Brutex
/
cavis
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
cavis/libnd4j/tests_cpu/layers_tests/DeclarableOpsTests5.cpp

2939 lines
130 KiB
C++
Raw Blame History

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* 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
******************************************************************************/
//
// @author raver119@gmail.com
//
#include "testlayers.h"
#include <ops/declarable/CustomOperations.h>
#include <helpers/helper_hash.h>
#include <NDArray.h>
#include <array/NDArrayList.h>
using namespace nd4j;
using namespace nd4j::graph;
class DeclarableOpsTests5 : public testing::Test {
public:
DeclarableOpsTests5() {
printf("\n");
fflush(stdout);
}
};
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_1) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
auto exp = NDArrayFactory::create<double>('c', {3, 5, 4}, {1.0, 6.0, 11.0, 16.0, 2.0, 7.0, 12.0, 17.0, 3.0, 8.0, 13.0, 18.0, 4.0, 9.0, 14.0, 19.0, 5.0, 10.0, 15.0, 20.0, 21.0, 26.0, 31.0, 36.0, 22.0, 27.0, 32.0, 37.0, 23.0, 28.0, 33.0, 38.0, 24.0, 29.0, 34.0, 39.0, 25.0, 30.0, 35.0, 40.0, 41.0, 46.0, 51.0, 56.0, 42.0, 47.0, 52.0, 57.0, 43.0, 48.0, 53.0, 58.0, 44.0, 49.0, 54.0, 59.0, 45.0, 50.0, 55.0, 60.0});
x.linspace(1);
x.reshapei('c', {3, 4, 5});
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {0, 2, 1});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_0) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
x.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0});
x.reshapei('c', {3, 4, 5});
// x.printShapeInfo("{0, 1, 2} shape");
// x.printBuffer("{0, 1, 2} data");
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {0, 1, 2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_2) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
x.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {4, 3, 5}, {1.0, 2.0, 3.0, 4.0, 5.0, 21.0, 22.0, 23.0, 24.0, 25.0, 41.0, 42.0, 43.0, 44.0, 45.0, 6.0, 7.0, 8.0, 9.0, 10.0, 26.0, 27.0, 28.0, 29.0, 30.0, 46.0, 47.0, 48.0, 49.0, 50.0, 11.0, 12.0, 13.0, 14.0, 15.0, 31.0, 32.0, 33.0, 34.0, 35.0, 51.0, 52.0, 53.0, 54.0, 55.0, 16.0, 17.0, 18.0, 19.0, 20.0, 36.0, 37.0, 38.0, 39.0, 40.0, 56.0, 57.0, 58.0, 59.0, 60.0});
x.reshapei('c', {3, 4, 5});
// x.printShapeInfo("{1, 0, 2} shape");
// x.printBuffer("{1, 0, 2} data");
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {1, 0, 2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_3) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
x.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {4, 5, 3}, {1.0, 21.0, 41.0, 2.0, 22.0, 42.0, 3.0, 23.0, 43.0, 4.0, 24.0, 44.0, 5.0, 25.0, 45.0, 6.0, 26.0, 46.0, 7.0, 27.0, 47.0, 8.0, 28.0, 48.0, 9.0, 29.0, 49.0, 10.0, 30.0, 50.0, 11.0, 31.0, 51.0, 12.0, 32.0, 52.0, 13.0, 33.0, 53.0, 14.0, 34.0, 54.0, 15.0, 35.0, 55.0, 16.0, 36.0, 56.0, 17.0, 37.0, 57.0, 18.0, 38.0, 58.0, 19.0, 39.0, 59.0, 20.0, 40.0, 60.0});
x.reshapei('c', {3, 4, 5});
// x.printShapeInfo("{1, 2, 0} shape");
// x.printBuffer("{1, 2, 0} data");
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {1, 2, 0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_4) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
x.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {5, 3, 4}, {1.0, 6.0, 11.0, 16.0, 21.0, 26.0, 31.0, 36.0, 41.0, 46.0, 51.0, 56.0, 2.0, 7.0, 12.0, 17.0, 22.0, 27.0, 32.0, 37.0, 42.0, 47.0, 52.0, 57.0, 3.0, 8.0, 13.0, 18.0, 23.0, 28.0, 33.0, 38.0, 43.0, 48.0, 53.0, 58.0, 4.0, 9.0, 14.0, 19.0, 24.0, 29.0, 34.0, 39.0, 44.0, 49.0, 54.0, 59.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0});
x.reshapei('c', {3, 4, 5});
// x.printShapeInfo("{2, 0, 1} shape");
// x.printBuffer("{2, 0, 1} data");
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {2, 0, 1});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_PermuteEquality_5) {
auto x = NDArrayFactory::create<double>('c', {1, 60});
x.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {5, 4, 3}, {1.0, 21.0, 41.0, 6.0, 26.0, 46.0, 11.0, 31.0, 51.0, 16.0, 36.0, 56.0, 2.0, 22.0, 42.0, 7.0, 27.0, 47.0, 12.0, 32.0, 52.0, 17.0, 37.0, 57.0, 3.0, 23.0, 43.0, 8.0, 28.0, 48.0, 13.0, 33.0, 53.0, 18.0, 38.0, 58.0, 4.0, 24.0, 44.0, 9.0, 29.0, 49.0, 14.0, 34.0, 54.0, 19.0, 39.0, 59.0, 5.0, 25.0, 45.0, 10.0, 30.0, 50.0, 15.0, 35.0, 55.0, 20.0, 40.0, 60.0});
x.reshapei('c', {3, 4, 5});
// x.printShapeInfo("{2, 1, 0} shape");
// x.printBuffer("{2, 1, 0} data");
nd4j::ops::permute op;
auto result = op.execute({&x}, {}, {2, 1, 0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_TTS_bp_1) {
auto x = NDArrayFactory::create<double>('c', {2, 1, 3});
auto eps = NDArrayFactory::create<double>('c', {2, 4, 3});
auto exp = NDArrayFactory::create<double>('c', {2, 1, 3}, {22.f, 26.f, 30.f, 70.f, 74.f, 78.f});
eps.linspace(1.f);
nd4j::ops::tile_to_shape_bp op;
auto result = op.execute({&x, &eps}, {}, {2, 4, 3});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
// z->printShapeInfo("RES shape");
// x.printShapeInfo("EXP shape");
// z->printIndexedBuffer("RES output");
ASSERT_TRUE(x.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_Rdiv_bp_1) {
auto x = NDArrayFactory::create<double>('c', {3, 1}, {1, 2, 3});
auto y = NDArrayFactory::create<double>('c', {1, 4}, {1, 2, 3, 4});
auto eps = NDArrayFactory::create<double>('c', {3, 4}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
nd4j::ops::reversedivide op_ff;
auto result_ff = op_ff.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result_ff->status());
auto z_ff = result_ff->at(0);
ASSERT_TRUE(eps.isSameShape(z_ff));
nd4j::ops::reversedivide_bp op_bp;
auto result_bp = op_bp.execute({&x, &y, &eps}, {}, {});
ASSERT_EQ(Status::OK(), result_bp->status());
auto z_bp = result_bp->at(0);
ASSERT_TRUE(x.isSameShape(z_bp));
delete result_ff;
delete result_bp;
}
TEST_F(DeclarableOpsTests5, Test_Boolean_diff_1) {
auto x = NDArrayFactory::create<double>('c', {1, 1}, {1.0f});
auto y = NDArrayFactory::create<double>(2.0f);
nd4j::ops::less op;
auto result = op.execute({&x, &y}, {}, {}, {}, false, nd4j::DataType::BOOL);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(result->at(0)->t<bool>(0), true);
delete result;
}
TEST_F(DeclarableOpsTests5, Test_SetSeed_1) {
auto x = NDArrayFactory::create<int>('c', {1, 1}, {120});
auto y = NDArrayFactory::create<int>(5);
nd4j::ops::set_seed op;
auto result = op.execute({&x, &y}, {}, {120, 5}, {}, false, nd4j::DataType::INT32);
ASSERT_EQ(Status::OK(), result->status());
// result->at(0)->printIndexedBuffer("RES SEED");
nd4j::ops::get_seed getOp;
auto getRes = getOp.execute({}, {}, {});
ASSERT_EQ(Status::OK(), getRes->status());
// getRes->at(0)->printIndexedBuffer("Output RES GET SEED");
// ASSERT_EQ(result->at(0)->t<bool>(0), true);
delete result;
delete getRes;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, scatterMul_test1) {
auto matrix = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
NDArray idc('c', {1}, {0LL}, nd4j::DataType::INT64);
auto updates = NDArrayFactory::create<float>('c', {1, 2}, {10, 1});
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {10, 2, 3, 4});
nd4j::ops::scatter_mul op;
auto result = op.execute({&matrix, &idc, &updates}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, scatterDiv_test1) {
