309f,
|
|
0.7271f, 0.1804f, 0.5056f, 0.8925f,
|
|
0.5461f, 0.9234f, 0.0856f, 0.7938f,
|
|
|
|
0.6591f, 0.5555f, 0.1596f, 0.3087f,
|
|
0.1548f, 0.4695f, 0.9939f, 0.6113f,
|
|
0.6765f, 0.1800f, 0.6750f, 0.2246f});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,3}, {0.7788f, 0.7271f, 0.7938f, 0.5555f, 0.6113f, 0.675f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_8) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2309f,
|
|
0.7271f, 0.1804f, 0.5056f, 0.8925f,
|
|
0.5461f, 0.9234f, 0.0856f, 0.7938f,
|
|
|
|
0.6591f, 0.5555f, 0.1596f, 0.3087f,
|
|
0.1548f, 0.4695f, 0.9939f, 0.6113f,
|
|
0.6765f, 0.1800f, 0.6750f, 0.2246f});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,3}, {0.7244f, 0.5056f, 0.5461f, 0.3087f, 0.4695f, 0.2246f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.evaluate({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test1) {
|
|
|
|
auto input = NDArrayFactory::create<Nd4jLong>('c', {3});
|
|
auto shape = NDArrayFactory::create<int>('c', {2}, {3, 3});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {3,3}, {1, 2, 3,1, 2, 3, 1, 2, 3});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test2) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {1,3});
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {1.f, 2.f, 3.f,1.f, 2.f, 3.f,1.f, 2.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test3) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3,1});
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.);
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {10.f, 10.f, 10.f,10.f, 10.f, 10.f, 10.f, 10.f, 10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<double>('c', {1}, {3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3}, {10.f, 10.f, 10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test6) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<double>(1.f);
|
|
auto exp = NDArrayFactory::create<double>('c', {1}, {10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test7) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<Nd4jLong>(1);
|
|
auto exp = NDArrayFactory::create<double>('c', {1}, {10.});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test8) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3});
|
|
auto shape = NDArrayFactory::create<double>('c', {3}, {1.f, 3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,3}, {1.f, 2.f, 3.f,1.f, 2.f, 3.f,1.f, 2.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test9) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,1,1});
|
|
auto shape = NDArrayFactory::create<double>('c', {5}, {2.f,1.f,5.f,1.f,3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {2,1,5,1,3}, {1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f,4.f, 4.f, 4.f,5.f, 5.f, 5.f,
|
|
1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f,4.f, 4.f, 4.f,5.f, 5.f, 5.f});
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test10) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,1,3});
|
|
auto shape = NDArrayFactory::create<double>('c', {5}, {2.f,1.f,5.f,1.f,3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {2,1,5,1,3}, {1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f,10.f, 11.f, 12.f,13.f, 14.f, 15.f,
|
|
1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f,10.f, 11.f, 12.f,13.f, 14.f, 15.f});
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.evaluate({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
|
|
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
|
|
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
|
|
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
|
|
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
|
|
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
|
|
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
|
|
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
|
|
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
|
|
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
|
|
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
|
|
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
|
|
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
|
|
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
|
|
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
|
|
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {10, 10});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
//result->printIndexedBuffer("Resized to 10x10");
|
|
//expected.printIndexedBuffer("Expect for 10x10");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test_11) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {1, 1, 1, 256});
|
|
|
|
input.assign(0.8f); //linspace(1);
|
|
auto size = NDArrayFactory::create<int>({65,65});
|
|
auto ex = NDArrayFactory::create<float>('c', {1,65,65,256});
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input, &size}, {}, {}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
ASSERT_NE(*result, ex);
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test_12) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {1, 1, 1, 256});
|
|
|
|
input.assign(0.8f); //linspace(1);
|
|
auto size = NDArrayFactory::create<int>({65,65});
|
|
auto ex = NDArrayFactory::create<float>('c', {1,65,65,256});
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input, &size}, {}, {}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
ASSERT_NE(*result, ex);
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 4, 5, 4}, {
|
|
1., 2., 3., 4.,
|
|
2.6, 3.6, 4.6, 5.6,
|
|
5., 6., 7., 8.,
|
|
7.4, 8.4, 9.4, 10.4,
|
|
9., 10., 11., 12.,
|
|
|
|
4., 5., 6., 7.,
|
|
5.6, 6.6, 7.6, 8.6,
|
|
8., 9., 10., 11.,
|
|
10.4, 11.4, 12.4, 13.4,
|
|
12., 13., 14., 15.,
|
|
|
|
10., 11., 12., 13.,
|
|
11.6, 12.6, 13.6, 14.6,
|
|
14., 15., 16., 17.,
|
|
16.4, 17.4, 18.4, 19.4,
|
|
18., 19., 20., 21.,
|
|
|
|
13., 14., 15., 16.,
|
|
14.6, 15.6, 16.6, 17.6,
|
|
17., 18., 19., 20.,
|
|
19.4, 20.4, 21.4, 22.4,
|
|
21., 22., 23., 24.
