2634 lines
110 KiB
C++
2634 lines
110 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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* Copyright (c) 2019 Konduit K.K.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// Created by raver on 8/4/2018.
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//
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#include "testlayers.h"
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#include <ops/declarable/CustomOperations.h>
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#include <NDArray.h>
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#include <ops/ops.h>
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#include <GradCheck.h>
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using namespace nd4j;
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class DeclarableOpsTests10 : public testing::Test {
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public:
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DeclarableOpsTests10() {
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printf("\n");
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fflush(stdout);
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}
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};
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template <typename T>
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class TypedDeclarableOpsTests10 : public testing::Test {
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public:
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TypedDeclarableOpsTests10() {
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printf("\n");
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fflush(stdout);
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}
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};
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typedef ::testing::Types<double, float> TestingTypes;
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TYPED_TEST_CASE(TypedDeclarableOpsTests10, TestingTypes);
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TEST_F(DeclarableOpsTests10, Test_ArgMax_1) {
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auto x = NDArrayFactory::create<double>('c', {3, 3});
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auto e = NDArrayFactory::create<Nd4jLong>(8);
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x.linspace(1.0);
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nd4j::ops::argmax op;
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auto result = op.execute({&x}, {}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = *result->at(0);
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ASSERT_EQ(e, z);
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_ArgMax_2) {
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auto x = NDArrayFactory::create<double>('c', {3, 3});
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auto y = NDArrayFactory::create<int>('c', {1}, {1});
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auto e = NDArrayFactory::create<Nd4jLong>('c', {3}, {2, 2, 2});
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x.linspace(1.0);
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nd4j::ops::argmax op;
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auto result = op.execute({&x, &y}, {}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = *result->at(0);
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//z.printIndexedBuffer("z");
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//z.printShapeInfo("z shape");
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ASSERT_EQ(e, z);
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_And_1) {
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auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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auto e = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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nd4j::ops::boolean_and op;
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auto result = op.execute({&x, &y}, {}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Or_1) {
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auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
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auto e = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
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nd4j::ops::boolean_or op;
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auto result = op.execute({&x, &y}, {}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Not_1) {
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auto x = NDArrayFactory::create<bool>('c', {4}, {1, 1, 0, 1});
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auto y = NDArrayFactory::create<bool>('c', {4}, {0, 0, 0, 1});
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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}, {0, 0, 1, 0});
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nd4j::ops::boolean_not op;
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auto result = op.execute({&x, &y}, {}, {}, {}, false, nd4j::DataType::BOOL);
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ASSERT_EQ(Status::OK(), result->status());
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auto res = result->at(0);
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res->printBuffer("OUtput NOT");
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ASSERT_TRUE(e.equalsTo(res));
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delete result;
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}
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TEST_F(DeclarableOpsTests10, Test_Size_at_1) {
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auto x = NDArrayFactory::create<double>('c', {10, 20, 30});
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auto e = NDArrayFactory::create<Nd4jLong>(20);
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nd4j::ops::size_at op;
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auto result = op.execute({&x}, {}, {1});
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ASSERT_EQ(Status::OK(), result->status());
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ASSERT_EQ(e, *result->at(0));
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delete result;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, MirrorPad_SGO_Test_1) {
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auto in = NDArrayFactory::create<double>({1., 2., 3., 4., 5.});
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// auto pad('c', {1, 2}, {1., 1.});// = Nd4j.create(new double[]{1, 1}, new long[]{1, 2});
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auto pad = NDArrayFactory::create<int>('c', {1, 2}, {1, 1});
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// auto value(10.0);
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auto exp = NDArrayFactory::create<double>({2., 1., 2., 3., 4., 5., 4.});
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nd4j::ops::mirror_pad op;
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auto res = op.execute({&in, &pad}, {10.0}, {0}, {}, false, nd4j::DataType::DOUBLE);
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ASSERT_EQ(res->status(), ND4J_STATUS_OK);
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res->at(0)->printIndexedBuffer("Mirror pad:");
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ASSERT_TRUE(exp.equalsTo(res->at(0)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Unique_SGO_Test_1) {
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auto input = NDArrayFactory::create<double>({3., 4., 3., 1., 3., 0., 2., 4., 2., 4.});
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auto expIdx = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
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auto exp = NDArrayFactory::create<double>({3., 4., 1., 0., 2.});
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nd4j::ops::unique op;
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auto res = op.execute({&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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res1->printIndexedBuffer("Unique values");
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res2->printIndexedBuffer("Unique idxs");
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ASSERT_TRUE(exp.equalsTo(res1));
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ASSERT_TRUE(expIdx.equalsTo(res2));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_1) {
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auto input = NDArrayFactory::create<bool>('c', {3, 3}, {true, false, false, true, true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {6, 2}, {0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 2LL, 0LL, 2LL, 1LL, 2LL, 2LL});
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nd4j::ops::Where op;
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auto res = op.execute({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(exp.isSameShape(resA));
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ASSERT_TRUE(exp.equalsTo(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_02) {
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auto input = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {5, 3}, {0LL, 0LL, 0LL, 0LL, 1LL, 1LL, 1LL, 0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 1LL, 0LL});
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nd4j::ops::Where op;