auto matrix = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
NDArray idc('c', {1}, {0LL}, nd4j::DataType::INT64);
auto updates = NDArrayFactory::create<float>('c', {1, 2}, {10, 1});
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {0.10, 2, 3, 4});
nd4j::ops::scatter_div op;
auto result = op.execute({&matrix, &idc, &updates}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
// z->printIndexedBuffer("Scatter Div");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, scatterSub_test1) {
auto matrix = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
NDArray idc('c', {1}, {0LL}, nd4j::DataType::INT64);
auto updates = NDArrayFactory::create<float>('c', {1, 2}, {10, 1});
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {-9, 1, 3, 4});
nd4j::ops::scatter_sub op;
auto result = op.execute({&matrix, &idc, &updates}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
// z->printIndexedBuffer("Scatter Sub");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, hardsigmoid_test1) {
auto matrix = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {0.7, 0.9, 1, 1});
nd4j::ops::hardsigmoid op;
auto result = op.execute({&matrix}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, hardsigmoid_test2) {
auto matrix = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
auto eps = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {0.2, 0.4, 0, 0});
nd4j::ops::hardsigmoid_bp op;
auto result = op.execute({&matrix, &eps}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, hardtanh_test1) {
auto matrix = NDArrayFactory::create<float>('c', {3, 3}, {-4, -3, -2, -1, 0, 1, 2, 3, 4});
auto exp = NDArrayFactory::create<float>('c', {3, 3}, {-1, -1, -1, -1, 0, 1, 1, 1, 1});
nd4j::ops::hardtanh op;
auto result = op.execute({&matrix}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
// z->printIndexedBuffer("Hardtanh 2x2");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, hardtanh_test2) {
auto matrix = NDArrayFactory::create<float>('c', {3, 3}, {-4, -3, -2, -1, 0, 1, 2, 3, 4});
auto eps = NDArrayFactory::create<float>('c', {3, 3}, {1, 2, 3, 4, 5, 6, 7, 8, 9});
auto exp = NDArrayFactory::create<float>('c', {3, 3}, {0, 0, 0, 4, 5, 6, 0, 0, 0});
nd4j::ops::hardtanh_bp op;
auto result = op.execute({&matrix, &eps}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
// z->printIndexedBuffer("Hardtanh_bp 2x2");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, histogram_test1) {
auto matrix = NDArrayFactory::create<double>('c', {3, 3}, {-4, -3, -2, -1, 0, 1, 2, 3, 4});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {3}, {3, 3, 3});
nd4j::ops::histogram op;
auto result = op.execute({&matrix}, {}, {3}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
// z->printIndexedBuffer("Histogram3");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, histogram_test2) {
auto matrix = NDArrayFactory::create<double>('c', {3}, {1, 2, 1});
auto exp = NDArrayFactory::create<Nd4jLong>('c', {4}, {2, 0, 0, 1});
nd4j::ops::histogram op;
auto result = op.execute({&matrix}, {}, {4}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Identity_test1) {
auto matrix = NDArrayFactory::create<float>('c', {3, 3}, {-4, -3, -2, -1, 0, 1, 2, 3, 4});
// auto exp = NDArrayFactory::create<Nd4jLong>('c', {3, 3}, {3, 3, 3});
nd4j::ops::identity op;
auto result = op.execute({&matrix}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(matrix.equalsTo(z));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Identity_test2) {
auto matrix = NDArrayFactory::create<float>('c', {3, 3}, {-4, -3, -2, -1, 0, 1, 2, 3, 4});
auto eps = NDArrayFactory::create<float>('c', {3, 3}, {1,2,3,4,5,6,7,8,9});
// auto exp = NDArrayFactory::create<float>('c', {3,3});
nd4j::ops::identity_bp op;
auto result = op.execute({&matrix, &eps}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(z->equalsTo(eps));
delete result;
}
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Log1p_test1) {
auto matrix = NDArrayFactory::create<float>('c', {3, 3}, {4, 3, 2, 1, 0, 1, 2, 3, 4});
auto y = NDArrayFactory::create<float>('c', {3,3}, {5,4,3,2,1,2,3,4,5});
// auto eps = NDArrayFactory::create<float>('c', {3, 3}, {1,2,3,4,5,6,7,8,9});
// auto exp = NDArrayFactory::create<float>('c', {3,3});
nd4j::ops::Log1p op;
y.applyTransform(nd4j::transform::Log, nullptr, nullptr);
auto result = op.execute({&matrix}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(z->equalsTo(y));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_SpaceToBatch_1) {
auto x = NDArrayFactory::create<double>('c', {1, 2, 2, 3}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
auto exp = NDArrayFactory::create<double>('c', {4, 1, 1, 3}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
auto paddings = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 0, 0});
nd4j::ops::space_to_batch op;
auto result = op.execute({&x, &paddings}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_SpaceToBatch_2) {
auto x = NDArrayFactory::create<double>('c', {1, 2, 2, 1}, {1, 2, 3, 4});
auto exp = NDArrayFactory::create<double>('c', {4, 1, 1, 1}, {1, 2, 3, 4});
auto paddings = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 0, 0});
nd4j::ops::space_to_batch op;
auto result = op.execute({&x, &paddings}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_SpaceToBatch_3) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 4, 1}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
auto paddings = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 2, 0});
auto exp = NDArrayFactory::create<double>('c', {8, 1, 3, 1}, {0, 1, 3, 0, 9, 11,0, 2, 4, 0, 10, 12,0, 5, 7, 0, 13, 15,0, 6, 8, 0, 14, 16});
nd4j::ops::space_to_batch op;
auto result = op.execute({&x, &paddings}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
// z->printIndexedBuffer();
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_SpaceToBatch_4) {
const int blockSize = 2;
NDArray x('c', {3, 3*blockSize - 1 - 2, 4*blockSize - 2 - 3, 2}, {147, 148, 219, 220, 149, 150, 11, 12, 83, 84, 13, 14, 155, 156, 227, 228, 157, 158, 171, 172, 243, 244, 173, 174, 35, 36, 107, 108, 37, 38, 179, 180, 251, 252, 181, 182, 195, 196, 267, 268, 197, 198, 59, 60, 131, 132, 61, 62, 203, 204, 275, 276, 205, 206}, nd4j::DataType::FLOAT32);
NDArray paddings = NDArrayFactory::create<int>('c', {2, 2}, {1, 2, 2, 3});
NDArray exp('c', {3*blockSize*blockSize, 3, 4, 2}, {0,0, 0,0, 0,0, 0,0, 0,0, 11,12, 13,14, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0,
0,0, 0,0, 0,0, 35,36, 37,38, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 59,60, 61,62, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0,
0,0, 0,0, 0,0, 0,0, 83,84, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 107, 108, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0,
0,0, 0,0, 0,0, 0,0, 0,0, 131, 132, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 147, 148, 149, 150, 0,0, 0,0, 155, 156, 157, 158,
0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 171, 172, 173, 174, 0,0, 0,0, 179, 180, 181, 182, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 195, 196,
197, 198, 0,0, 0,0, 203, 204, 205, 206, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 219, 220, 0,0, 0,0, 0,0, 227, 228, 0,0, 0,0, 0,0,
0,0, 0,0, 0,0, 0,0, 243, 244, 0,0, 0,0, 0,0, 251, 252, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0, 267, 268, 0,0, 0,0, 0,0, 275,