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {4, 5}, {false, true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printIndexedBuffer("Resized to 4x5 bilinear with half pixels");
|
|
//expected.printIndexedBuffer("Expect for 10x10");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1_2) {
|
|
|
|
NDArray input = NDArrayFactory::create<int>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1, 4, 5, 4}, {
|
|
1.f, 2.f, 3.f, 4.f,
|
|
2.6f, 3.6f, 4.6f, 5.6f,
|
|
5.f, 6.f, 7.f, 8.f,
|
|
7.4f, 8.4f, 9.4f, 10.4f,
|
|
9.f, 10.f, 11.f, 12.f,
|
|
|
|
4.f, 5.f, 6.f, 7.f,
|
|
5.6f, 6.6f, 7.6f, 8.6f,
|
|
8.f, 9.f, 10.f, 11.f,
|
|
10.4f, 11.4f, 12.4f, 13.4f,
|
|
12.f, 13.f, 14.f, 15.f,
|
|
|
|
10.f, 11.f, 12.f, 13.f,
|
|
11.6f, 12.6f, 13.6f, 14.6f,
|
|
14.f, 15.f, 16.f, 17.f,
|
|
16.4f, 17.4f, 18.4f, 19.4f,
|
|
18.f, 19.f, 20.f, 21.f,
|
|
|
|
13.f, 14.f, 15.f, 16.f,
|
|
14.6f, 15.6f, 16.6f, 17.6f,
|
|
17.f, 18.f, 19.f, 20.f,
|
|
19.4f, 20.4f, 21.4f, 22.4f,
|
|
21.f, 22.f, 23.f, 24.f
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {4, 5}, {false, true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printBuffer("Resized to 4x5");
|
|
// expected.printBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test01) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {2,3,4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
|
|
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
|
|
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
|
|
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
|
|
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
|
|
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
|
|
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
|
|
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
|
|
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
|
|
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
|
|
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
|
|
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
|
|
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
|
|
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
|
|
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
|
|
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {10, 10});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
//result->printIndexedBuffer("Resized to 10x10");
|
|
//expected.printIndexedBuffer("Expect for 10x10");
|
|
// result->printShapeInfo("Output shape");
|
|
// expected.printShapeInfo("Expect shape");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test02) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 5,5,3}, {
|
|
0.7788f, 0.8012f, 0.7244f,
|
|
0.2309f, 0.7271f, 0.1804f,
|
|
0.5056f, 0.8925f, 0.5461f,
|
|
0.9234f, 0.0856f, 0.7938f,
|
|
0.6591f, 0.5555f, 0.1596f,
|
|
0.3087f, 0.1548f, 0.4695f,
|
|
0.9939f, 0.6113f, 0.6765f,
|
|
0.1800f, 0.6750f, 0.2246f,
|
|
0.0509f, 0.4601f, 0.8284f,
|
|
0.2354f, 0.9752f, 0.8361f,
|
|
0.2585f, 0.4189f, 0.7028f,
|
|
0.7679f, 0.5373f, 0.7234f,
|
|
0.2690f, 0.0062f, 0.0327f,
|
|
0.0644f, 0.8428f, 0.7494f,
|
|
0.0755f, 0.6245f, 0.3491f,
|
|
0.5793f, 0.5730f, 0.1822f,
|
|
0.6420f, 0.9143f, 0.3019f,
|
|
0.3574f, 0.1704f, 0.8395f,
|
|
0.5468f, 0.0744f, 0.9011f,
|
|
0.6574f, 0.4124f, 0.2445f,
|
|
0.4248f, 0.5219f, 0.6952f,
|
|
0.4900f, 0.2158f, 0.9549f,
|
|
0.1386f, 0.1544f, 0.5365f,
|
|
0.0134f, 0.4163f, 0.1456f,
|
|
0.4109f, 0.2484f, 0.3330f,
|
|
0.2974f, 0.6636f, 0.3808f,
|
|
0.8664f, 0.1896f, 0.7530f,
|
|
0.7215f, 0.6612f, 0.7270f,
|
|
0.5704f, 0.2666f, 0.7453f,
|
|
0.0444f, 0.3024f, 0.4850f,
|
|
0.7982f, 0.0965f, 0.7843f,
|
|
0.5075f, 0.0844f, 0.8370f,
|
|
0.6103f, 0.4604f, 0.6087f,
|
|
0.8594f, 0.4599f, 0.6714f,
|
|
0.2744f, 0.1981f, 0.4143f,
|
|
0.7821f, 0.3505f, 0.5040f,
|
|
0.1180f, 0.8307f, 0.1817f,
|
|
0.8442f, 0.5074f, 0.4471f,
|
|
0.5105f, 0.6666f, 0.2576f,
|
|
0.2341f, 0.6801f, 0.2652f,
|
|
0.5394f, 0.4690f, 0.6146f,
|
|
0.1210f, 0.2576f, 0.0769f,
|
|
0.4643f, 0.1628f, 0.2026f,
|
|
0.3774f, 0.0506f, 0.3462f,
|
|
0.5720f, 0.0838f, 0.4228f,
|
|
0.0588f, 0.5362f, 0.4756f,
|
|
0.2530f, 0.1778f, 0.0751f,
|
|
0.8977f, 0.3648f, 0.3065f,
|
|
0.4739f, 0.7014f, 0.4473f,
|
|
0.5171f, 0.1744f, 0.3487f});
|
|
|
|
NDArray expected = NDArrayFactory::create<float>('c', {2, 9, 9, 3}, {
|
|
0.7788f, 0.8012f, 0.7244f, 0.4744111f, 0.7600333f, 0.42217776f,
|
|
0.26142225f, 0.7454778f, 0.22103335f, 0.41403335f, 0.8373667f, 0.42420003f,
|
|
0.59844446f, 0.71318877f, 0.6011445f, 0.83055556f, 0.264911f, 0.7387556f,
|
|
0.83529997f, 0.2422334f, 0.5823999f, 0.6884666f, 0.5032889f, 0.23006654f,
|
|
0.6591f, 0.5555f, 0.1596f, 0.5176333f, 0.44208887f , 0.5827889f,
|
|
0.5938309f, 0.5646876f, 0.5123568f, 0.61811364f, 0.6748667f, 0.44617534f,
|
|
0.43473703f, 0.7353667f, 0.3969963f, 0.35003704f, 0.6654419f, 0.46649635f,
|
|
0.41335183f, 0.39988017f, 0.7140149f, 0.43368888f, 0.45865932f, 0.72049254f,
|
|
0.42537406f, 0.73366547f, 0.5662765f, 0.42371112f, 0.78866667f, 0.53543335f,
|
|
0.30312222f, 0.18414445f, 0.49542224f, 0.67293704f, 0.4168852f, 0.59891605f,
|
|
0.8822444f, 0.60281235f, 0.62855184f, 0.4495222f, 0.6014852f, 0.36275554f,
|
|
0.15933579f, 0.5788963f, 0.34024328f, 0.08295307f, 0.52441484f, 0.6826569f,
|
|
0.10747781f, 0.64715934f, 0.80707777f, 0.19927411f, 0.8880544f, 0.7861703f,
|
|
0.21763334f, 0.9362333f, 0.78198886f, 0.27523333f, 0.3308667f, 0.6250333f,
|
|
0.5907889f, 0.45925558f, 0.6709963f, 0.7761333f, 0.5249852f, 0.63986665f,
|
|
0.4406333f, 0.34007773f, 0.3003666f, 0.19945924f, 0.33715558f, 0.24757043f,
|
|
0.09977405f, 0.60721123f, 0.6248297f, 0.08286668f, 0.7239556f, 0.6876333f,
|
|
0.12114445f, 0.73849255f ,0.54079986f, 0.12879999f, 0.74139994f, 0.51143324f,
|
|
0.32978892f, 0.45314446f, 0.58711106f, 0.5576408f, 0.5464408f, 0.6107901f,
|
|
0.68978024f, 0.55681235f, 0.5833172f, 0.43907034f, 0.23548517f, 0.35123706f,
|
|
0.26263458f, 0.18254575f, 0.33890504f, 0.1976099f, 0.5321877f, 0.65619516f,
|
|
0.18267044f, 0.6404851f, 0.63069254f, 0.20112106f, 0.58788633f, 0.37666163f,
|
|
0.20481117f, 0.57736665f, 0.32585555f, 0.50801116f, 0.5387556f, 0.29788882f,
|
|
0.59799266f, 0.7008482f, 0.35215425f, 0.6330642f, 0.753121f, 0.42497158f,
|
|
0.44849625f, 0.36611477f, 0.5719964f, 0.36038768f, 0.1586321f, 0.70625067f,
|
|
0.416968f, 0.22043455f, 0.82134944f, 0.4690964f, 0.31661478f, 0.6675073f,
|
|
0.5182569f, 0.4357136f, 0.33437145f, 0.528089f, 0.4595333f, 0.26774442f,
|
|
0.52779996f, 0.5559667f, 0.35320008f, 0.5630963f, 0.62568885f, 0.44562602f,
|
|
0.557237f, 0.62408876f, 0.5438927f, 0.3867555f, 0.3371999f, 0.6655223f,
|
|
0.30325183f, 0.17024446f, 0.71867025f, 0.35021478f, 0.18318895f, 0.6690962f,
|
|