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auto res = op.execute({&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("Where02");
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resA->printBuffer("Where02lINEAR");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_1) {
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auto cond3d = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
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// auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 1, 1, 1});
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auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 0, 1});
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auto exp3 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 1, 0});
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nd4j::ops::where_np op;
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auto res = op.execute({&cond3d}, {}, {});
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ASSERT_TRUE(res->size() == 3);
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ASSERT_EQ(res->status(), ND4J_STATUS_OK);
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auto res1 = res->at(0);
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auto res2 = res->at(1);
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auto res3 = res->at(2);
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// res1->printShapeInfo("Res1 shape"); res1->printBuffer("Res1");
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// res2->printShapeInfo("Res2 shape"); res2->printBuffer("Res2");
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// res3->printShapeInfo("Res3 shape"); res3->printBuffer("Res3");
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ASSERT_TRUE(exp1.equalsTo(res1));
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ASSERT_TRUE(exp2.equalsTo(res2));
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ASSERT_TRUE(exp3.equalsTo(res3));
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//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_2) {
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auto cond2d = NDArrayFactory::create<bool>('c', {3, 5}, {1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1});
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// auto expIdx({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
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auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2});
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auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 4, 0, 1, 2, 3, 4, 1, 2, 3, 4});
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nd4j::ops::where_np op;
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auto res = op.execute({&cond2d}, {}, {});
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ASSERT_TRUE(res->size() == 2);
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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ASSERT_TRUE(exp1.equalsTo(res->at(0)));
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ASSERT_TRUE(exp2.equalsTo(res->at(1)));
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//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_2) {
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auto input = NDArrayFactory::create<bool>({true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4,1}, {0, 2, 3, 4});
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nd4j::ops::Where op;
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auto res = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::INT64);
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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// resA->printIndexedBuffer("Result A");
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// resA->printShapeInfo("ShapeA");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_3) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {true, false, true, true, true});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::Where op;
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auto res = op.execute({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_4) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::Where op;
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auto res = op.execute({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(resA->isEmpty());
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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//ASSERT_TRUE(exp.equalsTo(resA));
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//ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Where_SGO_Test_5) {
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auto input = NDArrayFactory::create<float>('c', {5}, {1, 0, 0, 2, 3});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {3, 1}, {0, 3, 4});
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nd4j::ops::Where op;
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auto res = op.execute({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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//ASSERT_TRUE(resA->isEmpty());
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resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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ASSERT_TRUE(exp.equalsTo(resA));
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ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_4) {
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auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
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nd4j::ops::where_np op;
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auto res = op.execute({&input}, {}, {});
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ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
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auto resA = res->at(0);
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ASSERT_TRUE(resA->isEmpty());
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//resA->printIndexedBuffer("Result A");
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//resA->printShapeInfo("ShapeA");
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//ASSERT_TRUE(exp.equalsTo(resA));
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//ASSERT_TRUE(exp.isSameShape(resA));
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// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
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delete res;
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_1) {
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auto labels = NDArrayFactory::create<double>('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
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//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
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auto predictions = NDArrayFactory::create<double>('c', {2, 3}, {-0.3, -0.2, -0.1, 0, 0.1, 0.2});
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auto weights = NDArrayFactory::create<double>('c', {2, 1}, {0., 1.});
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auto exp = NDArrayFactory::create<double>(0.6);
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nd4j::ops::cosine_distance_loss op;
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auto res = op.execute({&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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delete res;
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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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nd4j::ops::cosine_distance_loss op;
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auto res = op.execute({&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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delete res;
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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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nd4j::ops::matrix_band_part op;
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auto results = op.execute({&x}, {}, {1, 1}, {}, false, nd4j::DataType::DOUBLE);
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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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delete results;
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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});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {-0.51, -0.46, -0.41, -0.36, -0.31, -0.26, -0.21, -0.16, -0.11, -0.06, -0.01, 0.04, 0.09, 0.14, 0.19, 0.24, 0.29, 0.34, 0.39, 0.44, 0.49, 0.54, 0.59, 0.61});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.04201, -2.03663, -2.03009, -2.02199,-2.01166, -1.99808, -1.97941, -1.95217,-1.90875, -1.8292 , -1.6416 , -0.942 ,
|
|
0.33172, 0.69614, 0.81846, 0.87776, 0.91253, 0.93533, 0.95141, 0.96336, 0.97259, 0.97993, 0.98591, 1.01266,});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&y, &x}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test2) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
|
|
auto x = NDArrayFactory::create<double>('c', { 3, 4}, {-1.05, -0.82, -0.639, -0.458, -0.277, -0.096, 0.085, 0.266, 0.447, 0.628, 0.809, 0.99});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.38008, -2.30149, -2.22748, -2.1232 ,-1.96979, -1.73736, -1.3973 , -0.98279,-0.61088, -0.34685, -0.17256, -0.0555 ,
|
|
3.11208, 2.99987, 2.83399, 2.57869, 2.207 , 1.77611, 1.41664, 1.17298, 1.01458, 0.90829, 0.8336 , 0.77879});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&y, &x}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printIndexedBuffer();
|
