cavis/libnd4j/tests_cpu/layers_tests/DeclarableOpsTests10.cpp

3350 lines
153 KiB
C++

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
* Copyright (c) 2019 Konduit K.K.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// Created by raver on 8/4/2018.
//
#include "testlayers.h"
#include <ops/declarable/CustomOperations.h>
#include <NDArray.h>
#include <ops/ops.h>
#include <GradCheck.h>
using namespace nd4j;
class DeclarableOpsTests10 : public testing::Test {
public:
DeclarableOpsTests10() {
printf("\n");
fflush(stdout);
}
};
template <typename T>
class TypedDeclarableOpsTests10 : public testing::Test {
public:
TypedDeclarableOpsTests10() {
printf("\n");
fflush(stdout);
}
};
typedef ::testing::Types<double, float> TestingTypes;
TYPED_TEST_CASE(TypedDeclarableOpsTests10, TestingTypes);
TEST_F(DeclarableOpsTests10, Test_ArgMax_1) {
auto x = NDArrayFactory::create<double>('c', {3, 3});
auto e = NDArrayFactory::create<Nd4jLong>(8);
x.linspace(1.0);
nd4j::ops::argmax op;
auto result = op.execute({&x}, {}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = *result->at(0);
ASSERT_EQ(e, z);
delete result;
}
TEST_F(DeclarableOpsTests10, Test_ArgMax_2) {
auto x = NDArrayFactory::create<double>('c', {3, 3});
auto y = NDArrayFactory::create<int>('c', {1}, {1});
auto e = NDArrayFactory::create<Nd4jLong>('c', {3}, {2, 2, 2});
x.linspace(1.0);
nd4j::ops::argmax op;
auto result = op.execute({&x, &y}, {}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = *result->at(0);
//z.printIndexedBuffer("z");
//z.printShapeInfo("z shape");
ASSERT_EQ(e, z);
delete result;
}
TEST_F(DeclarableOpsTests10, Test_And_1) {
auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
auto e = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
nd4j::ops::boolean_and op;
auto result = op.execute({&x, &y}, {}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
}
TEST_F(DeclarableOpsTests10, Test_Or_1) {
auto x = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
auto y = NDArrayFactory::create<double>('c', {4}, {0, 0, 0, 1});
auto e = NDArrayFactory::create<double>('c', {4}, {1, 1, 0, 1});
nd4j::ops::boolean_or op;
auto result = op.execute({&x, &y}, {}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
}
TEST_F(DeclarableOpsTests10, Test_Not_1) {
auto x = NDArrayFactory::create<bool>('c', {4}, {true, true, false, true});
auto y = NDArrayFactory::create<bool>('c', {4}, {false, false, false, true});
// auto e = NDArrayFactory::create<bool>('c', {4}, {1, 1, 1, 0});
auto e = NDArrayFactory::create<bool>('c', {4}, {false, false, true, false});
nd4j::ops::boolean_not op;
auto result = op.execute({&x, &y}, {}, {}, {}, false, nd4j::DataType::BOOL);
ASSERT_EQ(Status::OK(), result->status());
auto res = result->at(0);
ASSERT_TRUE(e.equalsTo(res));
delete result;
}
TEST_F(DeclarableOpsTests10, Test_Size_at_1) {
auto x = NDArrayFactory::create<double>('c', {10, 20, 30});
auto e = NDArrayFactory::create<Nd4jLong>(20);
nd4j::ops::size_at op;
auto result = op.execute({&x}, {}, {1});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, MirrorPad_SGO_Test_1) {
auto in = NDArrayFactory::create<double>({1., 2., 3., 4., 5.});
// auto pad('c', {1, 2}, {1., 1.});// = Nd4j.create(new double[]{1, 1}, new long[]{1, 2});
auto pad = NDArrayFactory::create<int>('c', {1, 2}, {1, 1});
// auto value(10.0);
auto exp = NDArrayFactory::create<double>({2., 1., 2., 3., 4., 5., 4.});
nd4j::ops::mirror_pad op;
auto res = op.execute({&in, &pad}, {10.0}, {0}, {}, false, nd4j::DataType::DOUBLE);
ASSERT_EQ(res->status(), ND4J_STATUS_OK);
ASSERT_TRUE(exp.equalsTo(res->at(0)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Unique_SGO_Test_1) {
auto input = NDArrayFactory::create<double>({3., 4., 3., 1., 3., 0., 2., 4., 2., 4.});
auto expIdx = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
auto exp = NDArrayFactory::create<double>({3., 4., 1., 0., 2.});
nd4j::ops::unique op;
auto res = op.execute({&input}, {}, {});
ASSERT_EQ(res->status(), ND4J_STATUS_OK);
auto res1 = res->at(0);
auto res2 = res->at(1);
ASSERT_TRUE(exp.equalsTo(res1));
ASSERT_TRUE(expIdx.equalsTo(res2));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_1) {
auto input = NDArrayFactory::create<bool>('c', {3, 3}, {true, false, false, true, true, false, true, true, true});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {6, 2}, {0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 2LL, 0LL, 2LL, 1LL, 2LL, 2LL});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(exp.isSameShape(resA));
ASSERT_TRUE(exp.equalsTo(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_02) {
auto input = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {5, 3}, {0LL, 0LL, 0LL, 0LL, 1LL, 1LL, 1LL, 0LL, 0LL, 1LL, 0LL, 1LL, 1LL, 1LL, 0LL});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(exp.equalsTo(resA));
ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_1) {
auto cond3d = NDArrayFactory::create<bool>('c', {2, 2, 2}, {true, false, false, true, true, true, true, false});
// auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 1, 1, 1});
auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 0, 1});
auto exp3 = NDArrayFactory::create<Nd4jLong>({0, 1, 0, 1, 0});
nd4j::ops::where_np op;
auto res = op.execute({&cond3d}, {}, {});
ASSERT_TRUE(res->size() == 3);
ASSERT_EQ(res->status(), ND4J_STATUS_OK);
auto res1 = res->at(0);
auto res2 = res->at(1);
auto res3 = res->at(2);
// res1->printShapeInfo("Res1 shape"); res1->printBuffer("Res1");
// res2->printShapeInfo("Res2 shape"); res2->printBuffer("Res2");
// res3->printShapeInfo("Res3 shape"); res3->printBuffer("Res3");
ASSERT_TRUE(exp1.equalsTo(res1));
ASSERT_TRUE(exp2.equalsTo(res2));
ASSERT_TRUE(exp3.equalsTo(res3));
//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_2) {
auto cond2d = NDArrayFactory::create<bool>('c', {3, 5}, {true, true, false, false, true, true, true,
true, true, true, false, true, true, true, true});
// auto expIdx({0, 1, 0, 2, 0, 3, 4, 1, 4, 1});
auto exp1 = NDArrayFactory::create<Nd4jLong>({0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2});
auto exp2 = NDArrayFactory::create<Nd4jLong>({0, 1, 4, 0, 1, 2, 3, 4, 1, 2, 3, 4});
nd4j::ops::where_np op;
auto res = op.execute({&cond2d}, {}, {});
ASSERT_TRUE(res->size() == 2);
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
ASSERT_TRUE(exp1.equalsTo(res->at(0)));
ASSERT_TRUE(exp2.equalsTo(res->at(1)));
//ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_2) {
auto input = NDArrayFactory::create<bool>({true, false, true, true, true});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {4,1}, {0, 2, 3, 4});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::INT64);
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