276, 0,0, 0,0, 0,0, 0,0, 0,0, 0,0}, nd4j::DataType::FLOAT32);
nd4j::ops::space_to_batch op;
auto result = op.execute({&x, &paddings}, {}, {blockSize});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
// z->printIndexedBuffer();
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_BatchToSpace_1) {
auto x = NDArrayFactory::create<double>('c', {4, 1, 1, 3}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
auto exp = NDArrayFactory::create<double>('c', {1, 2, 2, 3}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
auto crops = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 0, 0});
nd4j::ops::batch_to_space op;
auto result = op.execute({&x, &crops}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
// z->printIndexedBuffer();
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_BatchToSpace_2) {
auto x = NDArrayFactory::create<double>('c', {4, 1, 1, 1}, {1, 2, 3, 4});
auto exp = NDArrayFactory::create<double>('c', {1, 2, 2, 1}, {1, 2, 3, 4});
auto crops = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 0, 0});
nd4j::ops::batch_to_space op;
auto result = op.execute({&x, &crops}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_BatchToSpace_3) {
auto x = NDArrayFactory::create<double>('c', {8, 1, 3, 1}, {0, 1, 3, 0, 9, 11,
0, 2, 4, 0, 10, 12,
0, 5, 7, 0, 13, 15,
0, 6, 8, 0, 14, 16});
auto exp = NDArrayFactory::create<double>('c', {2, 2, 4, 1}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
auto crops = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 2, 0});
nd4j::ops::batch_to_space op;
auto result = op.execute({&x, &crops}, {}, {2});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_BatchToSpace_4) {
const int blockSize = 2;
NDArray x('c', {3*blockSize*blockSize, 3, 4, 2}, nd4j::DataType::FLOAT32);
x.linspace(1, 1);
NDArray crops = NDArrayFactory::create<int>('c', {2, 2}, {1, 2, 2, 3});
NDArray exp('c', {3, 3*blockSize - 1 - 2, 4*blockSize - 2 - 3, 2}, {147, 148, 219, 220, 149, 150, 11, 12, 83, 84, 13, 14, 155, 156, 227, 228, 157, 158, 171, 172, 243, 244, 173, 174, 35, 36, 107, 108, 37, 38, 179, 180, 251, 252, 181, 182, 195, 196, 267, 268, 197, 198, 59, 60, 131, 132, 61, 62, 203, 204, 275, 276, 205, 206}, nd4j::DataType::FLOAT32);
nd4j::ops::batch_to_space op;
auto result = op.execute({&x, &crops}, {}, {blockSize});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, eye_test1) {
auto expected = NDArrayFactory::create<float>('c', {3, 3}, {1, 0, 0, 0, 1, 0, 0, 0, 1});
nd4j::ops::eye op;
auto results = op.execute({}, {}, {-99, 3});
auto output = results->at(0);
// output->printIndexedBuffer();
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, eye_test2) {
auto expected = NDArrayFactory::create<float>('c', {3, 4}, {1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0});
nd4j::ops::eye op;
auto results = op.execute({}, {}, {-99, 3, 4});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, eye_test3) {
auto expected = NDArrayFactory::create<int>('c', {2, 3, 4}, {1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0});
nd4j::ops::eye op;
auto results = op.execute({}, {9 /*int*/}, {-99, 3, 4, 2});
auto output = results->at(0);
// output->printIndexedBuffer("Output eye");
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, eye_test4) {
auto expected = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {1., 0., 0., 0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 0., 1., 0.});
nd4j::ops::eye op;
auto results = op.execute({}, {6/*double*/}, {-99, 3, 4, 2, 2});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, eye_test5) {
nd4j::ops::eye op;
auto result = op.execute({},{},{3, 2});
auto z = result->at(0);
ASSERT_EQ(ND4J_STATUS_OK, result->status());
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test1) {
auto input = NDArrayFactory::create<double>('c', {4, 3, 2});
input.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {2,2,1}, {3,2,3,2});
auto expected = NDArrayFactory::create<double>('c', {2,2,3,2}, {19, 20, 21, 22, 23, 24, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 13, 14, 15, 16, 17, 18});
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test2) {
auto input = NDArrayFactory::create<double>('c', {4, 3, 2});
input.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {2,2,2}, {3,2,1,2, 0,1,0,1});
auto expected = NDArrayFactory::create<double>('c', {2,2,2}, {23, 24, 11, 12, 3, 4, 3, 4});
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test3) {
auto input = NDArrayFactory::create<double>('c', {4, 3, 2});
input.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {3}, {3,2,1});
auto expected = NDArrayFactory::create<double>(24.);
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test4) {
auto input = NDArrayFactory::create<double>('c', {4, 3, 2});
input.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {2,3}, {3,2,1,0,2,1});
auto expected = NDArrayFactory::create<double>('c',{2}, {24., 6});
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test5) {
auto input = NDArrayFactory::create<double>('c', {4}, {1,2,3,4});
auto indices = NDArrayFactory::create<int>('c', {5,1}, {3,2,0,1,1});
auto expected = NDArrayFactory::create<double>('c',{5}, {4.,3,1,2,2});
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test6) {
auto input = NDArrayFactory::create<double>('c', {4}, {1,2,3,4});
std::vector<Nd4jLong> shape = {1};
auto indices = NDArrayFactory::create<int>('c', shape, {2});
auto expected = NDArrayFactory::create<double>(3.);
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test7) {
auto input = NDArrayFactory::create<double>('c', {4, 4});
input.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {3,3,2}, {0,2,1, 0,1,0, 1,3,1, 0,2,1, 0,1,0, 1,3,1});
auto expected = NDArrayFactory::create<double>('c', {3,3}, {3,5,5,8,5,10,2,2,14});
nd4j::ops::gather_nd op;
auto results = op.execute({&input, &indices}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, gatherNd_test8) {
auto x = NDArrayFactory::create<double>('c', {2, 2}, {1., 2., 3., 4.});
auto y = NDArrayFactory::create<int>('c', {2, 2}, {0, 0, 1, 1});
auto e = NDArrayFactory::create<double>('c', {2}, {1., 4.});
nd4j::ops::gather_nd op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test1) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<int>('c', {4}, {4,4,4,4});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {4, 3, 2, 1, 5, 9, 8, 7, 6, 10, 14, 13, 12, 11, 15, 19, 18, 17, 16, 20, 24, 23, 22, 21, 25, 29, 28, 27, 26, 30, 34, 33, 32, 31, 35, 39, 38, 37, 36, 40, 44, 43, 42, 41, 45, 49, 48, 47, 46, 50, 54, 53, 52, 51, 55, 59, 58, 57, 56, 60});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {2, 1});
ASSERT_EQ(Status::OK(), results->status());
auto output = results->at(0);