|
|
|
// x.applyTrueBroadcast(nd4j::BroadcastOpsTuple::custom(scalar::Atan2, pairwise::Atan2, broadcast::Atan2), &y, &z, true);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test3) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
|
|
auto x = NDArrayFactory::create<double>('c', { 3, 4}, {-1.05, -0.82, -0.639, -0.458, -0.277, -0.096, 0.085, 0.266, 0.447, 0.628, 0.809, 0.99});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.33231, -2.41089, -2.48491, -2.58919,-2.74259, -2.97502, 2.9681 , 2.55359, 2.18167, 1.91765, 1.74335, 1.62629,
|
|
-1.54128, -1.42907, -1.2632 , -1.00789,-0.63621, -0.20531, 0.15416, 0.39782, 0.55622, 0.6625 , 0.7372 , 0.79201});
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&x, &y}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test4) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 1}, {-0.82, -0.458, -0.096, 0.085, 0.447, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.45527, -2.36165, -2.24628, -2.10492,-2.1703 , -1.86945, -1.50321, -1.15359,-0.25062, -0.17373, -0.13273, -0.10733,
|
|
3.05688, 3.03942, 3.01293, 2.9681 , 2.18167, 1.87635, 1.50156, 1.14451, 1.13674, 0.97626, 0.84423, 0.7372 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&x, &y}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test5) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', {2, 3, 1}, {-0.82, -0.458, -0.096, 0.085, 0.447, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.25712, -2.35074, -2.46611, -2.60747,-2.54209, -2.84294, 3.07401, 2.72438, 1.82141, 1.74453, 1.70353, 1.67813,
|
|
-1.48608, -1.46862, -1.44214, -1.3973 ,-0.61088, -0.30556, 0.06924, 0.42629, 0.43405, 0.59453, 0.72657, 0.8336 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, atan2_test6) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {-1.001 ,-0.829 ,-0.657 ,-0.485 ,-0.313 ,-0.141 ,0.031 ,0.203 ,0.375 ,0.547 ,0.719 ,0.891});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {-0.82, -0.096, 0.085, 0.809});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {-2.25712, -1.68608, -1.44214, -0.54006,-2.77695, -2.16855, 0.34972, 0.24585, 2.71267, 1.74453, 1.45312, 0.8336 });
|
|
|
|
nd4j::ops::tf_atan2 op;
|
|
auto result = op.execute({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, IGamma_Test1) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {1.1 , 2.1 , 3.1 ,4.1 , 5.1 , 6.1 ,7.1 ,8.1 ,9.1 ,10.1,11.1 ,12.1});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {1.2, 2.2, 3.2, 4.2});
|
|
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {
|
|
0.659917, 0.61757898, 0.59726304, 0.58478117,
|
|
0.0066205109, 0.022211598, 0.040677428, 0.059117373,
|
|
0.0000039433403, 0.000086064574, 0.000436067, 0.0012273735});
|
|
|
|
nd4j::ops::igamma op;
|
|
auto result = op.execute({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printBuffer("OUtput");
|
|
// exp.printBuffer("EXpect");
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, IGamma_Test2) {
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {1, 3, 4}, {1.1 , 2.1 , 3.1 ,4.1 , 5.1 , 6.1 ,
|
|
7.1 ,8.1 ,9.1 ,10.1,11.1 ,12.1});
|
|
auto x = NDArrayFactory::create<double>('c', { 4}, {1.2, 2.2, 3.2, 4.2});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,4}, {0.340083, 0.382421, 0.402737, 0.415221,
|
|
0.993379, 0.977788, 0.959323, 0.940883,
|
|
0.999996, 0.999914, 0.999564, 0.998773});
|
|
|
|
nd4j::ops::igammac op;
|
|
auto result = op.execute({&y, &x}, {}, {}, {});
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
auto z = result->at(0);
|
|
// z->printBuffer("OUtput");
|
|
// exp.printBuffer("EXpect");
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test10) {
|
|
|
|
auto limit = NDArrayFactory::create<double>('c', {1, 3, 4});
|
|
limit = 5.;
|
|
auto exp = NDArrayFactory::create<double>('c', {5}, {0.,1.,2.,3.,4.});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.execute({&limit}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test11) {
|
|
|
|
auto limit = NDArrayFactory::create<double>('c', {1, 3, 4});
|
|
auto start = NDArrayFactory::create<double>('c', {2, 4});
|
|
limit = 5.;
|
|
start = 0.5;
|
|
auto exp = NDArrayFactory::create<double>('c', {5}, {0.5,1.5,2.5,3.5,4.5});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.execute({&start, &limit}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, range_test12) {
|
|
|
|
auto exp = NDArrayFactory::create<float>('c', {9}, {0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5});
|
|
|
|
nd4j::ops::range op;
|
|
auto result = op.execute({}, {0.5, 5, 0.5}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, top_k_permuted_test1) {
|
|
|
|
auto x = NDArrayFactory::create<double>({7., 3., 1., 2., 5., 0., 4., 6., 9., 8.});
|
|
auto expUnsorted = NDArrayFactory::create<double>({7., 6., 9., 8.}); // Sorted = False
|
|
auto expSorted = NDArrayFactory::create<double>({9., 8., 7., 6., 5.}); // Sorted = False
|
|
|
|
|
|
nd4j::ops::top_k op;
|
|
auto result = op.execute({&x}, {}, {4}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
auto zI = result->at(1);
|
|
z->printIndexedBuffer("TopK(5)");
|
|
zI->printIndexedBuffer("TopKI(5)");
|
|
ASSERT_TRUE(expUnsorted.isSameShape(z));
|
|
ASSERT_TRUE(expUnsorted.equalsTo(z));
|
|
|
|
auto result2 = op.execute({&x}, {}, {5}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result2->status());
|
|
|
|
z = result2->at(0);
|
|
zI = result2->at(1);
|
|
z->printIndexedBuffer("sorted TopK(5)");
|
|
zI->printIndexedBuffer("sorted TopKI(5)");
|
|
ASSERT_TRUE(expSorted.isSameShape(z));
|
|
ASSERT_TRUE(expSorted.equalsTo(z));
|
|
|
|
delete result;
|
|
delete result2;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, top_k_permuted_test2) {
|
|
|
|
auto x = NDArrayFactory::create<double>({7., 3., 1., 2., 5., 0., 4., 6., 9., 8.});
|
|
auto expUnsorted = NDArrayFactory::create<double>({7., 5., 6., 9., 8.}); // Sorted = False
|
|
auto expSorted = NDArrayFactory::create<double>({9., 8., 7., 6., 5.}); // Sorted = False
|
|
|
|
|
|
nd4j::ops::top_k op;
|
|
auto result = op.execute({&x}, {}, {5}, {false});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result->status());
|
|
|
|
auto z = result->at(0);
|
|
auto zI = result->at(1);
|
|
z->printIndexedBuffer("TopK(5)");
|
|
zI->printIndexedBuffer("TopKI(5)");
|
|
ASSERT_TRUE(expUnsorted.isSameShape(z));
|
|
ASSERT_TRUE(expUnsorted.equalsTo(z));
|
|
|
|
auto result2 = op.execute({&x}, {}, {5}, {true});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, result2->status());
|
|
|
|
z = result2->at(0);
|
|
zI = result2->at(1);
|
|
z->printIndexedBuffer("sorted TopK(5)");
|
|
zI->printIndexedBuffer("sorted TopKI(5)");
|
|
ASSERT_TRUE(expSorted.isSameShape(z));
|
|
ASSERT_TRUE(expSorted.equalsTo(z));
|
|
|
|
delete result;
|
|
delete result2;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test1) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2,3},{3, 2, 1, 0, 1, 2});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,3,4});
|
|
auto expected = NDArrayFactory::create<double>('c', {2,3}, {1.24254, 1.34254, 1.44254, 1.54254, 1.44254, 1.34254});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.execute({&labels, &logits}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test2) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2},{1, 0});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,3});
|
|
auto expected = NDArrayFactory::create<double>('c', {2}, {1.10194, 1.20194});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.execute({&labels, &logits}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test3) {
|
|
|
|
NDArray labels('c', {1}, {0}, nd4j::DataType::INT32);
|
|
auto logits = NDArrayFactory::create<double>('c', {1,3});
|
|
auto expected = NDArrayFactory::create<double>('c', {1}, {1.20194});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.execute({&labels, &logits}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, sparse_softmax_cross_entropy_loss_with_logits_test4) {
|
|
|
|
auto labels = NDArrayFactory::create<int>('c', {2},{0, 0});
|
|
auto logits = NDArrayFactory::create<double>('c', {2,1});
|
|
auto expected = NDArrayFactory::create<double>('c', {2}, {0., 0.});
|
|
|
|
logits.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits op;
|
|
auto results = op.execute({&labels, &logits}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, split_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {10},{1.f,2.f,3.f,4.f,5.f,6.f,7.f,8.f,9.f,10.f});
|
|
auto axis = NDArrayFactory::create<double>(-1);
|
|
auto exp1 = NDArrayFactory::create<double>('c', {5}, {1.f,2.f,3.f,4.f,5.f});
|
|
auto exp2 = NDArrayFactory::create<double>('c', {5}, {6.f,7.f,8.f,9.f,10.f});
|
|
|
|
nd4j::ops::split op;
|
|
auto results = op.execute({&input, &axis}, {}, {2}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out1 = results->at(0);
|
|
auto out2 = results->at(1);
|
|
|
|
ASSERT_TRUE(exp1.isSameShape(out1));
|
|
ASSERT_TRUE(exp2.isSameShape(out2));
|
|
ASSERT_TRUE(exp1.equalsTo(out1));
|
|
ASSERT_TRUE(exp2.equalsTo(out2));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, split_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3,8},{1.f,2.f,3.f,4.f,5.f,6.f,7.f,8.f,9.f,10.f,11.f,12.f,13.f,14.f,15.f,16.f,17.f,18.f,19.f,20.f,21.f,22.f,23.f,24.f});
|
|
auto exp1 = NDArrayFactory::create<double>('c', {3,4}, {1.f,2.f,3.f,4.f, 9.f,10.f,11.f,12.f, 17.f,18.f,19.f,20.f});
|
|
auto exp2 = NDArrayFactory::create<double>('c', {3,4}, {5.f,6.f,7.f,8.f, 13.f,14.f,15.f,16.f, 21.f,22.f,23.f,24.f});
|
|
|
|
nd4j::ops::split op;
|
|
auto results = op.execute({&input}, {}, {2,-1},{});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out1 = results->at(0);
|
|
auto out2 = results->at(1);
|
|
|
|
ASSERT_TRUE(exp1.isSameShape(out1));
|
|