// resA->printIndexedBuffer("Result A");
// resA->printShapeInfo("ShapeA");
ASSERT_TRUE(exp.equalsTo(resA));
ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_3) {
auto input = NDArrayFactory::create<bool>('c', {5, 1}, {true, false, true, true, true});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
//resA->printIndexedBuffer("Result A");
//resA->printShapeInfo("ShapeA");
ASSERT_TRUE(exp.equalsTo(resA));
ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_4) {
auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(resA->isEmpty());
//resA->printIndexedBuffer("Result A");
//resA->printShapeInfo("ShapeA");
//ASSERT_TRUE(exp.equalsTo(resA));
//ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Where_SGO_Test_5) {
auto input = NDArrayFactory::create<float>('c', {5}, {1, 0, 0, 2, 3});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {3, 1}, {0, 3, 4});
nd4j::ops::Where op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
//ASSERT_TRUE(resA->isEmpty());
ASSERT_TRUE(exp.equalsTo(resA));
ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, WhereNP_SGO_Test_4) {
auto input = NDArrayFactory::create<bool>('c', {5, 1}, {false, false, false, false, false});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {4, 2}, {0, 0, 2, 0, 3, 0, 4, 0});
nd4j::ops::where_np op;
auto res = op.execute({&input}, {}, {});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(resA->isEmpty());
//resA->printIndexedBuffer("Result A");
//resA->printShapeInfo("ShapeA");
//ASSERT_TRUE(exp.equalsTo(resA));
//ASSERT_TRUE(exp.isSameShape(resA));
// ASSERT_TRUE(expIdx.equalsTo(res->at(1)));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_1) {
auto labels = NDArrayFactory::create<double>('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto predictions = NDArrayFactory::create<double>('c', {2, 3}, {-0.3, -0.2, -0.1, 0, 0.1, 0.2});
auto weights = NDArrayFactory::create<double>('c', {2, 1}, {0., 1.});
auto exp = NDArrayFactory::create<double>(0.6);
nd4j::ops::cosine_distance_loss op;
auto res = op.execute({&predictions, &weights, &labels}, {}, {3, 1});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(exp.equalsTo(resA));
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, CosineDistance_SGO_Test_2) {
auto labels = NDArrayFactory::create<double>('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
//auto expIdx({0., 1., 0., 2., 0., 3., 4., 1., 4., 1.});
auto predictions = NDArrayFactory::create<double>('c', {2, 3}, {-0.3, -0.2, -0.1, 0, 0.1, 0.2});
auto weights = NDArrayFactory::create<double>('c', {2, 1}, {0., 1.});
auto exp = NDArrayFactory::create<double>(0.6);
nd4j::ops::cosine_distance_loss op;
auto res = op.execute({&predictions, &weights, &labels}, {}, {2, 1});
ASSERT_TRUE(res->status() == ND4J_STATUS_OK);
auto resA = res->at(0);
ASSERT_TRUE(exp.equalsTo(resA));
delete res;
}
///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, TestMarixBandPart_Test_1) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 3});
auto exp = NDArrayFactory::create<double>('c', {2, 3, 3});
x.linspace(1);
exp.linspace(1);
exp.p(0, 0, 2, 0.);
exp.p(1, 0, 2, 0.);
exp.p(0, 2, 0, 0.);
exp.p(1, 2, 0, 0.);
nd4j::ops::matrix_band_part op;
auto results = op.execute({&x}, {}, {1, 1}, {}, false, nd4j::DataType::DOUBLE);
ASSERT_EQ(ND4J_STATUS_OK, results->status());
//results->at(0)->printIndexedBuffer("MBP Test1");
//exp.printIndexedBuffer("MBP Expec");
ASSERT_TRUE(exp.equalsTo(results->at(0)));
delete results;
}
//////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, atan2_test1) {
auto y = NDArrayFactory::create<double>('c', {2, 3, 4}, {-1.001 ,-0.915 ,-0.829 ,-0.743 ,-0.657 ,-0.571 ,-0.485 ,-0.399 ,-0.313 ,-0.227 ,-0.141 ,-0.055 ,0.031 ,0.117 ,0.203 ,0.289 ,0.375 ,0.461 ,0.547 ,0.633 ,0.719 ,0.805 ,0.891 ,0.977});
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {-0.51, -0.46, -0.41, -0.36, -0.31, -0.26, -0.21, -0.16, -0.11, -0.06, -0.01, 0.04, 0.09, 0.14, 0.19, 0.24, 0.29, 0.34, 0.39, 0.44, 0.49, 0.54, 0.59, 0.61});
auto exp = NDArrayFactory::create<double>('c', {2,3,4}, {-2.04201, -2.03663, -2.03009, -2.02199,-2.01166, -1.99808, -1.97941, -1.95217,-1.90875, -1.8292 , -1.6416 , -0.942 ,
0.33172, 0.69614, 0.81846, 0.87776, 0.91253, 0.93533, 0.95141, 0.96336, 0.97259, 0.97993, 0.98591, 1.01266,});
nd4j::ops::tf_atan2 op;
auto result = op.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, LGamma_Test1) {
auto x = NDArrayFactory::create<double>('c', {3, 3}, {0.1, 0.5, 0.7, 1.5, 1.7, 2.0, 2.5, 2.7, 3.});
auto exp = NDArrayFactory::create<double>('c', {3,3}, {
2.2527127 , 0.5723649 , 0.26086727,
-0.12078223, -0.09580769, 0.,
0.28468287, 0.4348206 , 0.6931472
});
nd4j::ops::lgamma op;
auto result = op.execute({&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}, {0.5f, 1.f , 1.5f, 2.f , 2.5f, 3.f , 3.5f, 4.f , 4.5f});
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);
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);
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);
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);
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);
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);
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);
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);
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_Test_11) {
NDArray input = NDArrayFactory::create<float>('c', {1, 1, 1, 256});
input.assign(0.8f); //linspace(1);
auto size = NDArrayFactory::create<int>({65,65});
auto ex = NDArrayFactory::create<float>('c', {1,65,65,256});
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input, &size}, {}, {}, {false});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
ASSERT_NE(*result, ex);
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test_12) {
NDArray input = NDArrayFactory::create<float>('c', {1, 1, 1, 256});
input.assign(0.8f); //linspace(1);
auto size = NDArrayFactory::create<int>({65,65});
auto ex = NDArrayFactory::create<float>('c', {1,65,65,256});
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input, &size}, {}, {}, {true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
ASSERT_NE(*result, ex);
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1_1) {
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<double>('c', {1, 4, 5, 4}, {
1., 2., 3., 4.,
2.6, 3.6, 4.6, 5.6,
5., 6., 7., 8.,
7.4, 8.4, 9.4, 10.4,
9., 10., 11., 12.,
4., 5., 6., 7.,
5.6, 6.6, 7.6, 8.6,
8., 9., 10., 11.,
10.4, 11.4, 12.4, 13.4,
12., 13., 14., 15.,
10., 11., 12., 13.,
11.6, 12.6, 13.6, 14.6,
14., 15., 16., 17.,
16.4, 17.4, 18.4, 19.4,
18., 19., 20., 21.,
13., 14., 15., 16.,
14.6, 15.6, 16.6, 17.6,
17., 18., 19., 20.,
19.4, 20.4, 21.4, 22.4,
21., 22., 23., 24.