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test2) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<Nd4jLong>('c', {4}, {0,1,2,3});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 11, 13, 14, 15, 18, 17, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 32, 31, 33, 34, 35, 38, 37, 36, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52, 51, 53, 54, 55, 58, 57, 56, 59, 60});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {2, 1});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test3) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<int>('c', {3}, {2,3,4});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {2, 1, 3, 4, 5, 7, 6, 8, 9, 10, 12, 11, 13, 14, 15, 17, 16, 18, 19, 20, 23, 22, 21, 24, 25, 28, 27, 26, 29, 30, 33, 32, 31, 34, 35, 38, 37, 36, 39, 40, 44, 43, 42, 41, 45, 49, 48, 47, 46, 50, 54, 53, 52, 51, 55, 59, 58, 57, 56, 60});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {2, 0});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test4) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<int>('c', {5}, {1, 2, 1, 2, 3});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {1, 22, 3, 24, 45, 6, 27, 8, 29, 50, 11, 32, 13, 34, 55, 16, 37, 18, 39, 60, 21, 2, 23, 4, 25, 26, 7, 28, 9, 30, 31, 12, 33, 14, 35, 36, 17, 38, 19, 40, 41, 42, 43, 44, 5, 46, 47, 48, 49, 10, 51, 52, 53, 54, 15, 56, 57, 58, 59, 20});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {0, 2});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test5) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<int>('c', {5}, {1, 2, 4, 2, 3});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {1, 7, 18, 9, 15, 6, 2, 13, 4, 10, 11, 12, 8, 14, 5, 16, 17, 3, 19, 20, 21, 27, 38, 29, 35, 26, 22, 33, 24, 30, 31, 32, 28, 34, 25, 36, 37, 23, 39, 40, 41, 47, 58, 49, 55, 46, 42, 53, 44, 50, 51, 52, 48, 54, 45, 56, 57, 43, 59, 60});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {1, 2});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test6) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto seqLengths = NDArrayFactory::create<int>('c', {4}, {1, 2, 3, 2});
auto exp = NDArrayFactory::create<double>('c', {3, 4, 5}, {1, 2, 3, 4, 5, 26, 27, 28, 29, 30, 51, 52, 53, 54, 55, 36, 37, 38, 39, 40, 21, 22, 23, 24, 25, 6, 7, 8, 9, 10, 31, 32, 33, 34, 35, 16, 17, 18, 19, 20, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 11, 12, 13, 14, 15, 56, 57, 58, 59, 60});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {0, 1});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test7) {
auto input = NDArrayFactory::create<double>('c', {1, 5});
input.linspace(1);
std::vector<int> data = {3};
auto seqLengths = NDArrayFactory::create<int>('c', {1}, data);
auto exp = NDArrayFactory::create<double>('c', {1, 5}, {3, 2, 1, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {1, 0});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test8) {
auto input = NDArrayFactory::create<double>('c', {1, 5});
input.linspace(1);
std::vector<int> data = {1,0,1,0,1};
auto seqLengths = NDArrayFactory::create<int>('c', {5}, data);
auto exp = NDArrayFactory::create<double>('c', {1, 5}, {1, 2, 3, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {0, 1});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test9) {
auto input = NDArrayFactory::create<double>('c', {5, 1});
input.linspace(1);
std::vector<Nd4jLong> data = {1,0,1,0,1};
auto seqLengths = NDArrayFactory::create<Nd4jLong>('c', {5}, data);
auto exp = NDArrayFactory::create<double>('c', {5, 1}, {1, 2, 3, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {1, 0});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test10) {
auto input = NDArrayFactory::create<double>('c', {5, 1});
input.linspace(1);
std::vector<int> data = {3};
auto seqLengths = NDArrayFactory::create<int>('c', {1}, data);
auto exp = NDArrayFactory::create<double>('c', {5, 1}, {3, 2, 1, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {0, 1});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test11) {
auto input = NDArrayFactory::create<double>('c', {1, 1, 5, 1});
input.linspace(1);
std::vector<int> data = {1, 0, 1, 0, 1};
auto seqLengths = NDArrayFactory::create<int>('c', {5}, data);
auto exp = NDArrayFactory::create<double>('c', {1, 1, 5, 1}, {1, 2, 3, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {1, 2});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test12) {
auto input = NDArrayFactory::create<double>('c', {1, 1, 5, 1});
input.linspace(1);
std::vector<int> data = {3};
auto seqLengths = NDArrayFactory::create<int>('c', {1}, data);
auto exp = NDArrayFactory::create<double>('c', {1, 1, 5, 1}, {3, 2, 1, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {2, 0});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test13) {
auto input = NDArrayFactory::create<double>('c', {1, 1, 5, 1});
input.linspace(1);
std::vector<int> data = {1};
auto seqLengths = NDArrayFactory::create<int>('c', {1}, data);
auto exp = NDArrayFactory::create<double>('c', {1, 1, 5, 1}, {1, 2, 3, 4, 5});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &seqLengths}, {}, {3, 0});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, reverse_sequense_test14) {
auto input = NDArrayFactory::create<double>('c', {8, 8, 3, 2}, {0.09753360, 0.76124972, 0.24693797, 0.13813169, 0.33144656, 0.08299957, 0.67197708, 0.80659380, 0.98274191, 0.63566073, 0.21592326, 0.54902743, 0.54555996, 0.23407607, 0.11372584, 0.49965927, 0.15210842, 0.53268608, 0.38700677, 0.68832738, 0.37292716, 0.94616004, 0.77735792, 0.60803430, 0.61523204, 0.64298760, 0.26848351, 0.75015615, 0.28683049, 0.70937606, 0.06478678, 0.68985848, 0.55216783, 0.55382648, 0.34652863, 0.17261296, 0.54193264, 0.05176904, 0.82555761, 0.71106697, 0.04416722, 0.07653656, 0.01034390, 0.99430482, 0.59944390, 0.17973880, 0.36437840, 0.86383673, 0.45025550, 0.97136977, 0.13565978, 0.71567448, 0.92094825, 0.93536442, 0.93630291, 0.67277404, 0.93899264, 0.52422773, 0.44892176, 0.03127759, 0.85910449, 0.18252879, 0.72830945, 0.96736828, 0.89831575, 0.83437150, 0.59050780, 0.36145925, 0.16483070, 0.44021176, 0.76018652, 0.44227383, 0.13052339, 0.18204235, 0.99743733, 0.26885190, 0.87726522, 0.16396056, 0.94943412, 0.40016700, 0.65267938, 0.71073267, 0.40094733, 0.91182634, 0.05391789, 0.49520416, 0.24963864, 0.34847086, 0.74088617, 0.36115701, 0.63074210, 0.97423085, 0.42216846, 0.06326975, 0.07858702, 0.20586622, 0.28752144, 0.38146961, 0.83518735, 0.08207577, 0.82083487, 0.81665728, 0.33309570, 0.67563176, 0.98343578, 0.95919930, 0.66994391, 0.89296165, 0.34755773, 0.63166554, 0.18849320, 0.34828456, 0.98477707, 0.75163124, 0.83306004, 0.14203056, 0.01497920, 0.85727447, 0.71194544, 0.85654019, 0.86160433, 0.79580411, 0.47710411, 0.09318029, 0.31369071, 0.64122249, 0.58399725, 0.26706597, 0.05655339, 0.91025211, 0.30330468, 0.33142930, 0.05668627, 0.02936449, 0.12613087, 0.09960114, 0.16218074, 0.15088139, 0.31239040, 0.55980062, 0.34804391, 0.34941538, 0.61370555, 0.07022964, 0.59757058, 0.31189846, 0.25215345, 0.52546591, 0.55744218, 0.59485650, 0.60553664, 0.07536713, 0.55971796, 0.38764845, 0.20737843, 0.37989120, 0.18361641, 0.48636240, 0.06052657, 0.04241913, 0.66710351, 0.07007925, 0.59371493, 0.74479056, 0.84699625, 0.51210368, 0.12489571, 0.23371067, 0.27274571, 0.83306066, 0.75830824, 0.25963478, 0.87137718, 0.24418835, 0.05032742, 0.52076188, 0.47762345, 0.89829370, 0.34417708, 0.84705151, 0.08203183, 0.10632956, 0.78431292, 0.86441722, 0.36487598, 0.09833603, 0.85863594, 0.11010505, 0.11659283, 0.42500288, 0.02747301, 0.12359903, 0.01753431, 0.41160932, 0.47245979, 0.08268172, 0.21580773, 0.75770279, 0.19736489, 0.44461885, 0.33341706, 0.22519571, 0.31528710, 0.14802902, 0.64171939, 0.52643769, 0.19261234, 0.98032835, 0.15401656, 0.85274458, 0.66408502, 0.23212704, 0.74630026, 0.05713613, 0.49025892, 