ASSERT_TRUE(exp2.isSameShape(out2));
|
|
ASSERT_TRUE(exp1.equalsTo(out1));
|
|
ASSERT_TRUE(exp2.equalsTo(out2));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test1) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3},{-1.f, 0.f, 1.5f, 2.f, 5.f, 15.f});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {2, 1, 1, 0, 2});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test2) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3,4},{0.f, 5.f, 2.f, 1.f, -1.f, 2.f, 5.f, 3.f, 2.f, 3.f, -1.f, 5.f, 3.f, 2.f, 1.f, 4.f, 2.f, 5.f, 5.f, 5.f, 6.f, 6.f, -1.f, 0.f});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {5, 2, 5, 3, 9});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test3) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {2,3,1,4,1},{0.f, 5.f, 2.001f, 1.f, -1.f, 2.f, 5.f, 3.f, 2.999f, 3.00001f, -1.f, 3.99999f, 3.f, 2.f, 1.f, 4.f, 2.f, 5.f, 5.f, 5.f, 6.f, 6.f, -1.f, 0.00001f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2,1}, {0, 5});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {5, 2, 5, 4, 8});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {20,5},{13.8387f,0.1509f,50.39f,30.403f,13.5174f,9.7351f,37.6652f,28.9215f,22.7011f,45.2834f,40.7628f,50.4995f,26.8003f,27.479f,44.633f,6.9109f,48.5004f,
|
|
46.5971f,1.6203f,23.6381f,38.9661f,50.8146f,17.2482f,8.0429f,7.5666f,7.9709f,21.8403f,20.1694f,23.3004f,50.9151f,46.239f,38.7323f,29.6946f,32.9876f,
|
|
23.0013f,39.7318f,19.4486f,37.6147f,-0.1506f,5.3246f,3.6173f,24.2573f,4.3941f,9.7105f,24.0364f,35.3681f,17.7805f,35.7681f,16.4144f,17.4362f,8.4987f,
|
|
26.8108f,36.2937f,31.6442f,29.7221f,8.7445f,33.3301f,4.0939f,13.078f,45.1481f,29.0172f,21.6548f,35.408f,27.1861f,2.2576f,40.6804f,36.2201f,29.7352f,
|
|
29.1244f,38.7444f,5.8721f,33.5983f,48.2694f,34.4161f,19.7148f,13.8085f,13.6075f,22.5042f,37.8002f,50.0543f,48.5314f,20.3694f,28.5042f,-0.4679f,4.4245f,
|
|
18.9837f,40.7724f,2.7611f,44.0431f,37.186f,27.7361f,14.6001f,9.1721f,14.6087f,21.4072f,49.3344f,11.4668f,14.6171f,15.2502f,5.244f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2}, {0, 50});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {22, 17, 24, 19, 18});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,20},{20.f, 0.f, 60.f, 40.f, 20.f, 0.f, 40.f, 0.f, 40.f, 40.f,40.f,60.f, 20.f, 20.f, 60.f, 0.f, 40.f,
|
|
46.5971f,1.6203f,23.6381f,38.9661f,50.8146f,17.2482f,8.0429f,7.5666f,7.9709f,21.8403f,20.1694f,23.3004f,50.9151f,46.239f,38.7323f,29.6946f,32.9876f,
|
|
23.0013f,39.7318f,19.4486f,37.6147f,-0.1506f,5.3246f,3.6173f,24.2573f,4.3941f,9.7105f,24.0364f,35.3681f,17.7805f,35.7681f,16.4144f,17.4362f,8.4987f,
|
|
26.8108f,36.2937f,31.6442f,29.7221f,8.7445f,33.3301f,4.0939f,13.078f,45.1481f,29.0172f,21.6548f,35.408f,27.1861f,2.2576f,40.6804f,36.2201f,29.7352f,
|
|
29.1244f,38.7444f,5.8721f,33.5983f,48.2694f,34.4161f,19.7148f,13.8085f,13.6075f,22.5042f,37.8002f,50.0543f,48.5314f,20.3694f,28.5042f,-0.4679f,4.4245f,
|
|
18.9837f,40.7724f,2.7611f,44.0431f,37.186f,27.7361f,14.6001f,9.1721f,14.6087f,21.4072f,49.3344f,11.4668f,14.6171f,15.2502f,5.244f});
|
|
auto range = NDArrayFactory::create<double>('c', {1,2}, {0, 50});
|
|
// auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {23, 19, 20, 23, 15}); // 23, 15, 24, 17, 21
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {23, 15, 24, 17, 21});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range}, {}, {5}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *out = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
// out->printBuffer("5HIST");
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, histogram_fixed_width_test6) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {7},{0.0, 0.1, 0.1, 0.3, 0.5, 0.5, 0.9});
|
|
auto range = NDArrayFactory::create<double>('c', {2}, {0, 1});
|
|
auto bins = NDArrayFactory::create<int>(5);
|
|
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5}, {3, 1, 2, 0, 1});
|
|
|
|
nd4j::ops::histogram_fixed_width op;
|
|
auto results = op.execute({&input, &range, &bins}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto out = results->at(0);
|
|
// out->printShapeInfo();
|
|
// out->printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(out));
|
|
ASSERT_TRUE(exp.equalsTo(out));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<float>(4.f);
|
|
NDArray exp = NDArrayFactory::create<float>(5.f);
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_2) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3, 4}, {10, 11, 9, 12, 8, 7, 6, 5, 1, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(3);
|
|
NDArray exp = NDArrayFactory::create<float>({12.f, 8.f, 4.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
output->printIndexedBuffer("Output 2");
|
|
exp.printIndexedBuffer("Expect 2");
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_3) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3,4}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(3);
|
|
NDArray exp = NDArrayFactory::create<float>({1.f, 5.f, 2.f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {1}); // with reverse = true
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
output->printIndexedBuffer("Output 3");
|
|
exp.printIndexedBuffer("Expect 3");
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_4) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 2, 3}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,2}, {10.f, 11.f, 12.f, 4.f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_04) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {6, 15});
|
|
NDArray n = NDArrayFactory::create<int>(4);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {6}, {5.f, 20.f, 35.f, 50.f, 65.f, 80.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_5) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 2, 3}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,2}, {1.f, 7.f, 5.f, 2.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_6) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(0);
|
|
NDArray exp = NDArrayFactory::create(1.f);//NDArrayFactory::create<float>('c', {2,2}, {1.f, 4.f, 7.f, 10.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_06) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {12}, {10, 1, 9, 8, 11, 7, 6, 5, 12, 3, 2, 4});
|
|
NDArray n = NDArrayFactory::create<int>(4);
|
|
NDArray exp = NDArrayFactory::create(8.f);//NDArrayFactory::create<float>('c', {2,2}, {1.f, 4.f, 7.f, 10.f});
|
|
|
|
// input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_7) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2309f,
|
|
0.7271f, 0.1804f, 0.5056f, 0.8925f,
|
|
0.5461f, 0.9234f, 0.0856f, 0.7938f,
|
|
|
|
0.6591f, 0.5555f, 0.1596f, 0.3087f,
|
|
0.1548f, 0.4695f, 0.9939f, 0.6113f,
|
|
0.6765f, 0.1800f, 0.6750f, 0.2246f});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,3}, {0.7788f, 0.7271f, 0.7938f, 0.5555f, 0.6113f, 0.675f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
output->printIndexedBuffer("NTH rank3_n2");
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, NTH_Element_Test_8) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {2, 3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2309f,
|
|
0.7271f, 0.1804f, 0.5056f, 0.8925f,
|
|
0.5461f, 0.9234f, 0.0856f, 0.7938f,
|
|
|
|
0.6591f, 0.5555f, 0.1596f, 0.3087f,
|
|
0.1548f, 0.4695f, 0.9939f, 0.6113f,
|
|
0.6765f, 0.1800f, 0.6750f, 0.2246f});
|
|
NDArray n = NDArrayFactory::create<int>(2);
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,3}, {0.7244f, 0.5056f, 0.5461f, 0.3087f, 0.4695f, 0.2246f});
|
|
|
|
//input.linspace(1.f);
|
|
|
|
nd4j::ops::nth_element op;
|
|
auto results = op.execute({&input, &n}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* output = results->at(0);
|
|
output->printIndexedBuffer("NTH rank3_n2_reverse");
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test1) {
|
|
|
|
auto input = NDArrayFactory::create<Nd4jLong>('c', {3});
|
|
auto shape = NDArrayFactory::create<int>('c', {2}, {3, 3});
|
|
auto exp = NDArrayFactory::create<Nd4jLong>('c', {3,3}, {1, 2, 3,1, 2, 3, 1, 2, 3});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test2) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {1,3});
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {1.f, 2.f, 3.f,1.f, 2.f, 3.f,1.f, 2.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test3) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3,1});
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test4) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.);
|
|
auto shape = NDArrayFactory::create<double>('c', {2}, {3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3,3}, {10.f, 10.f, 10.f,10.f, 10.f, 10.f, 10.f, 10.f, 10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test5) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<double>('c', {1}, {3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {3}, {10.f, 10.f, 10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test6) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<double>(1.f);
|
|
auto exp = NDArrayFactory::create<double>('c', {1}, {10.f});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test7) {
|
|
|
|
auto input = NDArrayFactory::create<double>(10.f);
|
|
auto shape = NDArrayFactory::create<Nd4jLong>(1);
|
|
auto exp = NDArrayFactory::create<double>('c', {1}, {10.});
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test8) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {3});
|
|
auto shape = NDArrayFactory::create<double>('c', {3}, {1.f, 3.f, 3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,3,3}, {1.f, 2.f, 3.f,1.f, 2.f, 3.f,1.f, 2.f, 3.f});
|
|
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test9) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,1,1});
|
|