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input}, {}, {4, 5}, {false, true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printIndexedBuffer("Resized to 4x5 bilinear with half pixels");
//expected.printIndexedBuffer("Expect for 10x10");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test1_2) {
NDArray input = NDArrayFactory::create<int>('c', {1, 2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<float>('c', {1, 4, 5, 4}, {
1.f, 2.f, 3.f, 4.f,
2.6f, 3.6f, 4.6f, 5.6f,
5.f, 6.f, 7.f, 8.f,
7.4f, 8.4f, 9.4f, 10.4f,
9.f, 10.f, 11.f, 12.f,
4.f, 5.f, 6.f, 7.f,
5.6f, 6.6f, 7.6f, 8.6f,
8.f, 9.f, 10.f, 11.f,
10.4f, 11.4f, 12.4f, 13.4f,
12.f, 13.f, 14.f, 15.f,
10.f, 11.f, 12.f, 13.f,
11.6f, 12.6f, 13.6f, 14.6f,
14.f, 15.f, 16.f, 17.f,
16.4f, 17.4f, 18.4f, 19.4f,
18.f, 19.f, 20.f, 21.f,
13.f, 14.f, 15.f, 16.f,
14.6f, 15.6f, 16.6f, 17.6f,
17.f, 18.f, 19.f, 20.f,
19.4f, 20.4f, 21.4f, 22.4f,
21.f, 22.f, 23.f, 24.f
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input}, {}, {4, 5}, {false, true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printBuffer("Resized to 4x5");
// expected.printBuffer("Expect for 4x5");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test01) {
NDArray input = NDArrayFactory::create<double>('c', {2,3,4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<double>('c', {10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
20.2,21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.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");
// result->printShapeInfo("Output shape");
// expected.printShapeInfo("Expect shape");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test02) {
NDArray input = NDArrayFactory::create<float>('c', {2, 5,5,3}, {
0.7788f, 0.8012f, 0.7244f,
0.2309f, 0.7271f, 0.1804f,
0.5056f, 0.8925f, 0.5461f,
0.9234f, 0.0856f, 0.7938f,
0.6591f, 0.5555f, 0.1596f,
0.3087f, 0.1548f, 0.4695f,
0.9939f, 0.6113f, 0.6765f,
0.1800f, 0.6750f, 0.2246f,
0.0509f, 0.4601f, 0.8284f,
0.2354f, 0.9752f, 0.8361f,
0.2585f, 0.4189f, 0.7028f,
0.7679f, 0.5373f, 0.7234f,
0.2690f, 0.0062f, 0.0327f,
0.0644f, 0.8428f, 0.7494f,
0.0755f, 0.6245f, 0.3491f,
0.5793f, 0.5730f, 0.1822f,
0.6420f, 0.9143f, 0.3019f,
0.3574f, 0.1704f, 0.8395f,
0.5468f, 0.0744f, 0.9011f,
0.6574f, 0.4124f, 0.2445f,
0.4248f, 0.5219f, 0.6952f,
0.4900f, 0.2158f, 0.9549f,
0.1386f, 0.1544f, 0.5365f,
0.0134f, 0.4163f, 0.1456f,
0.4109f, 0.2484f, 0.3330f,
0.2974f, 0.6636f, 0.3808f,
0.8664f, 0.1896f, 0.7530f,
0.7215f, 0.6612f, 0.7270f,
0.5704f, 0.2666f, 0.7453f,
0.0444f, 0.3024f, 0.4850f,
0.7982f, 0.0965f, 0.7843f,
0.5075f, 0.0844f, 0.8370f,
0.6103f, 0.4604f, 0.6087f,
0.8594f, 0.4599f, 0.6714f,
0.2744f, 0.1981f, 0.4143f,
0.7821f, 0.3505f, 0.5040f,
0.1180f, 0.8307f, 0.1817f,
0.8442f, 0.5074f, 0.4471f,
0.5105f, 0.6666f, 0.2576f,
0.2341f, 0.6801f, 0.2652f,
0.5394f, 0.4690f, 0.6146f,
0.1210f, 0.2576f, 0.0769f,
0.4643f, 0.1628f, 0.2026f,
0.3774f, 0.0506f, 0.3462f,
0.5720f, 0.0838f, 0.4228f,
0.0588f, 0.5362f, 0.4756f,
0.2530f, 0.1778f, 0.0751f,
0.8977f, 0.3648f, 0.3065f,
0.4739f, 0.7014f, 0.4473f,
0.5171f, 0.1744f, 0.3487f});
NDArray expected = NDArrayFactory::create<float>('c', {2, 9, 9, 3}, {
0.7788f, 0.8012f, 0.7244f, 0.4744111f, 0.7600333f, 0.42217776f,
0.26142225f, 0.7454778f, 0.22103335f, 0.41403335f, 0.8373667f, 0.42420003f,
0.59844446f, 0.71318877f, 0.6011445f, 0.83055556f, 0.264911f, 0.7387556f,
0.83529997f, 0.2422334f, 0.5823999f, 0.6884666f, 0.5032889f, 0.23006654f,
0.6591f, 0.5555f, 0.1596f, 0.5176333f, 0.44208887f , 0.5827889f,
0.5938309f, 0.5646876f, 0.5123568f, 0.61811364f, 0.6748667f, 0.44617534f,
0.43473703f, 0.7353667f, 0.3969963f, 0.35003704f, 0.6654419f, 0.46649635f,
0.41335183f, 0.39988017f, 0.7140149f, 0.43368888f, 0.45865932f, 0.72049254f,
0.42537406f, 0.73366547f, 0.5662765f, 0.42371112f, 0.78866667f, 0.53543335f,
0.30312222f, 0.18414445f, 0.49542224f, 0.67293704f, 0.4168852f, 0.59891605f,
0.8822444f, 0.60281235f, 0.62855184f, 0.4495222f, 0.6014852f, 0.36275554f,
0.15933579f, 0.5788963f, 0.34024328f, 0.08295307f, 0.52441484f, 0.6826569f,
0.10747781f, 0.64715934f, 0.80707777f, 0.19927411f, 0.8880544f, 0.7861703f,
0.21763334f, 0.9362333f, 0.78198886f, 0.27523333f, 0.3308667f, 0.6250333f,
0.5907889f, 0.45925558f, 0.6709963f, 0.7761333f, 0.5249852f, 0.63986665f,
0.4406333f, 0.34007773f, 0.3003666f, 0.19945924f, 0.33715558f, 0.24757043f,
0.09977405f, 0.60721123f, 0.6248297f, 0.08286668f, 0.7239556f, 0.6876333f,
0.12114445f, 0.73849255f ,0.54079986f, 0.12879999f, 0.74139994f, 0.51143324f,
0.32978892f, 0.45314446f, 0.58711106f, 0.5576408f, 0.5464408f, 0.6107901f,
0.68978024f, 0.55681235f, 0.5833172f, 0.43907034f, 0.23548517f, 0.35123706f,
0.26263458f, 0.18254575f, 0.33890504f, 0.1976099f, 0.5321877f, 0.65619516f,
0.18267044f, 0.6404851f, 0.63069254f, 0.20112106f, 0.58788633f, 0.37666163f,
0.20481117f, 0.57736665f, 0.32585555f, 0.50801116f, 0.5387556f, 0.29788882f,
0.59799266f, 0.7008482f, 0.35215425f, 0.6330642f, 0.753121f, 0.42497158f,
0.44849625f, 0.36611477f, 0.5719964f, 0.36038768f, 0.1586321f, 0.70625067f,
0.416968f, 0.22043455f, 0.82134944f, 0.4690964f, 0.31661478f, 0.6675073f,
0.5182569f, 0.4357136f, 0.33437145f, 0.528089f, 0.4595333f, 0.26774442f,
0.52779996f, 0.5559667f, 0.35320008f, 0.5630963f, 0.62568885f, 0.44562602f,
0.557237f, 0.62408876f, 0.5438927f, 0.3867555f, 0.3371999f, 0.6655223f,
0.30325183f, 0.17024446f, 0.71867025f, 0.35021478f, 0.18318895f, 0.6690962f,
0.4377444f, 0.24482228f, 0.5241777f, 0.5523185f, 0.33891484f, 0.3156962f,
0.5752333f, 0.3577333f, 0.27400002f, 0.44196665f, 0.52757776f, 0.6382001f,
0.47803456f, 0.3974851f, 0.7738359f, 0.4686691f, 0.27816284f, 0.8476581f,
0.2775703f, 0.20192216f, 0.6742259f, 0.14285672f, 0.20554078f, 0.4944727f,
0.0927209f, 0.32894826f, 0.30523813f, 0.19454071f, 0.3410815f, 0.26075178f,
0.3976642f, 0.27903205f, 0.31276423f, 0.43828884f, 0.2666222f, 0.32316667f,
0.4248f, 0.5219f, 0.6952f, 0.46102223f, 0.35184443f, 0.8394778f,
0.45095554f, 0.20897777f, 0.9084111f, 0.2557333f, 0.17486666f, 0.6759666f,
0.11077777f, 0.21260004f, 0.44963327f, 0.04122221f, 0.35810006f, 0.23246664f,
0.14590007f, 0.36033332f, 0.2080667f, 0.3667334f, 0.2670555f, 0.31217784f,
0.4109f, 0.2484f, 0.333f, 0.2974f, 0.6636f, 0.3808f,
0.6135111f, 0.40026665f, 0.5875778f, 0.8503f, 0.24200003f, 0.7501111f,
0.76979995f, 0.50400007f, 0.7356667f, 0.6879222f, 0.57351106f, 0.73106664f,
0.60397774f, 0.35428885f, 0.74123335f, 0.39506656f, 0.27853334f, 0.6585333f,
0.10284433f, 0.29842222f, 0.5139222f, 0.0444f, 0.3024f, 0.485f,
0.5756222f, 0.34854442f, 0.6049667f, 0.6263938f, 0.22777282f, 0.71313334f,
0.66620123f, 0.17765433f, 0.78429013f, 0.6621518f, 0.41014817f, 0.7074074f,
0.67555183f, 0.51060987f, 0.6708259f, 0.7151259f, 0.41302344f, 0.6946963f,