0.48418810, 0.59541513, 0.09243053, 0.93919152, 0.95357019, 0.52377729, 0.65963871, 0.47934951, 0.49919534, 0.34369898, 0.78211256, 0.13908708, 0.95754117, 0.84107746, 0.09126213, 0.42979124, 0.10295325, 0.34631257, 0.69448345, 0.41720536, 0.15282440, 0.74329854, 0.45775009, 0.12786280, 0.39830299, 0.20386769, 0.59703523, 0.94077086, 0.42255597, 0.80453309, 0.79757204, 0.28653229, 0.60175909, 0.55859623, 0.34318230, 0.63002770, 0.36533324, 0.89689906, 0.73236186, 0.61491989, 0.83787947, 0.67939463, 0.72016694, 0.77499849, 0.72428343, 0.34571059, 0.23143007, 0.20099338, 0.85583142, 0.73174191, 0.54284092, 0.20264181, 0.53037061, 0.30493131, 0.82279766, 0.58542432, 0.72632070, 0.18394258, 0.00608118, 0.23808232, 0.17007573, 0.75245459, 0.84990616, 0.38827634, 0.33809538, 0.01080317, 0.27250145, 0.81769542, 0.15323253, 0.71668395, 0.99427044, 0.11355576, 0.50511923, 0.60248266, 0.36610154, 0.99123140, 0.10519719, 0.18754650, 0.43232584, 0.25247084, 0.47968157, 0.88649124, 0.33588961, 0.92338319, 0.18808573, 0.79433656, 0.12074559, 0.02325163, 0.10117917, 0.83559239, 0.67213900, 0.67265260, 0.11917707, 0.76574855, 0.43842117, 0.28530411, 0.79648090, 0.47939640, 0.73564612, 0.41465671, 0.10995635, 0.20271728, 0.00521771, 0.22952055, 0.78271870, 0.12833592, 0.88639055, 0.76398188, 0.49533508, 0.85447872, 0.15937568, 0.92947480, 0.62705964, 0.85960084, 0.13435660, 0.81845809, 0.60715133, 0.83030708, 0.83071910, 0.38883408, 0.92033237, 0.46066239, 0.48806761, 0.50688779, 0.00654483, 0.32076493, 0.42367646, 0.07381865, 0.22801110, 0.26669388, 0.99691302, 0.12113623, 0.34373057, 0.98977921, 0.96225332, 0.90143562, 0.19559914, 0.08978307, 0.09687492, 0.59820890, 0.75527947, 0.67683355, 0.21847023, 0.29395619, 0.50477953, 0.07112842, 0.54090558, 0.68230725, 0.49713828, 0.41958965, 0.68013847, 0.47691765, 0.63269259, 0.94304095, 0.54587271, 0.72447569, 0.28913523, 0.75766936, 0.52965692, 0.96854824, 0.15589071, 0.84128672, 0.16337522, 0.05771034, 0.21556356, 0.12094140, 0.29721207, 0.00811008, 0.66184926});
auto lengths = NDArrayFactory::create<Nd4jLong>('c', {8}, {7, 2, 3, 5, 2, 1, 6, 4});
auto e = NDArrayFactory::create<double>('c', {8, 8, 3, 2}, {0.54193264, 0.05176904, 0.82555761, 0.71106697, 0.04416722, 0.07653656, 0.06478678, 0.68985848, 0.55216783, 0.55382648, 0.34652863, 0.17261296, 0.61523204, 0.64298760, 0.26848351, 0.75015615, 0.28683049, 0.70937606, 0.38700677, 0.68832738, 0.37292716, 0.94616004, 0.77735792, 0.60803430, 0.54555996, 0.23407607, 0.11372584, 0.49965927, 0.15210842, 0.53268608, 0.67197708, 0.80659380, 0.98274191, 0.63566073, 0.21592326, 0.54902743, 0.09753360, 0.76124972, 0.24693797, 0.13813169, 0.33144656, 0.08299957, 0.01034390, 0.99430482, 0.59944390, 0.17973880, 0.36437840, 0.86383673, 0.93630291, 0.67277404, 0.93899264, 0.52422773, 0.44892176, 0.03127759, 0.45025550, 0.97136977, 0.13565978, 0.71567448, 0.92094825, 0.93536442, 0.85910449, 0.18252879, 0.72830945, 0.96736828, 0.89831575, 0.83437150, 0.59050780, 0.36145925, 0.16483070, 0.44021176, 0.76018652, 0.44227383, 0.13052339, 0.18204235, 0.99743733, 0.26885190, 0.87726522, 0.16396056, 0.94943412, 0.40016700, 0.65267938, 0.71073267, 0.40094733, 0.91182634, 0.05391789, 0.49520416, 0.24963864, 0.34847086, 0.74088617, 0.36115701, 0.63074210, 0.97423085, 0.42216846, 0.06326975, 0.07858702, 0.20586622, 0.34755773, 0.63166554, 0.18849320, 0.34828456, 0.98477707, 0.75163124, 0.33309570, 0.67563176, 0.98343578, 0.95919930, 0.66994391, 0.89296165, 0.28752144, 0.38146961, 0.83518735, 0.08207577, 0.82083487, 0.81665728, 0.83306004, 0.14203056, 0.01497920, 0.85727447, 0.71194544, 0.85654019, 0.86160433, 0.79580411, 0.47710411, 0.09318029, 0.31369071, 0.64122249, 0.58399725, 0.26706597, 0.05655339, 0.91025211, 0.30330468, 0.33142930, 0.05668627, 0.02936449, 0.12613087, 0.09960114, 0.16218074, 0.15088139, 0.31239040, 0.55980062, 0.34804391, 0.34941538, 0.61370555, 0.07022964, 0.27274571, 0.83306066, 0.75830824, 0.25963478, 0.87137718, 0.24418835, 0.59371493, 0.74479056, 0.84699625, 0.51210368, 0.12489571, 0.23371067, 0.18361641, 0.48636240, 0.06052657, 0.04241913, 0.66710351, 0.07007925, 0.60553664, 0.07536713, 0.55971796, 0.38764845, 0.20737843, 0.37989120, 0.59757058, 0.31189846, 0.25215345, 0.52546591, 0.55744218, 0.59485650, 0.05032742, 0.52076188, 0.47762345, 0.89829370, 0.34417708, 0.84705151, 0.08203183, 0.10632956, 0.78431292, 0.86441722, 0.36487598, 0.09833603, 0.85863594, 0.11010505, 0.11659283, 0.42500288, 0.02747301, 0.12359903, 0.19736489, 0.44461885, 0.33341706, 0.22519571, 0.31528710, 0.14802902, 0.01753431, 0.41160932, 0.47245979, 0.08268172, 0.21580773, 0.75770279, 0.64171939, 0.52643769, 0.19261234, 0.98032835, 0.15401656, 0.85274458, 0.66408502, 0.23212704, 0.74630026, 0.05713613, 0.49025892, 0.48418810, 0.59541513, 0.09243053, 0.93919152, 0.95357019, 0.52377729, 0.65963871, 0.47934951, 0.49919534, 0.34369898, 0.78211256, 0.13908708, 0.95754117, 0.84107746, 0.09126213, 0.42979124, 0.10295325, 0.34631257, 0.69448345, 0.41720536, 0.15282440, 0.74329854, 0.45775009, 0.12786280, 0.39830299, 0.20386769, 0.59703523, 0.94077086, 0.42255597, 0.80453309, 0.79757204, 0.28653229, 0.60175909, 0.55859623, 0.34318230, 0.63002770, 0.36533324, 0.89689906, 0.73236186, 0.61491989, 0.83787947, 0.67939463, 0.72016694, 0.77499849, 0.72428343, 0.34571059, 0.23143007, 0.20099338, 0.85583142, 0.73174191, 0.54284092, 0.20264181, 0.53037061, 0.30493131, 0.82279766, 0.58542432, 0.72632070, 0.18394258, 0.00608118, 0.23808232, 0.17007573, 0.75245459, 0.84990616, 0.38827634, 0.33809538, 0.01080317, 0.27250145, 0.81769542, 0.15323253, 0.71668395, 0.99427044, 0.11355576, 0.50511923, 0.22952055, 0.78271870, 0.12833592, 0.88639055, 0.76398188, 0.49533508, 0.47939640, 0.73564612, 0.41465671, 0.10995635, 0.20271728, 0.00521771, 0.67265260, 0.11917707, 0.76574855, 0.43842117, 0.28530411, 0.79648090, 0.79433656, 0.12074559, 0.02325163, 0.10117917, 0.83559239, 0.67213900, 0.25247084, 0.47968157, 0.88649124, 0.33588961, 0.92338319, 0.18808573, 0.60248266, 0.36610154, 0.99123140, 0.10519719, 0.18754650, 0.43232584, 0.85447872, 0.15937568, 0.92947480, 0.62705964, 0.85960084, 0.13435660, 0.81845809, 0.60715133, 0.83030708, 0.83071910, 0.38883408, 0.92033237, 0.59820890, 0.75527947, 0.67683355, 0.21847023, 0.29395619, 0.50477953, 0.98977921, 0.96225332, 0.90143562, 0.19559914, 0.08978307, 0.09687492, 0.07381865, 0.22801110, 0.26669388, 0.99691302, 0.12113623, 0.34373057, 0.46066239, 0.48806761, 0.50688779, 0.00654483, 0.32076493, 0.42367646, 0.07112842, 0.54090558, 0.68230725, 0.49713828, 0.41958965, 0.68013847, 0.47691765, 0.63269259, 0.94304095, 0.54587271, 0.72447569, 0.28913523, 0.75766936, 0.52965692, 0.96854824, 0.15589071, 0.84128672, 0.16337522, 0.05771034, 0.21556356, 0.12094140, 0.29721207, 0.00811008, 0.66184926});
nd4j::ops::reverse_sequence op;
auto results = op.execute({&input, &lengths}, {}, {1, 0});
ASSERT_EQ(Status::OK(), results->status());
auto z = results->at(0);
ASSERT_EQ(e, *z);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_TopK_0) {
auto x = NDArrayFactory::create<double>('c', {2, 6}, {1.0, 1.0, 1.0, 1.0, 11.0, 3.0, 1.0, 1.0, 1.0, 14.0, 5.0, 6.0});
auto expV = NDArrayFactory::create<double>('c', {2, 1}, {11.0, 14.0});