auto shape = NDArrayFactory::create<double>('c', {5}, {2.f,1.f,5.f,1.f,3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {2,1,5,1,3}, {1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f,4.f, 4.f, 4.f,5.f, 5.f, 5.f,
|
|
1.f, 1.f, 1.f,2.f, 2.f, 2.f,3.f, 3.f, 3.f,4.f, 4.f, 4.f,5.f, 5.f, 5.f});
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, broadcast_to_test10) {
|
|
|
|
auto input = NDArrayFactory::create<double>('c', {5,1,3});
|
|
auto shape = NDArrayFactory::create<double>('c', {5}, {2.f,1.f,5.f,1.f,3.f});
|
|
auto exp = NDArrayFactory::create<double>('c', {2,1,5,1,3}, {1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f,10.f, 11.f, 12.f,13.f, 14.f, 15.f,
|
|
1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f,10.f, 11.f, 12.f,13.f, 14.f, 15.f});
|
|
input.linspace(1.f);
|
|
|
|
nd4j::ops::broadcast_to op;
|
|
auto results = op.execute({&input, &shape}, {}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *output = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(output));
|
|
ASSERT_TRUE(exp.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
|
|
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
|
|
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
|
|
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
|
|
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
|
|
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
|
|
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
|
|
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
|
|
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
|
|
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
|
|
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
|
|
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
|
|
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
|
|
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
|
|
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
|
|
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.execute({&input}, {}, {10, 10});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
//result->printIndexedBuffer("Resized to 10x10");
|
|
//expected.printIndexedBuffer("Expect for 10x10");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test2) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
NDArray size = NDArrayFactory::create<int>({10, 10});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
|
|
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
|
|
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
|
|
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
|
|
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
|
|
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
|
|
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
|
|
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
|
|
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
|
|
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
|
|
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
|
|
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
|
|
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
|
|
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
|
|
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
|
|
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
|
|
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
|
|
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
|
|
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
|
|
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
|
|
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
|
|
20.2,21.2, 22.2, 23.2,
|
|
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.execute({&input, &size}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test3) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4},
|
|
{ 1., 2., 3., 4. ,
|
|
1.8888888, 2.8888888, 3.8888888, 4.888889,
|
|
2.7777777, 3.7777777, 4.7777777, 5.7777777,
|
|
3.6666667, 4.666667 , 5.666667, 6.666667 ,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111111, 11.111111,
|
|
9., 10., 11., 12.,
|
|
|
|
2.3333335, 3.3333335, 4.3333335, 5.3333335,
|
|
3.2222223, 4.2222223, 5.2222223, 6.2222223,
|
|
4.111111, 5.111111, 6.111111, 7.111111,
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888888,
|
|
6.777778, 7.777778, 8.777778, 9.777778,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444444, 10.444444, 11.444444, 12.444444,
|
|
10.333333, 11.333333, 12.333333, 13.333333,
|
|
|
|
3.6666667, 4.666667, 5.666667, 6.666667,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445 ,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334 ,
|
|
7.2222223, 8.222222, 9.222222, 10.222222 ,
|
|
8.111112, 9.111112, 10.111112, 11.111112 ,
|
|
9., 10., 11.000001, 12.000001 ,
|
|
9.888889, 10.888889, 11.888889, 12.888889 ,
|
|
10.777778, 11.777778, 12.777778, 13.777778 ,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888889,
|
|
6.7777777, 7.7777777, 8.777779, 9.777779,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111111, 13.111111, 14.111111, 15.111111,
|
|
13., 14., 15., 16.,
|
|
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111112, 11.111112,
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777779, 11.777779, 12.777779, 13.777779,
|
|
11.666667, 12.666667, 13.666668, 14.666668,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13., 14., 15.0, 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666668, 17.666668, 18.666668,
|
|
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777778, 11.777778, 12.777779, 13.777779,
|
|
11.666667, 12.666666, 13.666666, 14.666666,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
15.222221, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222223, 12.222223, 13.222223, 14.222223,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13.000001, 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777779, 15.777779, 16.777779, 17.777779,
|
|
15.666668, 16.666668, 17.666668, 18.666668,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444446, 16.444447,
|
|
14.333334, 15.333333, 16.333332, 17.333332,
|
|
15.222222, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
17.88889, 18.88889, 19.88889, 20.88889,
|
|
18.777779, 19.777779, 20.777779, 21.777779,
|
|
19.666668, 20.666668, 21.666668, 22.666668,
|
|
|
|
13., 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666666, 17.666666, 18.666666,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
19.222221, 20.222221, 21.222221, 22.222221,
|
|
20.11111, 21.11111, 22.11111, 23.11111,
|
|
21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.execute({&input}, {}, {10, 10, 1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test4) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
|
|
NDArray size = NDArrayFactory::create<int>({10, 10});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4},
|
|
{ 1., 2., 3., 4. ,
|
|
1.8888888, 2.8888888, 3.8888888, 4.888889,
|
|
2.7777777, 3.7777777, 4.7777777, 5.7777777,
|
|
3.6666667, 4.666667 , 5.666667, 6.666667 ,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111111, 11.111111,
|
|
9., 10., 11., 12.,
|
|
|
|
2.3333335, 3.3333335, 4.3333335, 5.3333335,
|
|
3.2222223, 4.2222223, 5.2222223, 6.2222223,
|
|
4.111111, 5.111111, 6.111111, 7.111111,
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888888,
|
|
6.777778, 7.777778, 8.777778, 9.777778,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444444, 10.444444, 11.444444, 12.444444,
|
|
10.333333, 11.333333, 12.333333, 13.333333,
|
|
|
|
3.6666667, 4.666667, 5.666667, 6.666667,
|
|
4.5555553, 5.5555553, 6.5555553, 7.5555553,
|
|
5.4444447, 6.4444447, 7.4444447, 8.444445 ,
|
|
6.3333335, 7.3333335, 8.333334, 9.333334 ,
|
|
7.2222223, 8.222222, 9.222222, 10.222222 ,
|
|
8.111112, 9.111112, 10.111112, 11.111112 ,
|
|
9., 10., 11.000001, 12.000001 ,
|
|
9.888889, 10.888889, 11.888889, 12.888889 ,
|
|
10.777778, 11.777778, 12.777778, 13.777778 ,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
|
|
5., 6., 7., 8.,
|
|
5.888889, 6.888889, 7.888889, 8.888889,
|
|
6.7777777, 7.7777777, 8.777779, 9.777779,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111111, 13.111111, 14.111111, 15.111111,
|
|
13., 14., 15., 16.,
|
|
|
|
6.3333335, 7.3333335, 8.333334, 9.333334,
|
|
7.2222223, 8.222222, 9.222222, 10.222222,
|
|
8.111111, 9.111111, 10.111112, 11.111112,
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777779, 11.777779, 12.777779, 13.777779,
|
|
11.666667, 12.666667, 13.666668, 14.666668,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
7.666667, 8.666667, 9.666667, 10.666667,
|
|
8.555555, 9.555555, 10.555555, 11.555555,
|
|
9.444445, 10.444445, 11.444445, 12.444445,
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222222, 12.222222, 13.222222, 14.222222,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13., 14., 15.0, 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666668, 17.666668, 18.666668,
|
|
|
|
9., 10., 11., 12.,
|
|
9.888889, 10.888889, 11.888889, 12.888889,
|
|
10.777778, 11.777778, 12.777779, 13.777779,
|
|
11.666667, 12.666666, 13.666666, 14.666666,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444445, 16.444445,
|
|
14.333334, 15.333334, 16.333334, 17.333334,
|
|
15.222221, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
|
|
10.333334, 11.333334, 12.333334, 13.333334,
|
|
11.222223, 12.222223, 13.222223, 14.222223,
|
|
12.111112, 13.111112, 14.111112, 15.111112,
|
|
13.000001, 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777779, 15.777779, 16.777779, 17.777779,
|
|
15.666668, 16.666668, 17.666668, 18.666668,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
11.666667, 12.666667, 13.666667, 14.666667,
|
|
12.555555, 13.555555, 14.555555, 15.555555,
|
|
13.444445, 14.444445, 15.444446, 16.444447,
|
|