0.4377444f, 0.24482228f, 0.5241777f, 0.5523185f, 0.33891484f, 0.3156962f,
|
|
0.5752333f, 0.3577333f, 0.27400002f, 0.44196665f, 0.52757776f, 0.6382001f,
|
|
0.47803456f, 0.3974851f, 0.7738359f, 0.4686691f, 0.27816284f, 0.8476581f,
|
|
0.2775703f, 0.20192216f, 0.6742259f, 0.14285672f, 0.20554078f, 0.4944727f,
|
|
0.0927209f, 0.32894826f, 0.30523813f, 0.19454071f, 0.3410815f, 0.26075178f,
|
|
0.3976642f, 0.27903205f, 0.31276423f, 0.43828884f, 0.2666222f, 0.32316667f,
|
|
0.4248f, 0.5219f, 0.6952f, 0.46102223f, 0.35184443f, 0.8394778f,
|
|
0.45095554f, 0.20897777f, 0.9084111f, 0.2557333f, 0.17486666f, 0.6759666f,
|
|
0.11077777f, 0.21260004f, 0.44963327f, 0.04122221f, 0.35810006f, 0.23246664f,
|
|
0.14590007f, 0.36033332f, 0.2080667f, 0.3667334f, 0.2670555f, 0.31217784f,
|
|
0.4109f, 0.2484f, 0.333f, 0.2974f, 0.6636f, 0.3808f,
|
|
0.6135111f, 0.40026665f, 0.5875778f, 0.8503f, 0.24200003f, 0.7501111f,
|
|
0.76979995f, 0.50400007f, 0.7356667f, 0.6879222f, 0.57351106f, 0.73106664f,
|
|
0.60397774f, 0.35428885f, 0.74123335f, 0.39506656f, 0.27853334f, 0.6585333f,
|
|
0.10284433f, 0.29842222f, 0.5139222f, 0.0444f, 0.3024f, 0.485f,
|
|
0.5756222f, 0.34854442f, 0.6049667f, 0.6263938f, 0.22777282f, 0.71313334f,
|
|
0.66620123f, 0.17765433f, 0.78429013f, 0.6621518f, 0.41014817f, 0.7074074f,
|
|
0.67555183f, 0.51060987f, 0.6708259f, 0.7151259f, 0.41302344f, 0.6946963f,
|
|
0.5446962f, 0.33081108f, 0.6180703f, 0.23426408f, 0.25884813f, 0.4744469f,
|
|
0.17217779f, 0.24445555f, 0.44572222f, 0.7964111f, 0.12472223f, 0.7531556f,
|
|
0.6118617f, 0.1483889f, 0.75928515f, 0.4833407f, 0.2004667f, 0.7449173f,
|
|
0.57893336f, 0.3661889f, 0.6485592f, 0.6772543f, 0.46945432f, 0.5984506f,
|
|
0.7796679f, 0.47903457f, 0.617716f, 0.63706285f, 0.40579626f, 0.54952586f,
|
|
0.33111224f, 0.27734566f, 0.42303205f, 0.26992223f, 0.25165558f, 0.39773333f,
|
|
0.7874667f, 0.26583335f, 0.5974333f, 0.4876703f, 0.44144446f, 0.48782218f,
|
|
0.30543333f, 0.57191116f, 0.41133702f, 0.5934334f, 0.5218f, 0.46735552f,
|
|
0.73524815f, 0.5152815f, 0.47753704f, 0.6577852f, 0.5741519f, 0.41896293f,
|
|
0.50037766f, 0.57161117f, 0.3686555f, 0.28967398f, 0.5281297f, 0.3238592f,
|
|
0.24753332f, 0.5194334f, 0.31489998f, 0.72816664f, 0.37683335f, 0.5285778f,
|
|
0.3895555f, 0.5582283f, 0.32292962f, 0.18990126f, 0.6730641f, 0.18445063f,
|
|
0.5460741f, 0.5216629f, 0.31464812f, 0.6978098f, 0.45279747f, 0.36710492f,
|
|
0.5428901f, 0.5077358f, 0.30295062f, 0.42367774f, 0.53567034f, 0.28493333f,
|
|
0.32827038f, 0.54560244f, 0.2976741f, 0.30918893f, 0.5475888f, 0.30022222f,
|
|
0.5933333f, 0.44266668f, 0.59002227f, 0.3305555f, 0.4106049f, 0.31789258f,
|
|
0.16793211f, 0.36878017f, 0.11760493f, 0.40592593f, 0.28790364f, 0.20468517f,
|
|
0.5172234f, 0.22784683f, 0.27239504f, 0.4384765f, 0.19901967f, 0.3110494f,
|
|
0.43695557f, 0.19709623f, 0.34693336f, 0.4869186f, 0.21310854f, 0.38097042f,
|
|
0.49691117f, 0.21631104f, 0.3877778f, 0.37919992f, 0.4914f, 0.56826663f,
|
|
0.26019996f, 0.34673333f, 0.29495183f, 0.21430746f, 0.23090371f, 0.09418149f,
|
|
0.46084452f, 0.23042224f, 0.1835889f, 0.56450003f, 0.23844449f, 0.26893705f,
|
|
0.45383334f, 0.2592223f, 0.34819633f, 0.45761114f, 0.21635559f, 0.38596666f,
|
|
0.5376852f, 0.13105926f, 0.39607778f, 0.55370003f, 0.11400001f, 0.3981f,
|
|
0.11219993f, 0.5287333f, 0.49104443f, 0.18227404f, 0.3386963f, 0.26007527f,
|
|
0.30624574f, 0.20396544f, 0.09970618f, 0.6458075f, 0.2904593f, 0.22173704f,
|
|
0.7636852f, 0.40607417f, 0.32631359f, 0.549037f, 0.5653705f, 0.40470868f,
|
|
0.4831852f, 0.47417036f, 0.40968886f, 0.5165309f, 0.21597281f, 0.3657259f,
|
|
0.5232f, 0.16433334f, 0.3569333f, 0.0588f, 0.5362f, 0.4756f,
|
|
0.16668889f, 0.33708888f, 0.25309998f, 0.32463336f, 0.19857779f, 0.10081112f,
|
|
0.68280005f, 0.3024667f, 0.22936666f, 0.80352217f, 0.43960005f, 0.33778888f,
|
|
0.5680777f, 0.6266f, 0.41601112f, 0.4883f, 0.52573323f, 0.4144333f,
|
|
0.5123f, 0.23295549f, 0.35965553f, 0.5171f, 0.1744f, 0.3487f
|
|
});
|
|
//input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {9, 9});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printBuffer("Resized to 9x9");
|
|
// expected.printBuffer("Expect for 9x9");
|
|
// result->printShapeInfo("Output shape");
|
|
// expected.printShapeInfo("Expect shape");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test2) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
NDArray size = NDArrayFactory::create<int>({10, 10});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
|
|
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
|
|
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
|
|
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
|
|
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
|
|
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
|
|
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
|
|
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
|
|
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
|
|
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
|
|
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
|
|
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
|
|
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
|
|
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
|
|
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
|
|
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input, &size}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test3) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4},
|
|
{ 1., 2., 3., 4. ,
|
|
1.8888888, 2.8888888, 3.8888888, 4.888889,
|
|
2.7777777, 3.7777777, 4.7777777, 5.7777777,
|
|
3.6666667, 4.666667 , 5.666667, 6.666667 ,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111111, 11.111111,
|
|
9., 10., 11., 12.,
|
|
|
|
2.3333335, 3.3333335, 4.3333335, 5.3333335,
|
|
3.2222223, 4.2222223, 5.2222223, 6.2222223,
|
|
4.111111, 5.111111, 6.111111, 7.111111,
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888888,
|
|
6.777778, 7.777778, 8.777778, 9.777778,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444444, 10.444444, 11.444444, 12.444444,
|
|
10.333333, 11.333333, 12.333333, 13.333333,
|
|
|
|
3.6666667, 4.666667, 5.666667, 6.666667,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445 ,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334 ,
|
|
7.2222223, 8.222222, 9.222222, 10.222222 ,
|
|
8.111112, 9.111112, 10.111112, 11.111112 ,
|
|
9., 10., 11.000001, 12.000001 ,
|
|
9.888889, 10.888889, 11.888889, 12.888889 ,
|
|
10.777778, 11.777778, 12.777778, 13.777778 ,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888889,
|
|
6.7777777, 7.7777777, 8.777779, 9.777779,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111111, 13.111111, 14.111111, 15.111111,