0.5446962f, 0.33081108f, 0.6180703f, 0.23426408f, 0.25884813f, 0.4744469f,
0.17217779f, 0.24445555f, 0.44572222f, 0.7964111f, 0.12472223f, 0.7531556f,
0.6118617f, 0.1483889f, 0.75928515f, 0.4833407f, 0.2004667f, 0.7449173f,
0.57893336f, 0.3661889f, 0.6485592f, 0.6772543f, 0.46945432f, 0.5984506f,
0.7796679f, 0.47903457f, 0.617716f, 0.63706285f, 0.40579626f, 0.54952586f,
0.33111224f, 0.27734566f, 0.42303205f, 0.26992223f, 0.25165558f, 0.39773333f,
0.7874667f, 0.26583335f, 0.5974333f, 0.4876703f, 0.44144446f, 0.48782218f,
0.30543333f, 0.57191116f, 0.41133702f, 0.5934334f, 0.5218f, 0.46735552f,
0.73524815f, 0.5152815f, 0.47753704f, 0.6577852f, 0.5741519f, 0.41896293f,
0.50037766f, 0.57161117f, 0.3686555f, 0.28967398f, 0.5281297f, 0.3238592f,
0.24753332f, 0.5194334f, 0.31489998f, 0.72816664f, 0.37683335f, 0.5285778f,
0.3895555f, 0.5582283f, 0.32292962f, 0.18990126f, 0.6730641f, 0.18445063f,
0.5460741f, 0.5216629f, 0.31464812f, 0.6978098f, 0.45279747f, 0.36710492f,
0.5428901f, 0.5077358f, 0.30295062f, 0.42367774f, 0.53567034f, 0.28493333f,
0.32827038f, 0.54560244f, 0.2976741f, 0.30918893f, 0.5475888f, 0.30022222f,
0.5933333f, 0.44266668f, 0.59002227f, 0.3305555f, 0.4106049f, 0.31789258f,
0.16793211f, 0.36878017f, 0.11760493f, 0.40592593f, 0.28790364f, 0.20468517f,
0.5172234f, 0.22784683f, 0.27239504f, 0.4384765f, 0.19901967f, 0.3110494f,
0.43695557f, 0.19709623f, 0.34693336f, 0.4869186f, 0.21310854f, 0.38097042f,
0.49691117f, 0.21631104f, 0.3877778f, 0.37919992f, 0.4914f, 0.56826663f,
0.26019996f, 0.34673333f, 0.29495183f, 0.21430746f, 0.23090371f, 0.09418149f,
0.46084452f, 0.23042224f, 0.1835889f, 0.56450003f, 0.23844449f, 0.26893705f,
0.45383334f, 0.2592223f, 0.34819633f, 0.45761114f, 0.21635559f, 0.38596666f,
0.5376852f, 0.13105926f, 0.39607778f, 0.55370003f, 0.11400001f, 0.3981f,
0.11219993f, 0.5287333f, 0.49104443f, 0.18227404f, 0.3386963f, 0.26007527f,
0.30624574f, 0.20396544f, 0.09970618f, 0.6458075f, 0.2904593f, 0.22173704f,
0.7636852f, 0.40607417f, 0.32631359f, 0.549037f, 0.5653705f, 0.40470868f,
0.4831852f, 0.47417036f, 0.40968886f, 0.5165309f, 0.21597281f, 0.3657259f,
0.5232f, 0.16433334f, 0.3569333f, 0.0588f, 0.5362f, 0.4756f,
0.16668889f, 0.33708888f, 0.25309998f, 0.32463336f, 0.19857779f, 0.10081112f,
0.68280005f, 0.3024667f, 0.22936666f, 0.80352217f, 0.43960005f, 0.33778888f,
0.5680777f, 0.6266f, 0.41601112f, 0.4883f, 0.52573323f, 0.4144333f,
0.5123f, 0.23295549f, 0.35965553f, 0.5171f, 0.1744f, 0.3487f
});
//input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input}, {}, {9, 9});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printBuffer("Resized to 9x9");
// expected.printBuffer("Expect for 9x9");
// result->printShapeInfo("Output shape");
// expected.printShapeInfo("Expect shape");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test2) {
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
NDArray size = NDArrayFactory::create<int>({10, 10});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4}, {1., 2., 3., 4., 2.2, 3.2, 4.2, 5.2, 3.4, 4.4, 5.4, 6.4,
4.6, 5.6, 6.6, 7.6, 5.8, 6.8, 7.8, 8.8, 7., 8., 9., 10.,
8.2, 9.2, 10.2, 11.2, 9., 10., 11., 12., 9., 10., 11., 12.,
9., 10., 11., 12., 3.4, 4.4, 5.4, 6.4, 4.6, 5.6, 6.6, 7.6,
5.8, 6.8, 7.8, 8.8, 7.0, 8., 9., 10., 8.2, 9.2, 10.2, 11.2,
9.4,10.4, 11.4, 12.4,10.6, 11.6,12.6, 13.6,11.4, 12.4, 13.4, 14.4,
11.4,12.4, 13.4, 14.4,11.4, 12.4,13.4, 14.4, 5.8, 6.8, 7.8, 8.8,
7., 8., 9., 10., 8.2, 9.2,10.2, 11.2, 9.4, 10.4, 11.4, 12.4,
10.6,11.6, 12.6, 13.6,11.8, 12.8,13.8, 14.8,13.0, 14.0, 15.0, 16.,
13.8,14.8, 15.8, 16.8,13.8, 14.8,15.8, 16.8,13.8, 14.8, 15.8, 16.8,
8.2, 9.2, 10.2, 11.2, 9.4, 10.4,11.4, 12.4,10.6, 11.6, 12.6, 13.6,
11.8,12.8, 13.8, 14.8,13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
15.4,16.4, 17.4, 18.4,16.2, 17.2,18.2, 19.2,16.2, 17.2, 18.2, 19.2,
16.2,17.2, 18.2, 19.2,10.6, 11.6,12.6, 13.6,11.8, 12.8, 13.8, 14.8,
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8,19.8, 20.8,18.6, 19.6, 20.6, 21.6,
18.6,19.6, 20.6, 21.6,18.6, 19.6,20.6, 21.6,13., 14., 15., 16.,
14.2,15.2, 16.2, 17.2,15.4, 16.4,17.4, 18.4,16.6, 17.6, 18.6, 19.6,
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
13., 14., 15., 16., 14.2, 15.2,16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
20.2,21.2, 22.2, 23.2,21., 22., 23., 24., 21., 22., 23., 24.,
21., 22., 23., 24., 13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,
15.4,16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,
19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,21., 22., 23., 24.,
21., 22., 23., 24., 21., 22., 23., 24., 13., 14., 15., 16.,
14.2,15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,16.6, 17.6, 18.6, 19.6,
17.8,18.8, 19.8, 20.8,19., 20., 21., 22., 20.2, 21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.,
13., 14., 15., 16., 14.2, 15.2, 16.2, 17.2,15.4, 16.4, 17.4, 18.4,
16.6,17.6, 18.6, 19.6,17.8, 18.8, 19.8, 20.8,19., 20., 21., 22.,
20.2,21.2, 22.2, 23.2,
21., 22., 23., 24., 21., 22., 23., 24., 21., 22., 23., 24.});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.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}, {true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, ImageResizeBilinear_Test4) {
NDArray input = NDArrayFactory::create<double>('c', {1, 2,3,4});
NDArray size = NDArrayFactory::create<int>({10, 10});
NDArray expected = NDArrayFactory::create<double>('c', {1, 10, 10, 4},
{ 1., 2., 3., 4. ,
1.8888888, 2.8888888, 3.8888888, 4.888889,
2.7777777, 3.7777777, 4.7777777, 5.7777777,
3.6666667, 4.666667 , 5.666667, 6.666667 ,
4.5555553, 5.5555553, 6.5555553, 7.5555553,
5.4444447, 6.4444447, 7.4444447, 8.444445,
6.3333335, 7.3333335, 8.333334, 9.333334,
7.2222223, 8.222222, 9.222222, 10.222222,
8.111111, 9.111111, 10.111111, 11.111111,
9., 10., 11., 12.,
2.3333335, 3.3333335, 4.3333335, 5.3333335,
3.2222223, 4.2222223, 5.2222223, 6.2222223,
4.111111, 5.111111, 6.111111, 7.111111,
5., 6., 7., 8.,
5.888889, 6.888889, 7.888889, 8.888888,
6.777778, 7.777778, 8.777778, 9.777778,
7.666667, 8.666667, 9.666667, 10.666667,
8.555555, 9.555555, 10.555555, 11.555555,
9.444444, 10.444444, 11.444444, 12.444444,
10.333333, 11.333333, 12.333333, 13.333333,
3.6666667, 4.666667, 5.666667, 6.666667,
4.5555553, 5.5555553, 6.5555553, 7.5555553,
5.4444447, 6.4444447, 7.4444447, 8.444445 ,
6.3333335, 7.3333335, 8.333334, 9.333334 ,
7.2222223, 8.222222, 9.222222, 10.222222 ,
8.111112, 9.111112, 10.111112, 11.111112 ,
9., 10., 11.000001, 12.000001 ,
9.888889, 10.888889, 11.888889, 12.888889 ,
10.777778, 11.777778, 12.777778, 13.777778 ,
11.666667, 12.666667, 13.666667, 14.666667,
5., 6., 7., 8.,
5.888889, 6.888889, 7.888889, 8.888889,
6.7777777, 7.7777777, 8.777779, 9.777779,
7.666667, 8.666667, 9.666667, 10.666667,