14.333334, 15.333333, 16.333332, 17.333332,
|
|
15.222222, 16.222221, 17.222221, 18.222221,
|
|
16.11111, 17.11111, 18.11111, 19.11111,
|
|
17., 18., 19., 20.,
|
|
17.88889, 18.88889, 19.88889, 20.88889,
|
|
18.777779, 19.777779, 20.777779, 21.777779,
|
|
19.666668, 20.666668, 21.666668, 22.666668,
|
|
|
|
13., 14., 15., 16.,
|
|
13.888889, 14.888889, 15.888889, 16.88889,
|
|
14.777778, 15.777778, 16.777779, 17.777779,
|
|
15.666667, 16.666666, 17.666666, 18.666666,
|
|
16.555555, 17.555555, 18.555555, 19.555555,
|
|
17.444445, 18.444445, 19.444445, 20.444445,
|
|
18.333334, 19.333334, 20.333334, 21.333334,
|
|
19.222221, 20.222221, 21.222221, 22.222221,
|
|
20.11111, 21.11111, 22.11111, 23.11111,
|
|
21., 22., 23., 24.});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_bilinear op;
|
|
auto results = op.execute({&input, &size}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printIndexedBuffer("Resized to 10x10");
|
|
// expected.printIndexedBuffer("Expected of 10x10");
|
|
// result->printShapeInfo("Resized to 10x10 shape");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, LinSpace_Test1) {
|
|
|
|
NDArray start = NDArrayFactory::create<double>(1.);
|
|
NDArray finish = NDArrayFactory::create<double>(12.);
|
|
NDArray num = NDArrayFactory::create<int>(23);
|
|
NDArray expect = NDArrayFactory::create<double>({1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5,
|
|
8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5, 12.});
|
|
|
|
nd4j::ops::lin_space op;
|
|
auto result = op.execute({&start, &finish, &num}, {}, {});
|
|
ASSERT_EQ(result->status(), ND4J_STATUS_OK);
|
|
auto res = result->at(0);
|
|
res->printIndexedBuffer("from 1 to 24");
|
|
ASSERT_TRUE(expect.equalsTo(res));
|
|
delete result;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
|
|
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
|
|
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
|
|
NDArray expected = NDArrayFactory::create<double>('c', {1, 4, 5, 4}, { 1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
1, 2, 3, 4,
|
|
1, 2, 3, 4,
|
|
5, 6, 7, 8,
|
|
5, 6, 7, 8,
|
|
9, 10, 11, 12,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24,
|
|
|
|
13, 14, 15, 16,
|
|
13, 14, 15, 16,
|
|
17, 18, 19, 20,
|
|
17, 18, 19, 20,
|
|
21, 22, 23, 24
|
|
});
|
|
//input = 1.f;
|
|
input.linspace(1);
|
|
|
|
nd4j::ops::resize_nearest_neighbor op;
|
|
auto results = op.execute({&input}, {}, {4, 5});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
|
|
//result->printIndexedBuffer("Resized to 4x5");
|
|
//expected.printIndexedBuffer("Expect for 4x5");
|
|
ASSERT_TRUE(expected.isSameShape(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_1) {
|
|
|
|
NDArray input = NDArrayFactory::create<double> ('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<double>(2.5206409f);
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.execute({&input}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_2) {
|
|
|
|
NDArray input = NDArrayFactory::create<double>('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<double>({1.0986123f, 1.8619947f, 1.0986123f});
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.execute({&input}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("REDUCE_LOGSUMEXP");
|
|
// expected.printIndexedBuffer("LSE EXPECTED");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, ReduceLogSumExpTest_3) {
|
|
|
|
NDArray input = NDArrayFactory::create<float>('c', {3,3}, {0, 1, 0, 0, 1, 0, 0, 0, 0});
|
|
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,3}, {1.0986123f, 1.8619947f, 1.0986123f});
|
|
|
|
nd4j::ops::reduce_logsumexp op;
|
|
auto results = op.execute({&input}, {1.f}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("REDUCE_LOGSUMEXP");
|
|
// expected.printIndexedBuffer("LSE EXPECTED");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_1) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {3,4});
|
|
NDArray scores = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3}, {2, 1, 0});
|
|
boxes.linspace(1.f);
|
|
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.execute({&boxes, &scores}, {}, {3});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
//result->printIndexedBuffer("OOOOUUUUTTT");
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_2) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {6,4}, {0, 0, 1, 1, 0, 0.1f, 1, 1.1f, 0, -0.1f, 1.f, 0.9f,
|
|
0, 10, 1, 11, 0, 10.1f, 1.f, 11.1f, 0, 100, 1, 101});
|
|
NDArray scales = NDArrayFactory::create<double>('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f}); //3, 0, 1, 2, 4, 5
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3}, {3,0,5});
|
|
|
|
nd4j::ops::non_max_suppression op;
|
|
auto results = op.execute({&boxes, &scales}, {0.5}, {3});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppression OUtput2");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_1) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.9, .75, .6, .95}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(3);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {1,}, {3});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.execute({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap1 Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_2) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.9, .95, .6, .75}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(3);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {3,}, {1,1,1});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.execute({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_3) {
|
|
|
|
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
|
|
0, 0, 1, 1,
|
|
0, 0.1, 1, 1.1,
|
|
0, -0.1, 1, 0.9,
|
|
0, 10, 1, 11});
|
|
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.5, .95, -.6, .75}); //3
|
|
NDArray max_num = NDArrayFactory::create<int>(5);
|
|
NDArray expected = NDArrayFactory::create<int>('c', {5,}, {1,1,1,1,1});
|
|
|
|
nd4j::ops::non_max_suppression_overlaps op;
|
|
auto results = op.execute({&boxes, &scores, &max_num}, {0.5, 0.}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
NDArray* result = results->at(0);
|
|
// result->printBuffer("NonMaxSuppressionOverlap Output");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_1) {
|
|
int axis = 0;
|
|
NDArray images = NDArrayFactory::create<double>('c', {1,2,2,1}, {1,2,3,4});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1,4}, {0,0,1,1});
|
|
NDArray boxI = NDArrayFactory::create<int>('c', {1}, {axis});
|
|
NDArray cropSize = NDArrayFactory::create<int>({1, 1});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,1,1,1}, {2.5f});
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_2) {
|
|
int axis = 0;
|
|
NDArray images = NDArrayFactory::create<float>('c', {1,2,2,1}, {1.f, 2.f, 3.f, 4.f});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1,4}, {0.f, 0.f, 1.f, 1.f});
|
|
NDArray boxI = NDArrayFactory::create<int>('c', {1}, {axis});
|
|
NDArray cropSize = NDArrayFactory::create<int>({1, 1});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,1,1,1}, {4.f});
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->printIndexedBuffer("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_3) {
|
|
|
|
NDArray images ('c', {1,2,2,1}, {1,2,3,4});
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, {0}, nd4j::DataType::INT64);
|
|
NDArray cropSize = NDArrayFactory::create<Nd4jLong>({3, 3});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1,3,3,1}, {1, 1.5f, 2., 2.f, 2.5f, 3.f, 3.f, 3.5f, 4.f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->printIndexedBuffer("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_4) {
|
|
|
|
NDArray images('c', {1,2,2,1}, {1, 2, 3, 4});
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {1}, {0}, nd4j::DataType::INT32);
|
|
NDArray cropSize = NDArrayFactory::create<int>({3, 3});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1,3,3,1}, {1, 2.f, 2.f, 3.f, 4, 4.f, 3.f, 4.f, 4.f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_CropAndResize_5) {
|
|
|
|
NDArray images('c', {1, 100, 100, 3});
|
|
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
|
|
NDArray boxI('c', {2}, {1,1}, nd4j::DataType::INT32);
|
|
NDArray cropSize = NDArrayFactory::create<int>({10, 10});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected('c', {1, 10, 10,3}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::crop_and_resize op;
|
|
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
result->printShapeInfo("Cropped and Resized");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
//ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_1) {
|
|
NDArray images = NDArrayFactory::create<float>('c', {2,4,5,3});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {
|
|
0. , 0. , 1. , 1. , 0.1, 0.2, 0.9, 0.8,
|
|
0.3, 0.3, 0.7, 0.7, 0.4, 0.4, 0.6, 0.6
|
|
});
|
|
|
|
NDArray colors = NDArrayFactory::create<float>('c', {2, 3}, {201., 202., 203., 127., 128., 129.});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {2,4,5,3}, {
|
|
127., 128., 129., 127., 128., 129., 127., 128., 129., 127., 128., 129., 201., 202., 203.,
|
|
127., 128., 129., 19., 20., 21., 22., 23., 24., 127., 128., 129., 201., 202., 203.,
|
|
127., 128., 129., 127., 128., 129., 127., 128., 129., 127., 128., 129., 201., 202., 203.,
|
|
201., 202., 203., 201. ,202. ,203., 201., 202., 203., 201., 202., 203., 201., 202., 203.,
|
|
|
|
61., 62., 63., 201., 202., 203., 201., 202., 203., 70., 71., 72., 73., 74., 75.,
|
|
76., 77., 78., 127., 128., 129., 127., 128., 129., 85., 86., 87., 88., 89., 90.,
|
|
91., 92., 93., 201., 202., 203., 201., 202., 203., 100., 101., 102., 103., 104., 105.,
|
|
106., 107., 108., 109., 110., 111., 112., 113., 114., 115., 116., 117., 118., 119., 120.