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 1}, {4, 3});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {1, 0}); // without sorting
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
/*
v->printShapeInfo("topK_0: shape v");
expV.printShapeInfo("topK_0: shape expV");
i->printShapeInfo("topK_0: shape I");
expI.printShapeInfo("topK_0: shape expI");
v->printIndexedBuffer("topK_0: v");
expV.printIndexedBuffer("topK_0: expV");
i->printIndexedBuffer("topK_0: i");
expI.printIndexedBuffer("topK_0: expI");
*/
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
// repeat res again
for (int cases = 0; cases < 100; ++cases) {
op.execute({&x}, {v, i}, {}, {1, 0}, {}); // without sorting
}
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_TopK_1) {
auto x = NDArrayFactory::create<double>('c', {2, 3}, {1.0f, 11.0f, 3.0f, 14.0f, 5.0f, 6.0f});
auto expV = NDArrayFactory::create<double>('c', {2, 1}, {11.0f, 14.0f});
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 1}, {1, 0});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {1, 0}); // without sorting
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
// v->printShapeInfo("topK_1: shape v");
// expV.printShapeInfo("topK_1: shape expV");
// i->printShapeInfo("topK_1: shape I");
// expI.printShapeInfo("topK_1: shape expI");
// v->printIndexedBuffer("topK_1: v");
// expV.printIndexedBuffer("topK_1: expV");
// i->printIndexedBuffer("topK_1: i");
// expI.printIndexedBuffer("topK_1: expI");
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
// repeat res again
for (int cases = 0; cases < 100; ++cases) {
op.execute({&x}, {v, i}, {}, {1, 0}, {}); // without sorting
}
delete result;
}
///////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_TopK_2) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0
}
);
// <<<14.>,<9.>>, <<21.>,<9.>>, <<14.>,<16.>>>
auto expV = NDArrayFactory::create<double>('c', {2, 3, 1}, {14.0f, 9.0f,
21.0f,
9.0f, 14.0f,
16.0f
}
);
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 3, 1 }, {2, 1, 0, 1, 2, 0});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
// v->printShapeInfo("shape v");
// expV.printShapeInfo("shape expV");
// i->printShapeInfo("shape I");
// expI.printShapeInfo("shape expI");
// v->printIndexedBuffer("v");
// expV.printIndexedBuffer("expV");
// i->printIndexedBuffer("i");
// expI.printIndexedBuffer("expI");
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_TopK_3) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0
}
);
auto expV = NDArrayFactory::create<double>('c', {2, 3, 2}, {14.0f, 11.0f,
9.0f, 7.0f,
21.0f, 15.0f,
9.0f, 7.0f,
14.0f, 13.0f,
16.0f, 13.5f
}
);
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 3, 2 }, {2, 0, 1, 3, 0, 3, 1, 3, 2, 1, 0, 2});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {2, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
// v->printShapeInfo("shape v");
// expV.printShapeInfo("shape expV");
// i->printShapeInfo("shape I");
// expI.printShapeInfo("shape expI");
// v->printIndexedBuffer("v");
// expV.printIndexedBuffer("expV");
// i->printIndexedBuffer("i");
// expI.printIndexedBuffer("expI");
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_TopK_3_unsorted) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0
}
);
auto expV = NDArrayFactory::create<double>('c', {2, 3, 2}, {11.0f, 14.0f,
9.0f, 7.0f,
21.0f, 15.0f,
9.0f, 7.0f,
13.0f, 14.0f,
16.0f, 13.5f
}
);
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 3, 2 }, {0, 2, 1, 3, 0, 3, 1, 3, 1, 2, 0, 2});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {2}, {false});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_TopK_4) {
auto x = NDArrayFactory::create<double>('c', {2, 3}, {1.0f, 11.0f, 3.0f, 14.0f, 5.0f, 6.0f});
auto expV = NDArrayFactory::create<double>('c', {2, 2}, {11.0f, 3.0f, 14.0f, 6.0f});
auto expI = NDArrayFactory::create<Nd4jLong>('c', {2, 2}, {1, 2, 0, 2});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {2, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_TopK_5) {
auto x = NDArrayFactory::create<double>('f', {2, 3}, {1.1, 5.2, 3.1, 14.2, 11.1, 6.2});
auto expV = NDArrayFactory::create<double>('f', {2, 2}, {11.1, 14.2, 3.1, 6.2});
auto expI = NDArrayFactory::create<Nd4jLong>('f', {2, 2}, {2, 1, 1, 2});
nd4j::ops::top_k op;
auto result = op.execute({&x}, {}, {2, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto i = result->at(1);
ASSERT_TRUE(expV.isSameShape(v));
ASSERT_TRUE(expV.equalsTo(v));
ASSERT_TRUE(expI.isSameShape(i));
ASSERT_TRUE(expI.equalsTo(i));
delete result;
}
///////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, Test_Moments_1) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0}
);
auto y = NDArrayFactory::create<double>('c', {3}, {0, 1, 2});
//auto expV('f', {6}, {1, 0, 0, 0, 0, 0 });
float expMean = 9.395833f;
float expDeviation = 22.4579f;
//Mean 9.395833
//Deviance 22.4579
float inf = 1.e-5f;
nd4j::ops::moments op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto d = result->at(1);
// v->printIndexedBuffer("Result is ");
// d->printIndexedBuffer("Result is ");
ASSERT_TRUE(v->isScalar());
ASSERT_NEAR(expMean, v->e<double>(0), inf);
ASSERT_NEAR(expDeviation, d->e<double>(0), inf);
delete result;
}
TEST_F(DeclarableOpsTests5, Test_Moments_2) {
NDArray x('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0}
);
NDArray expV('c', {4}, {11.833333, 7.6666665, 10.416667, 7.6666665});
NDArray expD('c', {4}, {28.472221, 12.888889, 23.951387, 11.555554});
nd4j::ops::moments op;
auto result = op.execute({&x}, {}, {0, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto d = result->at(1);
ASSERT_TRUE(v->isVector());
ASSERT_TRUE(d->isVector());
ASSERT_TRUE(v->equalsTo(&expV));
ASSERT_TRUE(d->equalsTo(&expD));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_Moments_3) {
auto x = NDArrayFactory::create<double>('c', {2, 3, 4}, {11.0, 3.0, 14.0, 5.0,
6.0, 9.0, 3.5, 7.0,
21.0, 3.0, 14.0, 15.0,
6.0, 9.0, 3.5, 7.0,
11.0, 13.0, 14.0, 5.0,
16.0, 9.0, 13.5, 7.0}
);
auto expV = NDArrayFactory::create<double>('c', {3, 4}, { 8.5f, 6.f , 8.75f, 6.f,
8.5f, 11.f, 8.75f, 6.f,
18.5f, 6.f, 13.75f, 11.f});
auto expD = NDArrayFactory::create<double>('c', {3, 4}, { 6.25f, 9.f, 27.5625f, 1.f,
6.25f, 4.f, 27.5625f, 1.f,
6.25f, 9.f, 0.0625f, 16.f});
nd4j::ops::moments op;
auto result = op.execute({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto d = result->at(1);
ASSERT_TRUE(v->isMatrix());
ASSERT_TRUE(d->isMatrix());
ASSERT_TRUE(v->equalsTo(&expV));
ASSERT_TRUE(d->equalsTo(&expD));
delete result;
}
TEST_F(DeclarableOpsTests5, Test_Moments_4) {
auto x = NDArrayFactory::create<double>('f', {2, 3, 4}, {11.0f, 6.0f, 6.0f, 11.0f, 21.0f, 16.0f, 3.0f, 9.0f, 9.0f, 13.0f, 3.0f, 9.0f,
14.0f, 3.5f, 3.5f, 14.0f, 14.0f, 13.5f, 5.0f, 7.0f, 7.0f, 5.0f, 15.0f, 7.0f});
auto expV = NDArrayFactory::create<double>('c', {3, 4}, { 8.5f, 6.f , 8.75f, 6.f, 8.5f, 11.f, 8.75f, 6.f, 18.5f, 6.f, 13.75f, 11.f});
auto expD = NDArrayFactory::create<double>('c', {3, 4}, { 6.25f, 9.f, 27.5625f, 1.f, 6.25f, 4.f, 27.5625f, 1.f, 6.25f, 9.f, 0.0625f, 16.f});
nd4j::ops::moments op;
auto result = op.execute({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(2, result->size());
auto v = result->at(0);
auto d = result->at(1);
ASSERT_TRUE(v->isMatrix());
ASSERT_TRUE(d->isMatrix());
// v->printIndexedBuffer("v");