|
|
13., 14., 15., 16.,
|
|
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111112, 11.111112,
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777779, 11.777779, 12.777779, 13.777779,
|
|
11.666667, 12.666667, 13.666668, 14.666668,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13., 14., 15.0, 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666668, 17.666668, 18.666668,
|
|
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777778, 11.777778, 12.777779, 13.777779,
|
|
11.666667, 12.666666, 13.666666, 14.666666,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
15.222221, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222223, 12.222223, 13.222223, 14.222223,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13.000001, 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777779, 15.777779, 16.777779, 17.777779,
|
|
15.666668, 16.666668, 17.666668, 18.666668,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444446, 16.444447,
|
|
14.333334, 15.333333, 16.333332, 17.333332,
|
|
15.222222, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
17.88889, 18.88889, 19.88889, 20.88889,
|
|
18.777779, 19.777779, 20.777779, 21.777779,
|
|
19.666668, 20.666668, 21.666668, 22.666668,
|
|
|
|
13., 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666666, 17.666666, 18.666666,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
19.222221, 20.222221, 21.222221, 22.222221,
|
|
20.11111, 21.11111, 22.11111, 23.11111,
|
|
21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input}, {}, {10, 10}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test4) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
NDArray size = NDArrayFactory::create<int>({10, 10});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4},
|
|
{ 1., 2., 3., 4. ,
|
|
1.8888888, 2.8888888, 3.8888888, 4.888889,
|
|
2.7777777, 3.7777777, 4.7777777, 5.7777777,
|
|
3.6666667, 4.666667 , 5.666667, 6.666667 ,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111111, 11.111111,
|
|
9., 10., 11., 12.,
|
|
|
|
2.3333335, 3.3333335, 4.3333335, 5.3333335,
|
|
3.2222223, 4.2222223, 5.2222223, 6.2222223,
|
|
4.111111, 5.111111, 6.111111, 7.111111,
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888888,
|
|
6.777778, 7.777778, 8.777778, 9.777778,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444444, 10.444444, 11.444444, 12.444444,
|
|
10.333333, 11.333333, 12.333333, 13.333333,
|
|
|
|
3.6666667, 4.666667, 5.666667, 6.666667,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445 ,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334 ,
|
|
7.2222223, 8.222222, 9.222222, 10.222222 ,
|
|
8.111112, 9.111112, 10.111112, 11.111112 ,
|
|
9., 10., 11.000001, 12.000001 ,
|
|
9.888889, 10.888889, 11.888889, 12.888889 ,
|
|
10.777778, 11.777778, 12.777778, 13.777778 ,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888889,
|
|
6.7777777, 7.7777777, 8.777779, 9.777779,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111111, 13.111111, 14.111111, 15.111111,
|
|
13., 14., 15., 16.,
|
|
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111112, 11.111112,
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777779, 11.777779, 12.777779, 13.777779,
|
|
11.666667, 12.666667, 13.666668, 14.666668,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13., 14., 15.0, 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666668, 17.666668, 18.666668,
|
|
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777778, 11.777778, 12.777779, 13.777779,
|
|
11.666667, 12.666666, 13.666666, 14.666666,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
15.222221, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222223, 12.222223, 13.222223, 14.222223,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13.000001, 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777779, 15.777779, 16.777779, 17.777779,
|
|
15.666668, 16.666668, 17.666668, 18.666668,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444446, 16.444447,
|
|
14.333334, 15.333333, 16.333332, 17.333332,
|
|
15.222222, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
17.88889, 18.88889, 19.88889, 20.88889,
|
|
18.777779, 19.777779, 20.777779, 21.777779,
|
|
19.666668, 20.666668, 21.666668, 22.666668,
|
|
|
|
13., 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666666, 17.666666, 18.666666,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
19.222221, 20.222221, 21.222221, 22.222221,
|
|
20.11111, 21.11111, 22.11111, 23.11111,
|
|
21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.evaluate({&input, &size}, {}, {}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printIndexedBuffer("Resized to 10x10");
|
|
// expected.printIndexedBuffer("Expected of 10x10");
|
|
// result->printShapeInfo("Resized to 10x10 shape");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, LinSpace_Test1) {
|
|
|
|
NDArray start = NDArrayFactory::create<double>(1.);
|
|
NDArray finish = NDArrayFactory::create<double>(12.);
|
|
NDArray num = NDArrayFactory::create<int>(23);
|
|
NDArray expect = NDArrayFactory::create<double>({1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5,
|
|
8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5, 12.});
|
|
|
|
nd4j::ops::lin_space op;
|
|
auto result = op.evaluate({&start, &finish, &num}, {}, {});
|
|
ASSERT_EQ(result->status(), ND4J_STATUS_OK);
|
|
auto res = result->at(0);
|
|
|
|
ASSERT_TRUE(expect.equalsTo(res));
|
|
delete result;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 4, 5, 4}, {
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_nearest_neighbor op;
|
|
auto results = op.evaluate({&input}, {}, {4, 5}, {false, false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printIndexedBuffer("Resized to 4x5");
|
|
// expected.printIndexedBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<int>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<int>('c', {1, 4, 5, 4}, {
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_nearest_neighbor op;
|
|
auto results = op.evaluate({&input}, {}, {4, 5});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printIndexedBuffer("Resized to 4x5");
|
|
// expected.printIndexedBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1_1_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1, 4, 5, 4}, {
|
|
1.f, 2.f, 3.f, 4.f,
|
|
1.f, 2.f, 3.f, 4.f,
|
|
5.f, 6.f, 7.f, 8.f,
|
|
9.f, 10.f, 11.f, 12.f,
|
|
9.f, 10.f, 11.f, 12.f,
|
|
|
|
1.f, 2.f, 3.f, 4.f,
|
|
1.f, 2.f, 3.f, 4.f,
|
|
5.f, 6.f, 7.f, 8.f,
|
|
9.f, 10.f, 11.f, 12.f,
|
|
9.f, 10.f, 11.f, 12.f,
|
|
|
|
13.f, 14.f, 15.f, 16.f,
|
|
13.f, 14.f, 15.f, 16.f,
|
|