|
|
});
|
|
images.linspace(1.);
|
|
nd4j::ops::draw_bounding_boxes op;
|
|
auto results = op.execute({&images, &boxes, &colors}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Bounded boxes");
|
|
// expected.printBuffer("Bounded expec");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_2) {
|
|
NDArray images = NDArrayFactory::create<float>('c', {1,9,9,1});
|
|
NDArray boxes = NDArrayFactory::create<float>('c', {1, 1, 4}, {0.2, 0.2, 0.7, 0.7});
|
|
NDArray colors = NDArrayFactory::create<float>('c', {1, 1}, {0.95});
|
|
|
|
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
|
|
NDArray expected = NDArrayFactory::create<float>('c', {1,9,9,1}, {
|
|
1.1 , 2.1, 3.1 , 4.1 , 5.1 , 6.1 , 7.1 , 8.1 , 9.1 ,
|
|
10.1 , 0.95, 0.95, 0.95, 0.95, 0.95, 16.1 , 17.1 , 18.1 ,
|
|
19.1 , 0.95, 21.1, 22.1, 23.1, 0.95, 25.1 , 26.1 , 27.1 ,
|
|
28.1 , 0.95, 30.1, 31.1, 32.1, 0.95, 34.1 , 35.1 , 36.1 ,
|
|
37.1 , 0.95, 39.1, 40.1, 41.1, 0.95, 43.1 , 44.1 , 45.1 ,
|
|
46.1 , 0.95, 0.95, 0.95, 0.95, 0.95, 52.1 , 53.1 , 54.1 ,
|
|
55.1 , 56.1, 57.1 , 58.1 , 59.1 , 60.1 , 61.1 , 62.1 , 63.1 ,
|
|
64.1 , 65.1, 66.1 , 67.1 , 68.1 , 69.1 , 70.1 , 71.1 , 72.1 ,
|
|
73.1 , 74.1, 75.1 , 76.1 , 77.1 , 78.1 , 79.1 , 80.1 , 81.1 });
|
|
images.linspace(1.1);
|
|
nd4j::ops::draw_bounding_boxes op;
|
|
auto results = op.execute({&images, &boxes, &colors}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->syncToHost();
|
|
// result->printBuffer("Bounded boxes 2");
|
|
// expected.printBuffer("Bounded expec 2");
|
|
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
|
ASSERT_TRUE(expected.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_1) {
|
|
|
|
NDArray x('c', {2,3}, {-63.80f, -63.75f, -63.70f, -63.5f, 0.0f, 0.1f}, nd4j::DataType::FLOAT32);
|
|
NDArray exp('c', {2,3}, {-63.75, -63.75, -63.75, -63.5, 0., 0.}, nd4j::DataType::FLOAT32);
|
|
NDArray min('c', {}, {-63.65f}, nd4j::DataType::FLOAT32);
|
|
NDArray max('c', {}, {0.1f}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.execute({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized");
|
|
// exp.printBuffer("Expected");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_2) {
|
|
|
|
NDArray x = NDArrayFactory::create<double>('c', {2,3}, {-63.80, -63.75, -63.4, -63.5, 0.0, 0.1});
|
|
NDArray exp = NDArrayFactory::create<double>('c', {2,3}, {-63.75, -63.75, -63.5 , -63.5 , 0. , 0. });
|
|
NDArray min = NDArrayFactory::create<double>(-63.65);
|
|
NDArray max = NDArrayFactory::create<double>(0.1);
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars op;
|
|
auto results = op.execute({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized2");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_3) {
|
|
|
|
NDArray x = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.80, -63.75, -63.4, -63.5, 0.0, 0.1});
|
|
NDArray exp = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.75, -63.75, -63.5 , -63.5 , 0. , 0. });
|
|
NDArray min = NDArrayFactory::create<double>('c', {1},{-63.65});
|
|
NDArray max = NDArrayFactory::create<double>('c', {1}, {0.1});
|
|
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.execute({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Quantized2");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
|
|
|
|
NDArray x = NDArrayFactory::create<float>('c', {2,4,5,3});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2,4,5,3},{
|
|
1.0588236, 1.9607843, 3.019608, 4.0588236, 5.098039, 6.039216, 7.0588236, 8.039216, 9.058824,
|
|
10.058824, 10.980392, 12.078432, 13.058824, 13.921569, 15.09804, 16.058825, 17.058825, 18.117647,
|
|
19.058825, 20., 21.137257, 22.058825, 22.941177, 23.882355, 25.058825, 26.078432, 26.901962,
|
|
28.058825, 29.019608, 29.92157, 31.058825, 31.960785, 32.941177, 34.058823, 35.09804, 35.960785,
|
|
37.058823, 38.039215, 38.980392, 40.058823, 40.980392, 42.000004, 43.058826, 43.92157, 45.01961,
|
|
45., 47.058823, 48.03922, 45., 50., 51.058826, 45., 50., 54.078434,
|
|
45., 50., 57.09804, 45., 50., 60.11765, 45., 50., 62.862747,
|
|
45., 50., 65.882355, 45., 50., 68.90196, 45., 50., 70.,
|
|
45., 50., 70., 45., 50., 70., 45., 50., 70.,
|
|
45., 50., 70., 45., 50., 70., 45., 50., 70.,
|
|
45., 50., 70., 45., 50., 70., 45., 50., 70.,
|
|
45., 50., 70., 45., 50., 70., 45., 50., 70.,
|
|
45., 50., 70., 45., 50., 70., 45., 50., 70.,
|
|
45., 50., 70.});
|
|
NDArray min = NDArrayFactory::create<float>({20., 20., 20.});
|
|
NDArray max = NDArrayFactory::create<float>({65., 70., 90.});
|
|
x.linspace(1.);
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.execute({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized per channels 4");
|
|
// exp.printBuffer("Quantized per channest E");
|
|
// auto diff = *result - exp;
|
|
// diff.printIndexedBuffer("Difference");
|
|
ASSERT_TRUE(exp.isSameShapeStrict(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_5) {
|
|
NDArray x = NDArrayFactory::create<float>('c', {2, 3, 5, 4});
|
|
NDArray exp = NDArrayFactory::create<float>('c', {2, 3, 5, 4},{
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-19.92157 , -18.980392 , -18.039217 , -16.941177 ,
|
|
-16. , -15.058824 , -13.960785 , -13.0196085 ,
|
|
-11.92157 , -10.980392 , -10.039217 , -8.941177 ,
|
|
-8.000001 , -7.0588236 , -5.960785 , -5.0196085 ,
|
|
-3.9215698 , -2.9803925 , -2.039217 , -0.94117737,
|
|
0. , 0.94117737, 2.039215 , 2.9803925 ,
|
|
4.07843 , 5.0196075 , 5.960783 , 7.0588226 ,
|
|
8. , 8.941177 , 10.039215 , 10.980392 ,
|
|
12.07843 , 13.019608 , 13.960783 , 15.058823 ,
|
|
16. , 16.941177 , 18.039217 , 18.980392 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823 ,
|
|
20.07843 , 21.019608 , 21.960783 , 23.058823
|
|
});
|
|
NDArray min = NDArrayFactory::create<float>({-20., -19., -18., -17});
|
|
NDArray max = NDArrayFactory::create<float>({20., 21., 22., 23});
|
|
x.linspace(-60.);
|
|
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
|
|
auto results = op.execute({&x, &min, &max}, {}, {});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printBuffer("Quantized per channels 5");
|
|
// exp.printBuffer("Quantized per channest E");
|
|
// auto diff = *result - exp;
|
|
// diff.printIndexedBuffer("Difference");
|
|
|
|
ASSERT_TRUE(exp.isSameShapeStrict(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, batchnorm_test1) {
|
|
|
|
NDArray input ('c', {2,4}, nd4j::DataType::FLOAT32);
|
|
NDArray mean ('c', {4}, {1.05, 1.15, 1.2, 1.3}, nd4j::DataType::FLOAT32);
|
|
NDArray variance('c', {4}, {0.5, 0.7, 0.9, 1.1}, nd4j::DataType::FLOAT32);
|
|
NDArray gamma ('c', {4}, {-1.2, 1.3, -1.4, 1.5}, nd4j::DataType::FLOAT32);
|
|
NDArray beta ('c', {4}, {10, 20, -10, -20}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', {2,4}, {11.61218734, 18.52390321, -8.67185076, -21.28716864, 10.93337162, 19.14541765, -9.26213931, -20.71509369}, nd4j::DataType::FLOAT32);
|
|
|
|
input.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
// output->printBuffer();
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TYPED_TEST(TypedDeclarableOpsTests10, batchnorm_test2) {
|
|
|
|
auto input = NDArrayFactory::create<TypeParam>('c', {2,3,4});
|
