3164 lines
150 KiB
C++
3164 lines
150 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 <array/NDArray.h>
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#include <ops/ops.h>
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#include <helpers/GradCheck.h>
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using namespace sd;
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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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sd::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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}
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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);
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sd::ops::cosine_distance_loss op;
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auto res = op.evaluate({&predictions, &weights, &labels}, {}, {3, 1});
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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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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_2) {
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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);
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sd::ops::cosine_distance_loss op;
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auto res = op.evaluate({&predictions, &weights, &labels}, {}, {2, 1});
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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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}
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///////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, TestMarixBandPart_Test_1) {
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auto x = NDArrayFactory::create<double>('c', {2, 3, 3});
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auto exp = NDArrayFactory::create<double>('c', {2, 3, 3});
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x.linspace(1);
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exp.linspace(1);
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exp.p(0, 0, 2, 0.);
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exp.p(1, 0, 2, 0.);
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exp.p(0, 2, 0, 0.);
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exp.p(1, 2, 0, 0.);
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sd::ops::matrix_band_part op;
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auto results = op.evaluate({&x}, {}, {1, 1});
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ASSERT_EQ(ND4J_STATUS_OK, results.status());
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//results.at(0)->printIndexedBuffer("MBP Test1");
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//exp.printIndexedBuffer("MBP Expec");
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ASSERT_TRUE(exp.equalsTo(results.at(0)));
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}
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//////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, atan2_test1) {
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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});
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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});
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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 ,
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0.33172, 0.69614, 0.81846, 0.87776, 0.91253, 0.93533, 0.95141, 0.96336, 0.97259, 0.97993, 0.98591, 1.01266,});
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sd::ops::tf_atan2 op;
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auto result = op.evaluate({&y, &x}, {}, {});
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ASSERT_EQ(ND4J_STATUS_OK, result.status());
|
|
auto z = result.at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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(sd::BroadcastOpsTuple::custom(scalar::Atan2, pairwise::Atan2, broadcast::Atan2), &y, &z, true);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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 });
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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 });
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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 });
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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
|
|
});
|
|
|
|
sd::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));
|
|
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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.});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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
|
|
|
|
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
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
|
|
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test3) {
|
|
|
|
NDArray labels('c', {1}, std::vector<double>{0}, sd::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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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.});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
sd::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);
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
sd::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);
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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.});
|
|
|
|
sd::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));
|
|
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
|
|
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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);
|
|
sd::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));
|
|
}
|
|
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>());
|
|
sd::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));
|
|
}
|
|
|
|
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>());
|
|
sd::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));
|
|
}
|
|
|
|
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>());
|
|
sd::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));
|
|
}
|
|
|
|
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);
|
|
sd::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());
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_3) {
|
|
|
|
NDArray images ('c', {1,2,2,1}, {1,2,3,4}, sd::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, sd::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, std::vector<double>{0}, sd::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}, sd::DataType::FLOAT32);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_4) {
|
|
|
|
NDArray images('c', {1,2,2,1}, {1, 2, 3, 4}, sd::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, sd::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, std::vector<double>({0.}), sd::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}, sd::DataType::FLOAT32);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_5) {
|
|
|
|
NDArray images('c', {1, 100, 100, 3}, sd::DataType::FLOAT32);
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, sd::DataType::FLOAT32);
|
|
NDArray boxI('c', {2}, {1,1}, sd::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}, sd::DataType::FLOAT32);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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.);
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_1) {
|
|
|
|
NDArray x('c', {2,3}, {-63.80f, -63.75f, -63.70f, -63.5f, 0.0f, 0.1f}, sd::DataType::FLOAT32);
|
|
NDArray exp('c', {2,3}, {-63.75f, -63.75f, -63.75f, -63.5f, 0.f, 0.f}, sd::DataType::FLOAT32);
|
|
NDArray min('c', {}, std::vector<double>{-63.65f}, sd::DataType::FLOAT32);
|
|
NDArray max('c', {}, std::vector<double>{0.1f}, sd::DataType::FLOAT32);
|
|
|
|
sd::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));
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
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);
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
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});
|
|
|
|
sd::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));
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
|
|
#ifdef FFAST_MATH
|
|
if (1 > 0)
|
|
return;
|
|
#endif
|
|
|
|
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.);
|
|
sd::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));
|
|
}
|
|
|
|
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.);
|
|
sd::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));
|
|
}
|
|
|
|
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.);
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////
|
|
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);
|
|
sd::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));
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////
|
|
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);
|
|
sd::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));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, bool_broadcast_test_1) {
|
|
|
|
NDArray arr1('c', {2,2,1}, {1, 2, 3, 4}, sd::DataType::INT32);
|
|
NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, sd::DataType::INT32);
|
|
|
|
NDArray expd('c', {2,2,2}, {false, true, false, false, false, false, false, true}, sd::DataType::BOOL);
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|
|
|
NDArray result('c', {2,2,2}, sd::DataType::BOOL);
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|
|
|
arr1.applyTrueBroadcast(sd::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), arr2, result, true);
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// result.printIndexedBuffer();
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// expd.printIndexedBuffer();
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|
|
|
ASSERT_TRUE(expd.isSameShape(result));
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ASSERT_TRUE(expd.equalsTo(result));
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|
}
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|
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|
///////////////////////////////////////////////////////////////////
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|
TEST_F(DeclarableOpsTests10, printIndexedTest_1) {
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|
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NDArray arr('c', {2,2,2,2}, {1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16}, sd::DataType::INT32);
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|
// NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, sd::DataType::INT32);
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|
|
|
// NDArray expd('c', {2,2,2}, {0,1,0,0, 0,0,0,1}, sd::DataType::BOOL);
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|
|
|
// NDArray result('c', {2,2,2}, sd::DataType::BOOL);
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|
|
|
// arr1.applyTrueBroadcast(sd::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), &arr2, &result, true, nullptr);
|
|
// result.printIndexedBuffer();
|
|
// expd.printIndexedBuffer();
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|
|
|
// 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");
|
|
}
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|
|