17.f, 18.f, 19.f, 20.f,
|
|
21.f, 22.f, 23.f, 24.f,
|
|
21.f, 22.f, 23.f, 24.f,
|
|
|
|
13.f, 14.f, 15.f, 16.f,
|
|
13.f, 14.f, 15.f, 16.f,
|
|
17.f, 18.f, 19.f, 20.f,
|
|
21.f, 22.f, 23.f, 24.f,
|
|
21.f, 22.f, 23.f, 24.f
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_nearest_neighbor op;
|
|
auto results = op.evaluate({&input}, {}, {4,5}, {false, true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
// result->printIndexedBuffer("Resized to 4x5");
|
|
// expected.printBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test01) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {4, 5, 4}, { 1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_nearest_neighbor op;
|
|
auto results = op.evaluate({&input}, {}, {4, 5});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
//result->printIndexedBuffer("Resized to 4x5");
|
|
//expected.printIndexedBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double> ('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<double>(2.5206409f);
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.evaluate({&input}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_2) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<double>({1.0986123f, 1.8619947f, 1.0986123f});
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.evaluate({&input}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("REDUCE_LOGSUMEXP");
|
|
// expected.printIndexedBuffer("LSE EXPECTED");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_3) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,3}, {1.0986123f, 1.8619947f, 1.0986123f});
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.evaluate({&input}, {1.f}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("REDUCE_LOGSUMEXP");
|
|
// expected.printIndexedBuffer("LSE EXPECTED");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_1) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {3,4});
|
|
NDArray scores = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3}, {2, 1, 0});
|
|
boxes.linspace(1.f);
|
|
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.evaluate({&boxes, &scores}, {}, {3});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
//result->printIndexedBuffer("OOOOUUUUTTT");
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_2) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {6,4}, {0, 0, 1, 1, 0, 0.1f, 1, 1.1f, 0, -0.1f, 1.f, 0.9f,
|
|
0, 10, 1, 11, 0, 10.1f, 1.f, 11.1f, 0, 100, 1, 101});
|
|
NDArray scales = NDArrayFactory::create<double>('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3}, {3,0,5});
|
|
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.evaluate({&boxes, &scales}, {0.5}, {3});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput2");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_3) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
|
|
0.7412f, 0.7607f, 0.1543f, 0.5479f,
|
|
0.8223f, 0.2246f, 0.0049f, 0.6465f});
|
|
NDArray scales = NDArrayFactory::create<float>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {1}, {1});
|
|
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.evaluate({&boxes, &scales}, {0.5, 0.5}, {2});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput3");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_4) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
|
|
0.7412f, 0.7607f, 0.1543f, 0.5479f,
|
|
0.8223f, 0.2246f, 0.0049f, 0.6465f});
|
|
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {1}, {1});
|
|
NDArray maxSize = NDArrayFactory::create(2);
|
|
NDArray threshold = NDArrayFactory::create(0.5f);
|
|
NDArray scoreThreshold = NDArrayFactory::create(0.5);
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.evaluate({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput4");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_5) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
|
|
0.7412f, 0.7607f, 0.1543f, 0.5479f,
|
|
0.8223f, 0.2246f, 0.0049f, 0.6465f});
|
|
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1, 2});
|
|
NDArray maxSize = NDArrayFactory::create(2);
|
|
NDArray threshold = NDArrayFactory::create(0.5f);
|
|
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.evaluate({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput4");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_6) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
|
|
0.7412f, 0.7607f, 0.1543f, 0.5479f,
|
|
0.8223f, 0.2246f, 0.0049f, 0.6465f});
|
|
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1,2});
|
|
NDArray maxSize = NDArrayFactory::create(2);
|
|
NDArray threshold = NDArrayFactory::create(0.5f);
|
|
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
|
|
nd4j::ops::non_max_suppression_v3 op;
|
|
auto results = op.evaluate({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput6");
|
|
// result->printShapeInfo("Ouput6 shape is");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_06) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<bfloat16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
|
|
0.7412f, 0.7607f, 0.1543f, 0.5479f,
|
|
0.8223f, 0.2246f, 0.0049f, 0.6465f});
|
|
NDArray scales = NDArrayFactory::create<bfloat16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1,2});
|
|
NDArray maxSize = NDArrayFactory::create(2);
|
|
NDArray threshold = NDArrayFactory::create(0.5f);
|
|
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
|
|
nd4j::ops::non_max_suppression_v3 op;
|
|
auto results = op.evaluate({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput06");
|
|
// result->printShapeInfo("Ouput06 shape is");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_7) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2329f,
|
|
0.7271f, 0.1804f, 0.5056f, 0.8929f,
|
|
0.5461f, 0.9234f, 0.0856f, 0.7938f});
|
|
NDArray scales = NDArrayFactory::create<float>('c', {3}, {0.7717f, 0.9281f, 0.9846f}); //3, 0, 1, 2, 4, 5
|
|
NDArray maxSize = NDArrayFactory::create(0);
|
|
NDArray threshold = NDArrayFactory::create(0.5f);
|
|
NDArray scoreThreshold = NDArrayFactory::create(0.5f);
|
|
nd4j::ops::non_max_suppression_v3 op;
|
|
auto results = op.evaluate({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput7");
|
|
// result->printShapeInfo("Ouput6 shape is");
|
|
ASSERT_TRUE(result->isEmpty());