8.555555, 9.555555, 10.555555, 11.555555,
9.444445, 10.444445, 11.444445, 12.444445,
10.333334, 11.333334, 12.333334, 13.333334,
11.222222, 12.222222, 13.222222, 14.222222,
12.111111, 13.111111, 14.111111, 15.111111,
13., 14., 15., 16.,
6.3333335, 7.3333335, 8.333334, 9.333334,
7.2222223, 8.222222, 9.222222, 10.222222,
8.111111, 9.111111, 10.111112, 11.111112,
9., 10., 11., 12.,
9.888889, 10.888889, 11.888889, 12.888889,
10.777779, 11.777779, 12.777779, 13.777779,
11.666667, 12.666667, 13.666668, 14.666668,
12.555555, 13.555555, 14.555555, 15.555555,
13.444445, 14.444445, 15.444445, 16.444445,
14.333334, 15.333334, 16.333334, 17.333334,
7.666667, 8.666667, 9.666667, 10.666667,
8.555555, 9.555555, 10.555555, 11.555555,
9.444445, 10.444445, 11.444445, 12.444445,
10.333334, 11.333334, 12.333334, 13.333334,
11.222222, 12.222222, 13.222222, 14.222222,
12.111112, 13.111112, 14.111112, 15.111112,
13., 14., 15.0, 16.,
13.888889, 14.888889, 15.888889, 16.88889,
14.777778, 15.777778, 16.777779, 17.777779,
15.666667, 16.666668, 17.666668, 18.666668,
9., 10., 11., 12.,
9.888889, 10.888889, 11.888889, 12.888889,
10.777778, 11.777778, 12.777779, 13.777779,
11.666667, 12.666666, 13.666666, 14.666666,
12.555555, 13.555555, 14.555555, 15.555555,
13.444445, 14.444445, 15.444445, 16.444445,
14.333334, 15.333334, 16.333334, 17.333334,
15.222221, 16.222221, 17.222221, 18.222221,
16.11111, 17.11111, 18.11111, 19.11111,
17., 18., 19., 20.,
10.333334, 11.333334, 12.333334, 13.333334,
11.222223, 12.222223, 13.222223, 14.222223,
12.111112, 13.111112, 14.111112, 15.111112,
13.000001, 14., 15., 16.,
13.888889, 14.888889, 15.888889, 16.88889,
14.777779, 15.777779, 16.777779, 17.777779,
15.666668, 16.666668, 17.666668, 18.666668,
16.555555, 17.555555, 18.555555, 19.555555,
17.444445, 18.444445, 19.444445, 20.444445,
18.333334, 19.333334, 20.333334, 21.333334,
11.666667, 12.666667, 13.666667, 14.666667,
12.555555, 13.555555, 14.555555, 15.555555,
13.444445, 14.444445, 15.444446, 16.444447,
14.333334, 15.333333, 16.333332, 17.333332,
15.222222, 16.222221, 17.222221, 18.222221,
16.11111, 17.11111, 18.11111, 19.11111,
17., 18., 19., 20.,
17.88889, 18.88889, 19.88889, 20.88889,
18.777779, 19.777779, 20.777779, 21.777779,
19.666668, 20.666668, 21.666668, 22.666668,
13., 14., 15., 16.,
13.888889, 14.888889, 15.888889, 16.88889,
14.777778, 15.777778, 16.777779, 17.777779,
15.666667, 16.666666, 17.666666, 18.666666,
16.555555, 17.555555, 18.555555, 19.555555,
17.444445, 18.444445, 19.444445, 20.444445,
18.333334, 19.333334, 20.333334, 21.333334,
19.222221, 20.222221, 21.222221, 22.222221,
20.11111, 21.11111, 22.11111, 23.11111,
21., 22., 23., 24.});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_bilinear op;
auto results = op.execute({&input, &size}, {}, {}, {true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printIndexedBuffer("Resized to 10x10");
// expected.printIndexedBuffer("Expected of 10x10");
// result->printShapeInfo("Resized to 10x10 shape");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, LinSpace_Test1) {
NDArray start = NDArrayFactory::create<double>(1.);
NDArray finish = NDArrayFactory::create<double>(12.);
NDArray num = NDArrayFactory::create<int>(23);
NDArray expect = NDArrayFactory::create<double>({1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5,
8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5, 12.});
nd4j::ops::lin_space op;
auto result = op.execute({&start, &finish, &num}, {}, {});
ASSERT_EQ(result->status(), ND4J_STATUS_OK);
auto res = result->at(0);
ASSERT_TRUE(expect.equalsTo(res));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1) {
NDArray input = NDArrayFactory::create<double>('c', {1, 2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<double>('c', {1, 4, 5, 4}, {
1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_nearest_neighbor op;
auto results = op.execute({&input}, {}, {4, 5}, {false, false});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printIndexedBuffer("Resized to 4x5");
// expected.printIndexedBuffer("Expect for 4x5");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test1_1) {
NDArray input = NDArrayFactory::create<int>('c', {1, 2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<int>('c', {1, 4, 5, 4}, {
1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_nearest_neighbor op;
auto results = op.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, ImageResizeNeighbor_Test1_1_1) {
NDArray input = NDArrayFactory::create<float>('c', {1, 2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<float>('c', {1, 4, 5, 4}, {
1.f, 2.f, 3.f, 4.f,
1.f, 2.f, 3.f, 4.f,
5.f, 6.f, 7.f, 8.f,
9.f, 10.f, 11.f, 12.f,
9.f, 10.f, 11.f, 12.f,
1.f, 2.f, 3.f, 4.f,
1.f, 2.f, 3.f, 4.f,
5.f, 6.f, 7.f, 8.f,
9.f, 10.f, 11.f, 12.f,
9.f, 10.f, 11.f, 12.f,
13.f, 14.f, 15.f, 16.f,
13.f, 14.f, 15.f, 16.f,
17.f, 18.f, 19.f, 20.f,
21.f, 22.f, 23.f, 24.f,
21.f, 22.f, 23.f, 24.f,
13.f, 14.f, 15.f, 16.f,
13.f, 14.f, 15.f, 16.f,
17.f, 18.f, 19.f, 20.f,
21.f, 22.f, 23.f, 24.f,
21.f, 22.f, 23.f, 24.f
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_nearest_neighbor op;
auto results = op.execute({&input}, {}, {4,5}, {false, true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
NDArray* result = results->at(0);
// result->printIndexedBuffer("Resized to 4x5");
// expected.printBuffer("Expect for 4x5");
ASSERT_TRUE(expected.isSameShape(result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, ImageResizeNeighbor_Test01) {
NDArray input = NDArrayFactory::create<double>('c', {2, 3, 4});
//NDArray<float> paddings('c', {3,2}, {0,0, 0,1, 0,0});
//NDArray<float> expected('c', {2,4,4}, {1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,0.,0.,0.,0.});
NDArray expected = NDArrayFactory::create<double>('c', {4, 5, 4}, { 1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
1, 2, 3, 4,
1, 2, 3, 4,
5, 6, 7, 8,
5, 6, 7, 8,
9, 10, 11, 12,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24,
13, 14, 15, 16,
13, 14, 15, 16,
17, 18, 19, 20,
17, 18, 19, 20,
21, 22, 23, 24
});
//input = 1.f;
input.linspace(1);
nd4j::ops::resize_nearest_neighbor op;
auto results = op.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_NonMaxSuppressing_3) {
NDArray boxes = NDArrayFactory::create<float>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
0.7412f, 0.7607f, 0.1543f, 0.5479f,
0.8223f, 0.2246f, 0.0049f, 0.6465f});
NDArray scales = NDArrayFactory::create<float>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
NDArray expected = NDArrayFactory::create<int>('c', {1}, {1});
nd4j::ops::non_max_suppression op;
auto results = op.execute({&boxes, &scales}, {0.5, 0.5}, {2});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput3");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_4) {