// expV.printIndexedBuffer("expV");
// d->printIndexedBuffer("d");
// expD.printIndexedBuffer("expD");
ASSERT_TRUE(v->equalsTo(&expV));
ASSERT_TRUE(d->equalsTo(&expD));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, trace_test1) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5});
input.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {3}, {40, 120, 200});
NDArray matrix('c', {3, 3}, {1., 2., 3., 4., 5., 6., 7., 8., 9.});
nd4j::ops::trace op;
auto results = op.execute({&input}, {}, {});
auto output = results->at(0);
double traceM = matrix.getTrace();
// nd4j_printf("Trace for matrix is %f\n", traceM);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
// exp.printIndexedBuffer("EXP TRACE");
// output->printIndexedBuffer("OUT TRACE");
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, trace_test2) {
auto input = NDArrayFactory::create<double>('c', {4, 5});
input.linspace(1);
auto exp = NDArrayFactory::create<double>(40.);
nd4j::ops::trace op;
auto results = op.execute({&input}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, trace_test3) {
auto input = NDArrayFactory::create<double>('c', {1, 5});
input.linspace(1);
auto exp = NDArrayFactory::create<double>(1.);
nd4j::ops::trace op;
auto results = op.execute({&input}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, trace_test4) {
auto input = NDArrayFactory::create<double>('c', {5, 1});
input.linspace(1);
auto exp = NDArrayFactory::create<double>(1.);
nd4j::ops::trace op;
auto results = op.execute({&input}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, trace_test5) {
auto input = NDArrayFactory::create<double>('c', {3, 4, 5, 6});
input.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {3, 4}, {75, 225, 375, 525, 675, 825, 975, 1125, 1275, 1425, 1575, 1725});
nd4j::ops::trace op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test1) {
auto input = NDArrayFactory::create<double>('c', {2, 2, 2});
input.linspace(1);
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test2) {
auto input = NDArrayFactory::create<double>('c', {1, 3, 2});
input.linspace(1);
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(input.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test3) {
auto input = NDArrayFactory::create<double>('c', {3, 2, 1});
input.linspace(1);
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test04) {
auto input = NDArrayFactory::create<double>('c', {4});
input.linspace(1);
nd4j::ops::random_shuffle op;
//NDArray* output;
auto results = op.execute({&input}, {}, {}, {}, true, nd4j::DataType::DOUBLE);
ASSERT_EQ(Status::OK(), results->status());
auto output = &input; //results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_TRUE(input.isSameShape(output));
//ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test4) {
auto input = NDArrayFactory::create<double>('c', {4});
input.linspace(1);
nd4j::ops::random_shuffle op;
//NDArray* output;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
ASSERT_EQ(Status::OK(), results->status());
auto output = results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_TRUE(input.isSameShape(output));
//ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test5) {
auto input = NDArrayFactory::create<double>('c', {4,1});
input.linspace(1);
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test6) {
auto input = NDArrayFactory::create<double>('c', {4,1,1});
input.linspace(1);
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
bool haveZeros = false;
for(int i = 0; i < output->lengthOf(); ++i)
if(output->e<float>(i) == (float)0.)
haveZeros = true;
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(!input.equalsTo(output));
ASSERT_TRUE(!haveZeros);
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, random_shuffle_test7) {
auto input = NDArrayFactory::create<double>('c', {1,4});
input.linspace(1);
auto exp = NDArrayFactory::create<double>('c', {1,4}, {1, 2, 3, 4});
nd4j::ops::random_shuffle op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(input.isSameShape(output));
ASSERT_TRUE(input.equalsTo(output));
delete results;
}
////////////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, EmbeddingLookup_1) {
auto x = NDArrayFactory::create<double>('c', {3, 4, 2}, {10, 20, 11, 21, 12, 22, 13, 23,
14, 24, 15, 25, 16, 26, 17, 27,
18, 28, 19, 29, 20, 30, 21, 31});
auto y = NDArrayFactory::create<int>({1, 1, 1, 0, 0, 0, 2, 2, 2});
auto exp = NDArrayFactory::create<double>('c', {9, 4, 2}, {14, 24, 15, 25, 16, 26, 17, 27, 14, 24, 15, 25,
16, 26, 17, 27, 14, 24, 15, 25, 16, 26, 17, 27,
10, 20, 11, 21, 12, 22, 13, 23, 10, 20, 11, 21,
12, 22, 13, 23, 10, 20, 11, 21, 12, 22, 13, 23,
18, 28, 19, 29, 20, 30, 21, 31, 18, 28, 19, 29,
20, 30, 21, 31, 18, 28, 19, 29, 20, 30, 21, 31});
// y.printShapeInfo("y shape");
// y.printIndexedBuffer("y buffer");
nd4j::ops::embedding_lookup op;
auto result = op.execute({&x, &y}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto output = result->at(0);
// x.printShapeInfo("Input");
// output->printShapeInfo("Output");
// exp.printShapeInfo("Expected");
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_TRUE(exp.isSameShape(output));
//output->printIndexedBuffer("Output");
//exp.printIndexedBuffer("Expect");
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
TEST_F(DeclarableOpsTests5, EmbeddingLookup_2) {
auto x = NDArrayFactory::create<double>('c', {3, 4, 2}, {10, 20, 30, 40, 50, 60,
70, 80, 90, 10, 11, 12,
13, 14, 15, 16, 17, 18,
19, 20, 21, 22, 23, 24});
//1, 0, 1, 0, 1, 0
auto y = NDArrayFactory::create<Nd4jLong>({1, 0, 1, 0, 1, 0});
auto exp = NDArrayFactory::create<double>('c', {6, 4, 2}, {90, 10, 11, 12, 13, 14,
15, 16, 10, 20, 30, 40,
50, 60, 70, 80, 90, 10,
11, 12, 13, 14, 15, 16,
10, 20, 30, 40, 50, 60,
70, 80, 90, 10, 11, 12,
13, 14, 15, 16, 10, 20,
30, 40, 50, 60, 70, 80});
// y.printShapeInfo("y shape");
// y.printIndexedBuffer("y buffer");
nd4j::ops::embedding_lookup op;
auto result = op.execute({&x, &y}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto output = result->at(0);
// x.printShapeInfo("Input");
// output->printShapeInfo("Output");
// exp.printShapeInfo("Expected");
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_TRUE(exp.isSameShape(output));
// output->printIndexedBuffer("Output");
// exp.printIndexedBuffer("Expect");
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
TEST_F(DeclarableOpsTests5, EmbeddingLookup_3) {
auto y = NDArrayFactory::create<Nd4jLong>('c', {3,2}, {5, 4, 4, 5, 3, 3});
auto exp = NDArrayFactory::create<double>('c', {6, 3, 3}, {
6, 20, 11, 21, 12, 22, 13, 23, 14,
5, 20, 11, 21, 12, 22, 13, 23, 14,
5, 20, 11, 21, 12, 22, 13, 23, 14,
6, 20, 11, 21, 12, 22, 13, 23, 14,
4, 20, 11, 21, 12, 22, 13, 23, 14,
4, 20, 11, 21, 12, 22, 13, 23, 14 });
// y.printShapeInfo("y shape");
// y.printIndexedBuffer("y buffer");
auto p1 = NDArrayFactory::create<double>('c', {3,3}, {1, 20, 11, 21, 12, 22, 13, 23, 14});
auto p2 = NDArrayFactory::create<double>('c', {3,3}, {2, 20, 11, 21, 12, 22, 13, 23, 14});
auto p3 = NDArrayFactory::create<double>('c', {3,3}, {3, 20, 11, 21, 12, 22, 13, 23, 14});
auto p4 = NDArrayFactory::create<double>('c', {3,3}, {4, 20, 11, 21, 12, 22, 13, 23, 14});
auto p5 = NDArrayFactory::create<double>('c', {3,3}, {5, 20, 11, 21, 12, 22, 13, 23, 14});