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_1) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.9, .75, .6, .95}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(3);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {1,}, {3});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.evaluate({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap1 Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_2) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.9, .95, .6, .75}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(3);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3,}, {1,1,1});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.evaluate({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_3) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.5, .95, -.6, .75}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(5);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {5,}, {1,1,1,1,1});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.evaluate({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_1) {
|
|
int axis = 0;
|
|
NDArray images = NDArrayFactory::create<double>('c', {1,2,2,1}, {1,2,3,4});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1,4}, {0,0,1,1});
|
|
NDArray boxI = NDArrayFactory::create<int>('c', {1}, {axis});
|
|
NDArray cropSize = NDArrayFactory::create<int>({1, 1});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1,1,1,1}, {2.5f});
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.evaluate({&images, &boxes, &boxI, &cropSize}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Cropped and Resized");
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_2) {
|
|
int axis = 0;
|
|
NDArray images = NDArrayFactory::create<float>('c', {1,2,2,1}, {1.f, 2.f, 3.f, 4.f});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1,4}, {0.f, 0.f, 1.f, 1.f});
|
|
NDArray boxI = NDArrayFactory::create<int>('c', {1}, {axis});
|
|
NDArray cropSize = NDArrayFactory::create<int>({1, 1});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,1,1,1}, {4.f});
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.evaluate({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_3) {
|
|
|
|
NDArray images ('c', {1,2,2,1}, {1,2,3,4}, nd4j::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, std::vector<double>{0}, nd4j::DataType::INT64);
|
|
NDArray cropSize = NDArrayFactory::create<Nd4jLong>({3, 3});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1,3,3,1}, {1.f, 1.5f, 2., 2.f, 2.5f, 3.f, 3.f, 3.5f, 4.f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.evaluate({&images, &boxes, &boxI, &cropSize}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_4) {
|
|
|
|
NDArray images('c', {1,2,2,1}, {1, 2, 3, 4}, nd4j::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, std::vector<double>({0.}), nd4j::DataType::INT32);
|
|
NDArray cropSize = NDArrayFactory::create<int>({3, 3});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1,3,3,1}, {1.f, 2.f, 2.f, 3.f, 4, 4.f, 3.f, 4.f, 4.f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.evaluate({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_5) {
|
|
|
|
NDArray images('c', {1, 100, 100, 3}, nd4j::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {2}, {1,1}, nd4j::DataType::INT32);
|
|
NDArray cropSize = NDArrayFactory::create<int>({10, 10});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1, 10, 10,3}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.evaluate({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
//ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_1) {
|
|
NDArray images = NDArrayFactory::create<float>('c', {2,4,5,3});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {
|
|
0.f , 0.f , 1.f , 1.f , 0.1f, 0.2f, 0.9f, 0.8f,
|
|
0.3f, 0.3f, 0.7f, 0.7f, 0.4f, 0.4f, 0.6f, 0.6f
|
|
});
|
|
|
|
NDArray colors = NDArrayFactory::create<float>('c', {2, 3}, {201.f, 202.f, 203.f, 127.f, 128.f, 129.f});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {2,4,5,3}, {
|
|
127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
|
|
127.f, 128.f, 129.f, 19.f, 20.f, 21.f, 22.f, 23.f, 24.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
|
|
127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
|
|
201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f,
|
|
|
|
61.f, 62.f, 63.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 70.f, 71.f, 72.f, 73.f, 74.f, 75.f,
|
|
76.f, 77.f, 78.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 85.f, 86.f, 87.f, 88.f, 89.f, 90.f,
|
|
91.f, 92.f, 93.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 100.f, 101.f, 102.f, 103.f, 104.f, 105.f,
|
|
106.f, 107.f, 108.f, 109.f, 110.f, 111.f, 112.f, 113.f, 114.f, 115.f, 116.f, 117.f, 118.f, 119.f, 120.f
|
|
});
|
|
images.linspace(1.);
|
|
nd4j::ops::draw_bounding_boxes op;
|
|
auto results = op.evaluate({&images, &boxes, &colors}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->syncToHost();
|
|
// result->printBuffer("Bounded boxes");
|
|
// expected.printBuffer("Bounded expec");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_2) {
|
|
NDArray images = NDArrayFactory::create<float>('c', {1,9,9,1});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1, 1, 4}, {0.2f, 0.2f, 0.7f, 0.7f});
|
|
NDArray colors = NDArrayFactory::create<float>('c', {1, 1}, {0.95f});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,9,9,1}, {
|
|
1.1f , 2.1f, 3.1f, 4.1f, 5.1f, 6.1f, 7.1f , 8.1f , 9.1f ,
|
|
10.1f , 0.95f, 0.95f, 0.95f, 0.95f, 0.95f, 16.1f , 17.1f , 18.1f ,
|
|
19.1f , 0.95f, 21.1f, 22.1f, 23.1f, 0.95f, 25.1f , 26.1f , 27.1f ,
|
|
28.1f , 0.95f, 30.1f, 31.1f, 32.1f, 0.95f, 34.1f , 35.1f , 36.1f ,
|
|
37.1f , 0.95f, 39.1f, 40.1f, 41.1f, 0.95f, 43.1f , 44.1f , 45.1f ,
|
|
46.1f , 0.95f, 0.95f, 0.95f, 0.95f, 0.95f, 52.1f , 53.1f , 54.1f ,
|
|
55.1f , 56.1f, 57.1f, 58.1f, 59.1f , 60.1f, 61.1f , 62.1f , 63.1f ,
|
|
64.1f , 65.1f, 66.1f, 67.1f, 68.1f , 69.1f, 70.1f , 71.1f , 72.1f ,
|
|
73.1f , 74.1f, 75.1f, 76.1f, 77.1f , 78.1f, 79.1f , 80.1f , 81.1f });
|
|
images.linspace(1.1);
|
|
nd4j::ops::draw_bounding_boxes op;
|
|
auto results = op.evaluate({&images, &boxes, &colors}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->syncToHost();
|
|
// result->printBuffer("Bounded boxes 2");
|
|
// expected.printBuffer("Bounded expec 2");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_3) {
|
|
NDArray images = NDArrayFactory::create<float>('c', {2,5,5,1}, {0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f, 0.1804f,
|
|
0.5056f, 0.8925f, 0.5461f, 0.9234f, 0.0856f, 0.7938f,
|
|
0.6591f, 0.5555f, 0.1596f, 0.3087f, 0.1548f, 0.4695f,
|
|
0.9939f, 0.6113f, 0.6765f, 0.1800f, 0.6750f, 0.2246f,
|
|
0.0509f, 0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
|
|
0.2585f, 0.4189f, 0.7028f, 0.7679f, 0.5373f, 0.7234f,
|
|
0.2690f, 0.0062f, 0.0327f, 0.0644f, 0.8428f, 0.7494f,
|
|
0.0755f, 0.6245f, 0.3491f, 0.5793f, 0.5730f, 0.1822f,
|
|
0.6420f, 0.9143f});
|
|
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {0.7717f, 0.9281f, 0.9846f, 0.4838f,
|
|
0.6433f, 0.6041f, 0.6501f, 0.7612f,
|
|