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
0.7412f, 0.7607f, 0.1543f, 0.5479f,
0.8223f, 0.2246f, 0.0049f, 0.6465f});
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
NDArray expected = NDArrayFactory::create<int>('c', {1}, {1});
NDArray maxSize = NDArrayFactory::create(2);
NDArray threshold = NDArrayFactory::create(0.5f);
NDArray scoreThreshold = NDArrayFactory::create(0.5);
nd4j::ops::non_max_suppression op;
auto results = op.execute({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput4");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_5) {
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
0.7412f, 0.7607f, 0.1543f, 0.5479f,
0.8223f, 0.2246f, 0.0049f, 0.6465f});
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1, 2});
NDArray maxSize = NDArrayFactory::create(2);
NDArray threshold = NDArrayFactory::create(0.5f);
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
nd4j::ops::non_max_suppression op;
auto results = op.execute({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput4");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_6) {
NDArray boxes = NDArrayFactory::create<float16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
0.7412f, 0.7607f, 0.1543f, 0.5479f,
0.8223f, 0.2246f, 0.0049f, 0.6465f});
NDArray scales = NDArrayFactory::create<float16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1,2});
NDArray maxSize = NDArrayFactory::create(2);
NDArray threshold = NDArrayFactory::create(0.5f);
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
nd4j::ops::non_max_suppression_v3 op;
auto results = op.execute({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput6");
// result->printShapeInfo("Ouput6 shape is");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_06) {
NDArray boxes = NDArrayFactory::create<bfloat16>('c', {3, 4}, {0.8115f, 0.4121f, 0.0771f, 0.4863f,
0.7412f, 0.7607f, 0.1543f, 0.5479f,
0.8223f, 0.2246f, 0.0049f, 0.6465f});
NDArray scales = NDArrayFactory::create<bfloat16>('c', {3}, {0.0029f, 0.8135f, 0.4873f}); //3, 0, 1, 2, 4, 5
NDArray expected = NDArrayFactory::create<int>('c', {2}, {1,2});
NDArray maxSize = NDArrayFactory::create(2);
NDArray threshold = NDArrayFactory::create(0.5f);
NDArray scoreThreshold = NDArrayFactory::create(-DataTypeUtils::infOrMax<float>());
nd4j::ops::non_max_suppression_v3 op;
auto results = op.execute({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput06");
// result->printShapeInfo("Ouput06 shape is");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressing_7) {
NDArray boxes = NDArrayFactory::create<float>('c', {3, 4}, {0.7788f, 0.8012f, 0.7244f, 0.2329f,
0.7271f, 0.1804f, 0.5056f, 0.8929f,
0.5461f, 0.9234f, 0.0856f, 0.7938f});
NDArray scales = NDArrayFactory::create<float>('c', {3}, {0.7717f, 0.9281f, 0.9846f}); //3, 0, 1, 2, 4, 5
NDArray maxSize = NDArrayFactory::create(0);
NDArray threshold = NDArrayFactory::create(0.5f);
NDArray scoreThreshold = NDArrayFactory::create(0.5f);
nd4j::ops::non_max_suppression_v3 op;
auto results = op.execute({&boxes, &scales, &maxSize, &threshold, &scoreThreshold}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
NDArray* result = results->at(0);
// result->printBuffer("NonMaxSuppression OUtput7");
// result->printShapeInfo("Ouput6 shape is");
ASSERT_TRUE(result->isEmpty());
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Image_NonMaxSuppressingOverlap_1) {
NDArray boxes = NDArrayFactory::create<double>('c', {4,4}, {
0, 0, 1, 1,
0, 0.1, 1, 1.1,
0, -0.1, 1, 0.9,
0, 10, 1, 11});
NDArray scores = NDArrayFactory::create<double>('c', {4}, {0.9, .75, .6, .95}); //3
NDArray max_num = NDArrayFactory::create<int>(3);
NDArray expected = NDArrayFactory::create<int>('c', {1,}, {3});
nd4j::ops::non_max_suppression_overlaps op;
auto results = op.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<double>('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);
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Image_CropAndResize_3) {
NDArray images ('c', {1,2,2,1}, {1,2,3,4}, nd4j::DataType::FLOAT32);
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
NDArray boxI('c', {1}, {0}, nd4j::DataType::INT64);
NDArray cropSize = NDArrayFactory::create<Nd4jLong>({3, 3});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
NDArray expected('c', {1,3,3,1}, {1.f, 1.5f, 2., 2.f, 2.5f, 3.f, 3.f, 3.5f, 4.f}, nd4j::DataType::FLOAT32);
nd4j::ops::crop_and_resize op;
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Image_CropAndResize_4) {
NDArray images('c', {1,2,2,1}, {1, 2, 3, 4}, nd4j::DataType::FLOAT32);
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
NDArray boxI('c', {1}, {0}, nd4j::DataType::INT32);
NDArray cropSize = NDArrayFactory::create<int>({3, 3});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
NDArray expected('c', {1,3,3,1}, {1.f, 2.f, 2.f, 3.f, 4, 4.f, 3.f, 4.f, 4.f}, nd4j::DataType::FLOAT32);
nd4j::ops::crop_and_resize op;
auto results = op.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}, nd4j::DataType::FLOAT32);
NDArray boxes('c', {1,4}, {0,0,1,1}, nd4j::DataType::FLOAT32);
NDArray boxI('c', {2}, {1,1}, nd4j::DataType::INT32);
NDArray cropSize = NDArrayFactory::create<int>({10, 10});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
NDArray expected('c', {1, 10, 10,3}, nd4j::DataType::FLOAT32);
nd4j::ops::crop_and_resize op;
auto results = op.execute({&images, &boxes, &boxI, &cropSize}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
ASSERT_TRUE(expected.isSameShapeStrict(*result));
//ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_1) {
NDArray images = NDArrayFactory::create<float>('c', {2,4,5,3});
NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {
0.f , 0.f , 1.f , 1.f , 0.1f, 0.2f, 0.9f, 0.8f,
0.3f, 0.3f, 0.7f, 0.7f, 0.4f, 0.4f, 0.6f, 0.6f
});
NDArray colors = NDArrayFactory::create<float>('c', {2, 3}, {201.f, 202.f, 203.f, 127.f, 128.f, 129.f});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
NDArray expected = NDArrayFactory::create<float>('c', {2,4,5,3}, {
127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
127.f, 128.f, 129.f, 19.f, 20.f, 21.f, 22.f, 23.f, 24.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 201.f, 202.f, 203.f,
201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f,
61.f, 62.f, 63.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 70.f, 71.f, 72.f, 73.f, 74.f, 75.f,
76.f, 77.f, 78.f, 127.f, 128.f, 129.f, 127.f, 128.f, 129.f, 85.f, 86.f, 87.f, 88.f, 89.f, 90.f,
91.f, 92.f, 93.f, 201.f, 202.f, 203.f, 201.f, 202.f, 203.f, 100.f, 101.f, 102.f, 103.f, 104.f, 105.f,
106.f, 107.f, 108.f, 109.f, 110.f, 111.f, 112.f, 113.f, 114.f, 115.f, 116.f, 117.f, 118.f, 119.f, 120.f
});
images.linspace(1.);
nd4j::ops::draw_bounding_boxes op;