|
auto mean = NDArrayFactory::create<TypeParam>('c', {4});
|
|
auto variance = NDArrayFactory::create<TypeParam>('c', {4});
|
|
auto gamma = NDArrayFactory::create<TypeParam>('c', {4});
|
|
auto beta = NDArrayFactory::create<TypeParam>('c', {4});
|
|
|
|
auto expected = NDArrayFactory::create<TypeParam>('c', {2,3,4}, {-0.52733537,-0.35763144,-0.18792751,-0.01822358, 0.15148035, 0.32118428, 0.49088821, 0.66059214, 0.83029607, 1. , 1.16970393, 1.33940786,
|
|
1.50911179, 1.67881572, 1.84851965, 2.01822358, 2.18792751, 2.35763144, 2.52733537, 2.6970393 , 2.86674323, 3.03644717, 3.2061511 , 3.37585503});
|
|
|
|
input.linspace(0.1, 0.1);
|
|
mean.assign(1.);
|
|
variance.assign(0.5);
|
|
gamma.assign(1.2);
|
|
beta.assign(1.);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
// output->printBuffer();
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TYPED_TEST(TypedDeclarableOpsTests10, batchnorm_test3) {
|
|
|
|
auto input = NDArrayFactory::create<TypeParam>('c', {2,3,4});
|
|
auto mean = NDArrayFactory::create<TypeParam>('c', {3}, {1.05, 1.1, 1.15});
|
|
auto variance = NDArrayFactory::create<TypeParam>('c', {3}, {0.5, 0.6, 0.7});
|
|
auto gamma = NDArrayFactory::create<TypeParam>('c', {3}, {1.2, 1.3, 1.4});
|
|
auto beta = NDArrayFactory::create<TypeParam>('c', {3}, {0.1, 0.2, 0.3});
|
|
|
|
auto expected = NDArrayFactory::create<TypeParam>('c', {2,3,4}, {-1.51218734,-1.34248341,-1.17277948,-1.00307555,-0.80696728,-0.6391394 ,-0.47131152,-0.30348364,-0.11832703, 0.04900378, 0.21633459, 0.38366541,
|
|
0.52425983, 0.69396376, 0.86366769, 1.03337162, 1.20696728, 1.37479516, 1.54262304, 1.71045092, 1.8896427 , 2.05697351, 2.22430432, 2.39163513,});
|
|
|
|
input.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1,1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TYPED_TEST(TypedDeclarableOpsTests10, batchnorm_test4) {
|
|
|
|
auto input = NDArrayFactory::create<TypeParam>('c', {2,3,4});
|
|
auto mean = NDArrayFactory::create<TypeParam>('c', {2,1,4}, {1.05, 1.1, 1.15, 1.2, 1.25, 1.3, 1.35, 1.4});
|
|
auto variance = NDArrayFactory::create<TypeParam>('c', {2,1,4}, {0.5, 0.6, 0.7, 0.8, 0.9, 1., 1.1, 1.2});
|
|
auto gamma = NDArrayFactory::create<TypeParam>('c', {2,1,4}, {1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9});
|
|
auto beta = NDArrayFactory::create<TypeParam>('c', {2,1,4}, {0.1, 0.2, 0.3, 0.4, 0.5, 0.66, 0.7, 0.8});
|
|
|
|
auto expected = NDArrayFactory::create<TypeParam>('c', {2,3,4}, {-1.51218734,-1.31045092,-1.12231189,-0.9416324 ,-0.83337162,-0.6391394 ,-0.45298865,-0.2708162 ,-0.1545559 , 0.03217212, 0.21633459, 0.4,
|
|
0.58432694, 0.82999915, 0.95743373, 1.14688951, 1.25894242, 1.50999575, 1.64392367, 1.84066852, 1.93355791, 2.18999235, 2.33041362, 2.53444754});
|
|
|
|
input.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1,0,2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, batchnorm_test5) {
|
|
|
|
NDArray input ('c', {2,4,2,2}, nd4j::DataType::FLOAT32);
|
|
NDArray mean ('c', {4}, {1.05, 1.15, 1.2, 1.3}, nd4j::DataType::FLOAT32);
|
|
NDArray variance('c', {4}, {0.5, 0.7, 0.9, 1.1}, nd4j::DataType::FLOAT32);
|
|
NDArray gamma ('c', {4}, {-1.2, 1.3, -1.4, 1.5}, nd4j::DataType::FLOAT32);
|
|
NDArray beta ('c', {4}, {10, 20, -10, -20}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', {2,4,2,2}, {11.612187, 11.442483, 11.272779, 11.103076, 18.990039, 19.145418, 19.300796, 19.456175, -9.557284, -9.704856, -9.852428, -10., -20.,
|
|
-19.856981, -19.713963, -19.570944, 8.896924, 8.727221, 8.557517, 8.387813, 21.476097, 21.631475, 21.786854, 21.942233, -11.918438,
|
|
-12.06601 , -12.213582, -12.361154, -17.7117, -17.568681, -17.425663, -17.282644}, nd4j::DataType::FLOAT32);
|
|
input.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1,1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
// output->printBuffer();
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, batchnorm_test6) {
|
|
|
|
NDArray input ('c', {2,2,2,4}, nd4j::DataType::FLOAT32);
|
|
NDArray mean ('c', {4}, {1.05, 1.15, 1.2, 1.3}, nd4j::DataType::FLOAT32);
|
|
NDArray variance('c', {4}, {0.5, 0.7, 0.9, 1.1}, nd4j::DataType::FLOAT32);
|
|
NDArray gamma ('c', {4}, {-1.2, 1.3, -1.4, 1.5}, nd4j::DataType::FLOAT32);
|
|
NDArray beta ('c', {4}, {10, 20, -10, -20}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', {2,2,2,4}, {11.612187, 18.523903, -8.671851, -21.287169, 10.933372, 19.145418, -9.262139, -20.715094, 10.254556, 19.766932, -9.852428, -20.143019, 9.57574 ,
|
|
20.388447, -10.442716, -19.570944,8.896924, 21.009961, -11.033005, -18.998869, 8.218109, 21.631475, -11.623294, -18.426794, 7.539293, 22.25299 ,
|
|
-12.213582, -17.854719, 6.860477, 22.874504, -12.803871, -17.282644}, nd4j::DataType::FLOAT32);
|
|
input.linspace(0.1, 0.1);
|
|
|
|
nd4j::ops::batchnorm op;
|
|
|
|
auto results = op.execute({&input, &mean, &variance, &gamma, &beta}, {1e-5}, {1,1,3});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto output = results->at(0);
|
|
|
|
ASSERT_TRUE(expected.isSameShapeStrict(output));
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, bool_broadcast_test_1) {
|
|
|
|
NDArray arr1('c', {2,2,1}, {1, 2, 3, 4}, nd4j::DataType::INT32);
|
|
NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
|
|
|
|
NDArray expd('c', {2,2,2}, {0,1,0,0, 0,0,0,1}, nd4j::DataType::BOOL);
|
|
|
|
NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
|
|
|
|
arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), &arr2, &result, true, nullptr);
|
|
// result.printIndexedBuffer();
|
|
// expd.printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(expd.isSameShape(result));
|
|
ASSERT_TRUE(expd.equalsTo(result));
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests10, printIndexedTest_1) {
|
|
|
|
NDArray arr('c', {2,2,2,2}, {1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16}, nd4j::DataType::INT32);
|
|
// NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
|
|
|
|
// NDArray expd('c', {2,2,2}, {0,1,0,0, 0,0,0,1}, nd4j::DataType::BOOL);
|
|
|
|
// NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
|
|
|
|
// arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), &arr2, &result, true, nullptr);
|
|
// result.printIndexedBuffer();
|
|
// expd.printIndexedBuffer();
|
|
|
|
// ASSERT_TRUE(expd.isSameShape(result));
|
|
// ASSERT_TRUE(expd.equalsTo(result));
|
|
// arr.printIndexedBuffer("Test Print"); // output as [1, 2, 3, 4, 5, 6, 7, 8]
|
|
//
|
|
// we want output as
|
|
// [[[1 2]
|
|
// [3 4]]
|
|
//
|
|
// [[5 6]
|
|
// [7 8]]]
|
|
//
|
|
ResultSet* lastDims = arr.allTensorsAlongDimension({3}); // last dim
|
|
size_t k = 0; // k from 0 to lastDims->size()
|
|
Nd4jLong rank = 4; // in this case
|
|
printf("[");
|
|
for (Nd4jLong i = 0; i < rank - 1; i++) {
|
|
|
|
for (Nd4jLong l = 0; l < i; ++l)
|
|
printf("\n");
|
|
printf("[");
|
|
for (Nd4jLong j = 0; j < arr.sizeAt(i); j++) {
|
|
// if (!i)
|
|
// printf("[");
|
|
// else
|
|
// printf(" ");
|
|
lastDims->at(k++)->printBuffer();
|
|
//if (k == arr.sizeAt(i))
|
|
// printf("]\n");
|
|
}
|
|
printf("]\n");
|
|
}
|
|
printf("]\n");
|
|
delete lastDims;
|
|
|
|
}
|
|
|
|
|