0.7605f, 0.3948f, 0.9493f, 0.8600f,
|
|
0.7876f, 0.8945f, 0.4638f, 0.7157f});
|
|
NDArray colors = NDArrayFactory::create<float>('c', {1, 2}, {0.9441f, 0.5957f});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
// NDArray expected = NDArrayFactory::create<float>('c', {2,5,5,1}, {
|
|
// 0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f,
|
|
// 0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f, 0.0856f, 0.7938f, 0.9441f,
|
|
// 0.9441f, 0.1596f, 0.3087f, 0.1548f, 0.4695f, 0.9939f, 0.6113f, 0.6765f,
|
|
// 0.1800f, 0.6750f, 0.2246f, 0.0509f, 0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
|
|
// 0.2585f, 0.4189f,0.7028f,0.7679f,0.5373f,0.7234f,0.2690f,0.0062f,0.0327f,0.0644f,
|
|
// 0.8428f, 0.9441f,0.9441f,0.9441f,0.3491f,0.5793f,0.5730f,0.1822f,0.6420f,0.9143f });
|
|
NDArray expected = NDArrayFactory::create<float>('c', {2,5,5,1}, {
|
|
0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.9441f, 0.9441f, 0.1596f,
|
|
0.3087f, 0.1548f, 0.4695f, 0.9939f, 0.6113f,
|
|
0.6765f, 0.18f , 0.675f , 0.2246f, 0.0509f,
|
|
|
|
0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
|
|
0.2585f, 0.4189f, 0.7028f, 0.7679f, 0.5373f,
|
|
0.7234f, 0.269f , 0.0062f, 0.0327f, 0.0644f,
|
|
0.8428f, 0.9441f, 0.9441f, 0.9441f, 0.3491f,
|
|
0.5793f, 0.573f , 0.1822f, 0.642f , 0.9143f});
|
|
nd4j::ops::draw_bounding_boxes op;
|
|
auto results = op.evaluate({&images, &boxes, &colors}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Boxes3 output");
|
|
// expected.printBuffer("Boxes3 expect");
|
|
|
|
// result->syncToHost();
|
|
// result->printBuffer("Bounded boxes 2");
|
|
// expected.printBuffer("Bounded expec 2");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_1) {
|
|
|
|
NDArray x('c', {2,3}, {-63.80f, -63.75f, -63.70f, -63.5f, 0.0f, 0.1f}, nd4j::DataType::FLOAT32);
|
|
NDArray exp('c', {2,3}, {-63.75f, -63.75f, -63.75f, -63.5f, 0.f, 0.f}, nd4j::DataType::FLOAT32);
|
|
NDArray min('c', {}, std::vector<double>{-63.65f}, nd4j::DataType::FLOAT32);
|
|
NDArray max('c', {}, std::vector<double>{0.1f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized");
|
|
// exp.printBuffer("Expected");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_2) {
|
|
|
|
NDArray x = NDArrayFactory::create<double>('c', {2,3}, {-63.80, -63.75, -63.4, -63.5, 0.0, 0.1});
|
|
NDArray exp = NDArrayFactory::create<double>('c', {2,3}, {-63.75, -63.75, -63.5 , -63.5 , 0. , 0. });
|
|
NDArray min = NDArrayFactory::create<double>(-63.65);
|
|
NDArray max = NDArrayFactory::create<double>(0.1);
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized2");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_3) {
|
|
|
|
NDArray x = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.80, -63.75, -63.4, -63.5, 0.0, 0.1});
|
|
NDArray exp = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.75, -63.75, -63.5 , -63.5 , 0. , 0. });
|
|
NDArray min = NDArrayFactory::create<double>('c', {1},{-63.65});
|
|
NDArray max = NDArrayFactory::create<double>('c', {1}, {0.1});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized2");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
|
|
0.777002f, 0.596913f, 0.72314f, 0.231040f, 0.509824f,
|
|
0.179308f, 0.505282f, 0.86846f, 0.349958f, 0.509824f,
|
|
0.087355f, 0.596913f, 0.65740f, 0.349958f, 0.159745f});
|
|
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
|
|
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized03");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_1) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
|
|
0.780061f, 0.596635f, 0.725987f, 0.231950f, 0.508419f,
|
|
0.180014f, 0.504643f, 0.868406f, 0.351335f, 0.508419f,
|
|
0.087699f, 0.596635f, 0.659988f, 0.351335f, 0.160374f});
|
|
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
|
|
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {8}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized03_1");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_2) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
|
|
0.775297f, 0.592226f, 0.725763f, 0.237561f, 0.503245f,
|
|
0.189097f, 0.506084f, 0.868069f, 0.349355f, 0.503245f,
|
|
0.094548f, 0.592226f, 0.654610f, 0.349355f, 0.153769f});
|
|
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
|
|
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {6}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->printIndexedBuffer("Quantized03_2");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_3) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
|
|
0.781600f, 0.593422f, 0.728248f, 0.233790f, 0.509014f, 0.186095f, 0.508648f, 0.868295f, 0.343809f,
|
|
0.509014f, 0.093048f, 0.593422f, 0.658224f, 0.343809f, 0.165086f});
|
|
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
|
|
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {6}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->printIndexedBuffer("Quantized03_3");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
|
|
|
|
NDArray x = NDArrayFactory::create<float>('c', {2,4,5,3});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,4,5,3},{
|
|
1.0588236f, 1.9607843f, 3.019608f, 4.0588236f, 5.098039f, 6.039216f, 7.0588236f, 8.039216f, 9.058824f,
|
|
10.058824f, 10.980392f, 12.078432f, 13.058824f, 13.921569f, 15.09804f, 16.058825f, 17.058825f, 18.117647f,
|
|
19.058825f, 20.f, 21.137257f, 22.058825f, 22.941177f, 23.882355f, 25.058825f, 26.078432f, 26.901962f,
|
|
28.058825f, 29.019608f, 29.92157f, 31.058825f, 31.960785f, 32.941177f, 34.058823f, 35.09804f, 35.960785f,
|
|
37.058823f, 38.039215f, 38.980392f, 40.058823f, 40.980392f, 42.000004f, 43.058826f, 43.92157f, 45.01961f,
|
|
45.f, 47.058823f, 48.03922f, 45.f, 50.f, 51.058826f, 45.f, 50.f, 54.078434f,
|
|
45.f, 50.f, 57.09804f, 45.f, 50.f, 60.11765f, 45.f, 50.f, 62.862747f,
|
|
45.f, 50.f, 65.882355f, 45.f, 50.f, 68.90196f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
|
|
45.f, 50.f, 70.f});
|
|
NDArray min = NDArrayFactory::create<float>({20.f, 20.f, 20.f});
|
|
NDArray max = NDArrayFactory::create<float>({65.f, 70.f, 90.f});
|
|
x.linspace(1.);
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized per channels 4");
|
|
// exp.printBuffer("Quantized per channest E");
|
|
// auto diff = *result - exp;
|
|
// diff.printIndexedBuffer("Difference");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_5) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {2, 3, 5, 4});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2, 3, 5, 4},{
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
|
|
-16.f, -15.058824f, -13.960785f, -13.0196085f,
|
|
-11.92157f, -10.980392f, -10.039217f, -8.941177f,
|
|
-8.000001f, -7.0588236f, -5.960785f, -5.0196085f,