auto results = op.execute({&images, &boxes, &colors}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
result->syncToHost();
// result->printBuffer("Bounded boxes");
// expected.printBuffer("Bounded expec");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_2) {
NDArray images = NDArrayFactory::create<float>('c', {1,9,9,1});
NDArray boxes = NDArrayFactory::create<float>('c', {1, 1, 4}, {0.2f, 0.2f, 0.7f, 0.7f});
NDArray colors = NDArrayFactory::create<float>('c', {1, 1}, {0.95f});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
NDArray expected = NDArrayFactory::create<float>('c', {1,9,9,1}, {
1.1f , 2.1f, 3.1f, 4.1f, 5.1f, 6.1f, 7.1f , 8.1f , 9.1f ,
10.1f , 0.95f, 0.95f, 0.95f, 0.95f, 0.95f, 16.1f , 17.1f , 18.1f ,
19.1f , 0.95f, 21.1f, 22.1f, 23.1f, 0.95f, 25.1f , 26.1f , 27.1f ,
28.1f , 0.95f, 30.1f, 31.1f, 32.1f, 0.95f, 34.1f , 35.1f , 36.1f ,
37.1f , 0.95f, 39.1f, 40.1f, 41.1f, 0.95f, 43.1f , 44.1f , 45.1f ,
46.1f , 0.95f, 0.95f, 0.95f, 0.95f, 0.95f, 52.1f , 53.1f , 54.1f ,
55.1f , 56.1f, 57.1f, 58.1f, 59.1f , 60.1f, 61.1f , 62.1f , 63.1f ,
64.1f , 65.1f, 66.1f, 67.1f, 68.1f , 69.1f, 70.1f , 71.1f , 72.1f ,
73.1f , 74.1f, 75.1f, 76.1f, 77.1f , 78.1f, 79.1f , 80.1f , 81.1f });
images.linspace(1.1);
nd4j::ops::draw_bounding_boxes op;
auto results = op.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, Image_DrawBoundingBoxes_3) {
NDArray images = NDArrayFactory::create<float>('c', {2,5,5,1}, {0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f, 0.1804f,
0.5056f, 0.8925f, 0.5461f, 0.9234f, 0.0856f, 0.7938f,
0.6591f, 0.5555f, 0.1596f, 0.3087f, 0.1548f, 0.4695f,
0.9939f, 0.6113f, 0.6765f, 0.1800f, 0.6750f, 0.2246f,
0.0509f, 0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
0.2585f, 0.4189f, 0.7028f, 0.7679f, 0.5373f, 0.7234f,
0.2690f, 0.0062f, 0.0327f, 0.0644f, 0.8428f, 0.7494f,
0.0755f, 0.6245f, 0.3491f, 0.5793f, 0.5730f, 0.1822f,
0.6420f, 0.9143f});
NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {0.7717f, 0.9281f, 0.9846f, 0.4838f,
0.6433f, 0.6041f, 0.6501f, 0.7612f,
0.7605f, 0.3948f, 0.9493f, 0.8600f,
0.7876f, 0.8945f, 0.4638f, 0.7157f});
NDArray colors = NDArrayFactory::create<float>('c', {1, 2}, {0.9441f, 0.5957f});
//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
// NDArray expected = NDArrayFactory::create<float>('c', {2,5,5,1}, {
// 0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f,
// 0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f, 0.0856f, 0.7938f, 0.9441f,
// 0.9441f, 0.1596f, 0.3087f, 0.1548f, 0.4695f, 0.9939f, 0.6113f, 0.6765f,
// 0.1800f, 0.6750f, 0.2246f, 0.0509f, 0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
// 0.2585f, 0.4189f,0.7028f,0.7679f,0.5373f,0.7234f,0.2690f,0.0062f,0.0327f,0.0644f,
// 0.8428f, 0.9441f,0.9441f,0.9441f,0.3491f,0.5793f,0.5730f,0.1822f,0.6420f,0.9143f });
NDArray expected = NDArrayFactory::create<float>('c', {2,5,5,1}, {
0.7788f, 0.8012f, 0.7244f, 0.2309f, 0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.9441f, 0.9441f, 0.1596f,
0.3087f, 0.1548f, 0.4695f, 0.9939f, 0.6113f,
0.6765f, 0.18f , 0.675f , 0.2246f, 0.0509f,
0.4601f, 0.8284f, 0.2354f, 0.9752f, 0.8361f,
0.2585f, 0.4189f, 0.7028f, 0.7679f, 0.5373f,
0.7234f, 0.269f , 0.0062f, 0.0327f, 0.0644f,
0.8428f, 0.9441f, 0.9441f, 0.9441f, 0.3491f,
0.5793f, 0.573f , 0.1822f, 0.642f , 0.9143f});
nd4j::ops::draw_bounding_boxes op;
auto results = op.execute({&images, &boxes, &colors}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// result->printBuffer("Boxes3 output");
// expected.printBuffer("Boxes3 expect");
// result->syncToHost();
// result->printBuffer("Bounded boxes 2");
// expected.printBuffer("Bounded expec 2");
ASSERT_TRUE(expected.isSameShapeStrict(*result));
ASSERT_TRUE(expected.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_1) {
NDArray x('c', {2,3}, {-63.80f, -63.75f, -63.70f, -63.5f, 0.0f, 0.1f}, nd4j::DataType::FLOAT32);
NDArray exp('c', {2,3}, {-63.75f, -63.75f, -63.75f, -63.5f, 0.f, 0.f}, nd4j::DataType::FLOAT32);
NDArray min('c', {}, {-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_03) {
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
0.777002f, 0.596913f, 0.72314f, 0.231040f, 0.509824f,
0.179308f, 0.505282f, 0.86846f, 0.349958f, 0.509824f,
0.087355f, 0.596913f, 0.65740f, 0.349958f, 0.159745f});
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// result->printIndexedBuffer("Quantized03");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_1) {
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
0.780061f, 0.596635f, 0.725987f, 0.231950f, 0.508419f,
0.180014f, 0.504643f, 0.868406f, 0.351335f, 0.508419f,
0.087699f, 0.596635f, 0.659988f, 0.351335f, 0.160374f});
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {8}, {true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// result->printIndexedBuffer("Quantized03_1");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_2) {
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
0.775297f, 0.592226f, 0.725763f, 0.237561f, 0.503245f,
0.189097f, 0.506084f, 0.868069f, 0.349355f, 0.503245f,
0.094548f, 0.592226f, 0.654610f, 0.349355f, 0.153769f});
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {6}, {true});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
result->printIndexedBuffer("Quantized03_2");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_03_3) {
NDArray x = NDArrayFactory::create<float>('c', {3,5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
0.781600f, 0.593422f, 0.728248f, 0.233790f, 0.509014f, 0.186095f, 0.508648f, 0.868295f, 0.343809f,
0.509014f, 0.093048f, 0.593422f, 0.658224f, 0.343809f, 0.165086f});
NDArray min = NDArrayFactory::create<float>({-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
NDArray max = NDArrayFactory::create<float>({0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {6}, {false});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
result->printIndexedBuffer("Quantized03_3");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
NDArray x = NDArrayFactory::create<float>('c', {2,4,5,3});
NDArray exp = NDArrayFactory::create<float>('c', {2,4,5,3},{
1.0588236f, 1.9607843f, 3.019608f, 4.0588236f, 5.098039f, 6.039216f, 7.0588236f, 8.039216f, 9.058824f,
10.058824f, 10.980392f, 12.078432f, 13.058824f, 13.921569f, 15.09804f, 16.058825f, 17.058825f, 18.117647f,
19.058825f, 20.f, 21.137257f, 22.058825f, 22.941177f, 23.882355f, 25.058825f, 26.078432f, 26.901962f,
28.058825f, 29.019608f, 29.92157f, 31.058825f, 31.960785f, 32.941177f, 34.058823f, 35.09804f, 35.960785f,
37.058823f, 38.039215f, 38.980392f, 40.058823f, 40.980392f, 42.000004f, 43.058826f, 43.92157f, 45.01961f,
45.f, 47.058823f, 48.03922f, 45.f, 50.f, 51.058826f, 45.f, 50.f, 54.078434f,
45.f, 50.f, 57.09804f, 45.f, 50.f, 60.11765f, 45.f, 50.f, 62.862747f,