|
|
-3.9215698f, -2.9803925f, -2.039217f, -0.94117737f,
|
|
0.f, 0.94117737f, 2.039215f, 2.9803925f,
|
|
4.07843f, 5.0196075f, 5.960783f, 7.0588226f,
|
|
8.f, 8.941177f, 10.039215f, 10.980392f,
|
|
12.07843f, 13.019608f, 13.960783f, 15.058823f,
|
|
16.f, 16.941177f, 18.039217f, 18.980392f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f,
|
|
20.07843f, 21.019608f, 21.960783f, 23.058823f
|
|
});
|
|
NDArray min = NDArrayFactory::create<float>({-20.f, -19.f, -18.f, -17.f});
|
|
NDArray max = NDArrayFactory::create<float>({20.f, 21.f, 22.f, 23.f});
|
|
x.linspace(-60.);
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized per channels 5");
|
|
// exp.printBuffer("Quantized per channest E");
|
|
// auto diff = *result - exp;
|
|
// diff.printIndexedBuffer("Difference");
|
|
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_6) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {3, 5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
|
|
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
|
|
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
|
|
// NDArray exp = NDArrayFactory::create<float>('c', {3, 5},{
|
|
// 0.7801f, 0.5966f, 0.7260f, 0.2320f, 0.5084f,
|
|
// 0.1800f, 0.5046f, 0.8684f, 0.3513f, 0.5084f,
|
|
// 0.0877f, 0.5966f, 0.6600f, 0.3513f, 0.1604f
|
|
// });
|
|
|
|
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
|
|
0.77700233f, 0.596913f, 0.72314f, 0.23104f, 0.50982356f,
|
|
0.17930824f, 0.50528157f, 0.86846f, 0.34995764f, 0.50982356f,
|
|
0.08735529f, 0.596913f, 0.6574f, 0.34995764f, 0.15974471f});
|
|
NDArray min = NDArrayFactory::create<float>('c', {5}, {-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
|
|
NDArray max = NDArrayFactory::create<float>('c', {5}, {0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
|
|
// x.linspace(-60.);
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized per channels 5");
|
|
// exp.printBuffer("Quantized per channest E");
|
|
// auto diff = *result - exp;
|
|
// diff.printIndexedBuffer("Difference");
|
|
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_7) {
|
|
|
|
NDArray x = NDArrayFactory::create<float>('c', {100});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {100}, {
|
|
0.f, 0.01176471f, 0.01960784f, 0.03137255f, 0.03921569f,
|
|
0.0509804f, 0.05882353f, 0.07058824f, 0.07843138f, 0.09019608f,
|
|
0.09803922f, 0.10980393f, 0.12156864f, 0.12941177f, 0.14117648f,
|
|
0.14901961f, 0.16078432f, 0.16862746f, 0.18039216f, 0.18823531f,
|
|
0.20000002f, 0.21176472f, 0.21960786f, 0.23137257f, 0.2392157f,
|
|
0.2509804f, 0.25882354f, 0.27058825f, 0.2784314f, 0.2901961f,
|
|
0.3019608f, 0.30980393f, 0.32156864f, 0.32941177f, 0.34117648f,
|
|
0.34901962f, 0.36078432f, 0.36862746f, 0.3803922f, 0.38823533f,
|
|
0.40000004f, 0.41176474f, 0.41960788f, 0.43137258f, 0.43921572f,
|
|
0.45098042f, 0.45882356f, 0.47058827f, 0.4784314f, 0.4901961f,
|
|
0.49803925f, 0.50980395f, 0.52156866f, 0.5294118f, 0.5411765f,
|
|
0.54901963f, 0.56078434f, 0.5686275f, 0.5803922f, 0.5882353f,
|
|
0.6f, 0.6117647f, 0.61960787f, 0.6313726f, 0.6392157f,
|
|
0.6509804f, 0.65882355f, 0.67058825f, 0.6784314f, 0.6901961f,
|
|
0.69803923f, 0.70980394f, 0.72156864f, 0.7294118f, 0.7411765f,
|
|
0.7490196f, 0.7607844f, 0.7686275f, 0.7803922f, 0.78823537f,
|
|
0.8000001f, 0.8117648f, 0.8196079f, 0.8313726f, 0.83921576f,
|
|
0.85098046f, 0.8588236f, 0.8705883f, 0.87843144f, 0.89019614f,
|
|
0.8980393f, 0.909804f, 0.9215687f, 0.9294118f, 0.94117653f,
|
|
0.9490197f, 0.9607844f, 0.9686275f, 0.9803922f, 0.98823535f
|
|
});
|
|
NDArray min = NDArrayFactory::create<float>('c', {1},{0.0f});
|
|
NDArray max = NDArrayFactory::create<float>('c', {1}, {1.f});
|
|
x.linspace(0., 0.01);
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized7");
|
|
// exp.printBuffer("Expected 7");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_8) {
|
|
|
|
NDArray x = NDArrayFactory::create<float>('c', {10});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {10}, {
|
|
0.f, 0.09803922f, 0.20000002f, 0.3019608f, 0.40000004f, 0.49803925f,
|
|
0.6f, 0.69803923f, 0.8000001f, 0.8980393f
|
|
});
|
|
NDArray min = NDArrayFactory::create<float>('c', {1},{0.0f});
|
|
NDArray max = NDArrayFactory::create<float>('c', {1}, {1.f});
|
|
x.linspace(0., 0.1);
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.evaluate({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// x.printBuffer("SourInput8");
|
|
// result->printBuffer("Quantized8");
|
|
// exp.printBuffer("Expected 8");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(*result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, bool_broadcast_test_1) {
|
|
|
|
NDArray arr1('c', {2,2,1}, {1, 2, 3, 4}, nd4j::DataType::INT32);
|
|
NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
|
|
|
|
NDArray expd('c', {2,2,2}, {false, true, false, false, false, false, false, true}, nd4j::DataType::BOOL);
|
|
|
|
NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
|
|
|
|
arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), arr2, result, true);
|
|
// result.printIndexedBuffer();
|
|
// expd.printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(expd.isSameShape(result));
|
|
ASSERT_TRUE(expd.equalsTo(result));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, printIndexedTest_1) {
|
|
|
|
NDArray arr('c', {2,2,2,2}, {1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16}, nd4j::DataType::INT32);
|
|
// NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
|
|
|
|
// NDArray expd('c', {2,2,2}, {0,1,0,0, 0,0,0,1}, nd4j::DataType::BOOL);
|
|
|
|
// NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
|
|
|
|
// arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), &arr2, &result, true, nullptr);
|
|
// result.printIndexedBuffer();
|
|
// expd.printIndexedBuffer();
|
|
|
|
// ASSERT_TRUE(expd.isSameShape(result));
|
|
// ASSERT_TRUE(expd.equalsTo(result));
|
|
// arr.printIndexedBuffer("Test Print"); // output as [1, 2, 3, 4, 5, 6, 7, 8]
|
|
//
|
|
// we want output as
|
|
// [[[1 2]
|
|
// [3 4]]
|
|
//
|
|
// [[5 6]
|
|
// [7 8]]]
|
|
//
|
|
ResultSet lastDims = arr.allTensorsAlongDimension({3}); // last dim
|
|
size_t k = 0; // k from 0 to lastDims->size()
|
|
Nd4jLong rank = 4; // in this case
|
|
printf("[");
|
|
for (Nd4jLong i = 0; i < rank - 1; i++) {
|
|
|
|
for (Nd4jLong l = 0; l < i; ++l)
|
|
printf("\n");
|
|
printf("[");
|
|
for (Nd4jLong j = 0; j < arr.sizeAt(i); j++) {
|
|
// if (!i)
|
|
// printf("[");
|
|
// else
|
|
// printf(" ");
|
|
lastDims.at(k++)->printBuffer();
|
|
//if (k == arr.sizeAt(i))
|
|
// printf("]\n");
|
|
}
|
|
printf("]\n");
|
|
}
|
|
printf("]\n");
|
|
}
|
|
|
|
|