45.f, 50.f, 65.882355f, 45.f, 50.f, 68.90196f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f, 45.f, 50.f, 70.f, 45.f, 50.f, 70.f,
45.f, 50.f, 70.f});
NDArray min = NDArrayFactory::create<float>({20.f, 20.f, 20.f});
NDArray max = NDArrayFactory::create<float>({65.f, 70.f, 90.f});
x.linspace(1.);
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.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},{
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-19.92157f, -18.980392f, -18.039217f, -16.941177f,
-16.f, -15.058824f, -13.960785f, -13.0196085f,
-11.92157f, -10.980392f, -10.039217f, -8.941177f,
-8.000001f, -7.0588236f, -5.960785f, -5.0196085f,
-3.9215698f, -2.9803925f, -2.039217f, -0.94117737f,
0.f, 0.94117737f, 2.039215f, 2.9803925f,
4.07843f, 5.0196075f, 5.960783f, 7.0588226f,
8.f, 8.941177f, 10.039215f, 10.980392f,
12.07843f, 13.019608f, 13.960783f, 15.058823f,
16.f, 16.941177f, 18.039217f, 18.980392f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f,
20.07843f, 21.019608f, 21.960783f, 23.058823f
});
NDArray min = NDArrayFactory::create<float>({-20.f, -19.f, -18.f, -17.f});
NDArray max = NDArrayFactory::create<float>({20.f, 21.f, 22.f, 23.f});
x.linspace(-60.);
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.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, FakeQuantWithMinMaxVars_Test_6) {
NDArray x = NDArrayFactory::create<float>('c', {3, 5}, {0.7788f,0.8012f, 0.7244f, 0.2309f,0.7271f,
0.1804f, 0.5056f, 0.8925f, 0.5461f, 0.9234f,
0.0856f, 0.7938f, 0.6591f, 0.5555f, 0.1596f});
// NDArray exp = NDArrayFactory::create<float>('c', {3, 5},{
// 0.7801f, 0.5966f, 0.7260f, 0.2320f, 0.5084f,
// 0.1800f, 0.5046f, 0.8684f, 0.3513f, 0.5084f,
// 0.0877f, 0.5966f, 0.6600f, 0.3513f, 0.1604f
// });
NDArray exp = NDArrayFactory::create<float>('c', {3,5}, {
0.77700233f, 0.596913f, 0.72314f, 0.23104f, 0.50982356f,
0.17930824f, 0.50528157f, 0.86846f, 0.34995764f, 0.50982356f,
0.08735529f, 0.596913f, 0.6574f, 0.34995764f, 0.15974471f});
NDArray min = NDArrayFactory::create<float>('c', {5}, {-0.2283f, -0.0719f, -0.0154f, -0.5162f, -0.3567f});
NDArray max = NDArrayFactory::create<float>('c', {5}, {0.9441f, 0.5957f, 0.8669f, 0.3502f, 0.5100f});
// x.linspace(-60.);
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.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, FakeQuantWithMinMaxVars_Test_7) {
NDArray x = NDArrayFactory::create<float>('c', {100});
NDArray exp = NDArrayFactory::create<float>('c', {100}, {
0.f, 0.01176471f, 0.01960784f, 0.03137255f, 0.03921569f,
0.0509804f, 0.05882353f, 0.07058824f, 0.07843138f, 0.09019608f,
0.09803922f, 0.10980393f, 0.12156864f, 0.12941177f, 0.14117648f,
0.14901961f, 0.16078432f, 0.16862746f, 0.18039216f, 0.18823531f,
0.20000002f, 0.21176472f, 0.21960786f, 0.23137257f, 0.2392157f,
0.2509804f, 0.25882354f, 0.27058825f, 0.2784314f, 0.2901961f,
0.3019608f, 0.30980393f, 0.32156864f, 0.32941177f, 0.34117648f,
0.34901962f, 0.36078432f, 0.36862746f, 0.3803922f, 0.38823533f,
0.40000004f, 0.41176474f, 0.41960788f, 0.43137258f, 0.43921572f,
0.45098042f, 0.45882356f, 0.47058827f, 0.4784314f, 0.4901961f,
0.49803925f, 0.50980395f, 0.52156866f, 0.5294118f, 0.5411765f,
0.54901963f, 0.56078434f, 0.5686275f, 0.5803922f, 0.5882353f,
0.6f, 0.6117647f, 0.61960787f, 0.6313726f, 0.6392157f,
0.6509804f, 0.65882355f, 0.67058825f, 0.6784314f, 0.6901961f,
0.69803923f, 0.70980394f, 0.72156864f, 0.7294118f, 0.7411765f,
0.7490196f, 0.7607844f, 0.7686275f, 0.7803922f, 0.78823537f,
0.8000001f, 0.8117648f, 0.8196079f, 0.8313726f, 0.83921576f,
0.85098046f, 0.8588236f, 0.8705883f, 0.87843144f, 0.89019614f,
0.8980393f, 0.909804f, 0.9215687f, 0.9294118f, 0.94117653f,
0.9490197f, 0.9607844f, 0.9686275f, 0.9803922f, 0.98823535f
});
NDArray min = NDArrayFactory::create<float>('c', {1},{0.0f});
NDArray max = NDArrayFactory::create<float>('c', {1}, {1.f});
x.linspace(0., 0.01);
nd4j::ops::fake_quant_with_min_max_vars op;
auto results = op.execute({&x, &min, &max}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// result->printBuffer("Quantized7");
// exp.printBuffer("Expected 7");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
//////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_8) {
NDArray x = NDArrayFactory::create<float>('c', {10});
NDArray exp = NDArrayFactory::create<float>('c', {10}, {
0.f, 0.09803922f, 0.20000002f, 0.3019608f, 0.40000004f, 0.49803925f,
0.6f, 0.69803923f, 0.8000001f, 0.8980393f
});
NDArray min = NDArrayFactory::create<float>('c', {1},{0.0f});
NDArray max = NDArrayFactory::create<float>('c', {1}, {1.f});
x.linspace(0., 0.1);
nd4j::ops::fake_quant_with_min_max_vars op;
auto results = op.execute({&x, &min, &max}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// x.printBuffer("SourInput8");
// result->printBuffer("Quantized8");
// exp.printBuffer("Expected 8");
ASSERT_TRUE(exp.isSameShapeStrict(*result));
ASSERT_TRUE(exp.equalsTo(result));
delete results;
}
///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, bool_broadcast_test_1) {
NDArray arr1('c', {2,2,1}, {1, 2, 3, 4}, nd4j::DataType::INT32);
NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
NDArray expd('c', {2,2,2}, {false, true, false, false, false, false, false, true}, nd4j::DataType::BOOL);
NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), arr2, result, true);
// result.printIndexedBuffer();
// expd.printIndexedBuffer();
ASSERT_TRUE(expd.isSameShape(result));
ASSERT_TRUE(expd.equalsTo(result));
}
///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, printIndexedTest_1) {
NDArray arr('c', {2,2,2,2}, {1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16}, nd4j::DataType::INT32);
// NDArray arr2('c', { 2,2}, {0, 1, 0, 4}, nd4j::DataType::INT32);
// NDArray expd('c', {2,2,2}, {0,1,0,0, 0,0,0,1}, nd4j::DataType::BOOL);
// NDArray result('c', {2,2,2}, nd4j::DataType::BOOL);
// arr1.applyTrueBroadcast(nd4j::BroadcastBoolOpsTuple::custom(scalar::EqualTo, pairwise::EqualTo, broadcast::EqualTo), &arr2, &result, true, nullptr);
// result.printIndexedBuffer();
// expd.printIndexedBuffer();
// ASSERT_TRUE(expd.isSameShape(result));
// ASSERT_TRUE(expd.equalsTo(result));
// arr.printIndexedBuffer("Test Print"); // output as [1, 2, 3, 4, 5, 6, 7, 8]
//
// we want output as
// [[[1 2]
// [3 4]]
//
// [[5 6]
// [7 8]]]
//
ResultSet lastDims = arr.allTensorsAlongDimension({3}); // last dim
size_t k = 0; // k from 0 to lastDims->size()
Nd4jLong rank = 4; // in this case
printf("[");
for (Nd4jLong i = 0; i < rank - 1; i++) {
for (Nd4jLong l = 0; l < i; ++l)
printf("\n");
printf("[");
for (Nd4jLong j = 0; j < arr.sizeAt(i); j++) {
// if (!i)
// printf("[");
// else
// printf(" ");
lastDims.at(k++)->printBuffer();
//if (k == arr.sizeAt(i))
// printf("]\n");
}
printf("]\n");
}
printf("]\n");
}