auto p6 = NDArrayFactory::create<double>('c', {3,3}, {6, 20, 11, 21, 12, 22, 13, 23, 14});
auto p7 = NDArrayFactory::create<double>('c', {3,3}, {7, 20, 11, 21, 12, 22, 13, 23, 14});
auto p8 = NDArrayFactory::create<double>('c', {3,3}, {8, 20, 11, 21, 12, 22, 13, 23, 14});
// res = tf.nn.embedding_lookup((p1, p2, p3, p4, p5, p6, p7), ids, 'mod')
nd4j::ops::embedding_lookup op;
auto result = op.execute({&p1, &p2, &p3, &p4, &p5, &p6, &p7, &p8, &y}, {}, {1}, {}, false, nd4j::DataType::DOUBLE);
auto output = result->at(0);
// x.printShapeInfo("Input");
// output->printIndexedBuffer("Output");
// exp.printShapeInfo("Expected");
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_TRUE(exp.isSameShape(output));
// output->printIndexedBuffer("Output");
// exp.printIndexedBuffer("Expect");
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
/* @Test
public void testDynamicPartition(){
INDArray data = Nd4j.createFromArray(2, 1, 2, 0);
INDArray partitions = Nd4j.createFromArray(0, 2, 1, 0);
INDArray[] out = Nd4j.exec(DynamicCustomOp.builder("dynamic_partition")
.addOutputs(Nd4j.createUninitialized(DataType.INT, 2), Nd4j.createUninitialized(DataType.INT, 1), Nd4j.createUninitialized(DataType.INT, 1))
.addIntegerArguments(3) //3 partitions
.addInputs(data, partitions).build());
INDArray exp0 = Nd4j.createFromArray(2, 0);
INDArray exp1 = Nd4j.createFromArray(2);
INDArray exp2 = Nd4j.createFromArray(1);
assertEquals(exp0, out[0]); //Usually just gives [0,0]
assertEquals(exp1, out[1]);
assertEquals(exp2, out[2]);
}*/
TEST_F(DeclarableOpsTests5, DynamicPartition_01) {
auto x = NDArrayFactory::create<int>({2,1,2,0});
auto y = NDArrayFactory::create<int>({0,2,1,0});
int numPartition = 3;
std::vector<NDArray> exp( { NDArrayFactory::create<int>('c', {2}, {2, 0}),
NDArrayFactory::create<int>('c', {1}, {2}),
NDArrayFactory::create<int>('c', {1}, {1})});
nd4j::ops::dynamic_partition op;
auto result = op.execute({&x, &y}, {}, {numPartition});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(result->size(), numPartition); // result has the same size as given param 4
for (int e = 0; e < result->size(); e++) {
auto output = result->at(e);
// output->printShapeInfo("Output shape> ");
// output->printIndexedBuffer("Output data> ");
ASSERT_TRUE(exp[e].isSameShape(output));
ASSERT_TRUE(exp[e].equalsTo(output));
}
delete result;
}
TEST_F(DeclarableOpsTests5, DynamicPartition_1) {
auto x = NDArrayFactory::create<double>('c', {3, 4, 2}, {10, 20, 11, 21, 12, 22,
13, 23, 14, 24, 15, 25, 16, 26, 17, 27,
18, 28, 19, 29, 20, 30, 21, 31});
auto y = NDArrayFactory::create<int>('c', {3, 4, 2}, {0, 0, 0, 0, 0, 0,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 1, 1, 1, 1, 1, 1, 1
}
);
/* auto y = NDArrayFactory::create<double>('c', {3, 4}, {0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
2.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f, 2.f,
1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f
}
);
*/
int numPartition = 3;
std::vector<NDArray> exp( { NDArrayFactory::create<double>('c', {6}, {10, 20, 11, 21, 12, 22}),
NDArrayFactory::create<double>('c', {8}, {18, 28, 19, 29, 20, 30, 21, 31}),
NDArrayFactory::create<double>('c', {10}, {13, 23, 14, 24, 15, 25, 16, 26, 17, 27})});
nd4j::ops::dynamic_partition op;
auto result = op.execute({&x, &y}, {}, {numPartition});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(result->size(), numPartition); // result has the same size as given param 4
for (int e = 0; e < result->size(); e++) {
auto output = result->at(e);
// output->printShapeInfo("Output shape> ");
// output->printIndexedBuffer("Output data> ");
ASSERT_TRUE(exp[e].isSameShape(output));
ASSERT_TRUE(exp[e].equalsTo(output));
}
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, DynamicPartition_2) {
auto x = NDArrayFactory::create<double>('c', {2, 4}, {0.1f, -1.f, 5.2f, 4.3f, -1.f, 7.4f, 0.0f, -2.2f});
auto y = NDArrayFactory::create<int>('c', {2, 4}, {1, 2, 1, 2, 1, 2, 3, 0});
std::vector<NDArray> exp( {NDArrayFactory::create<double>('c', {1}, {-2.2}),
NDArrayFactory::create<double>('c', {3}, {0.1, 5.2, -1.}),
NDArrayFactory::create<double>('c', {3}, {-1., 4.3, 7.4}),
NDArrayFactory::create<double>('c', {1}, {0.0})});
nd4j::ops::dynamic_partition op;
int numPartition = 4;
auto result = op.execute({&x, &y}, {}, {numPartition});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(result->size(), numPartition); // result has the same size as given param 4
for (int e = 0; e < result->size(); e++) {
auto output = result->at(e);
ASSERT_TRUE(exp[e].isSameShape(output));
ASSERT_TRUE(exp[e].equalsTo(output));
}
delete result;
}
TEST_F(DeclarableOpsTests5, DynamicPartition_3) {
auto x = NDArrayFactory::create<double>('c', {2, 4}, {0.1f, -1.f, 5.2f, 4.3f, -1.f, 7.4f, 0.0f, -2.2f});
auto y = NDArrayFactory::create<Nd4jLong>('c', {2, 4}, {0, 1, 0, 2, 0, 2, 3, 0});
std::vector<NDArray> exp( {NDArrayFactory::create<double>({0.1f, 5.2f, -1.f, -2.2f}),
NDArrayFactory::create<double>('c', {1}, {-1.f}),
NDArrayFactory::create<double>({4.3f, 7.4f}),
NDArrayFactory::create<double>('c', {1}, {0.0f})});
nd4j::ops::dynamic_partition op;
int numPartition = 4;
auto result = op.execute({&x, &y}, {}, {numPartition});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(result->size(), numPartition); // result has the same size as given param 4
for (int e = 0; e < result->size(); e++) {
auto output = result->at(e);
if (output)
{
// output->printShapeInfo("Output shape> ");
// exp[e].printShapeInfo("Expected shape> ");
// output->printIndexedBuffer("Output data> ");
ASSERT_TRUE(exp[e].isSameShape(output));
ASSERT_TRUE(exp[e].equalsTo(output));
}
else
{
ASSERT_TRUE(exp[e].lengthOf() == 0);
}
}
delete result;
}
TEST_F(DeclarableOpsTests5, DynamicStitch_empty_1) {
auto i0 = NDArrayFactory::create<int>('c', {2}, {2, 3});
auto i1 = NDArrayFactory::empty<int>();
auto i2 = NDArrayFactory::create<int>('c', {2}, {0, 1});
auto d0 = NDArrayFactory::create<double>('c', {2, 5}, {0.085571885,0.7937801,0.65908563,0.55552566,0.15962744,0.7787856,0.80119777,0.72437465,0.23089433,0.72714126});
auto d1 = NDArrayFactory::empty<double>();
auto d2 = NDArrayFactory::create<double>('c', {2, 5}, {0.94414854,0.5956861,0.8668989,0.3502196,0.5100082,0.061725974,0.6621324,0.034165382,0.32576954,0.51917326});
nd4j::ops::dynamic_stitch op;
auto result = op.execute({&i0, &i1, &i2, &d0, &d1, &d2}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
delete result;
}
TEST_F(DeclarableOpsTests5, DynamicStitch_empty_2) {
auto i0 = NDArrayFactory::create<int>('c', {2}, {2, 3});
auto i1 = NDArrayFactory::create<int>('c', {0});
auto i2 = NDArrayFactory::create<int>('c', {2}, {0, 1});
auto d0 = NDArrayFactory::create<double>('c', {2, 5}, {0.085571885,0.7937801,0.65908563,0.55552566,0.15962744,0.7787856,0.80119777,0.72437465,0.23089433,0.72714126});
auto d1 = NDArrayFactory::create<double>('c', {0, 5});
auto d2 = NDArrayFactory::create<double>('c', {2, 5}, {0.94414854,0.5956861,0.8668989,0.3502196,0.5100082,0.061725974,0.6621324,0.034165382,0.32576954,0.51917326});
nd4j::ops::dynamic_stitch op;
auto result = op.execute({&i0, &i1, &i2, &d0, &d1, &d2}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, DynamicStitch_1) {
auto x1 = NDArrayFactory::create<int>({1, 3, 5, 0});
auto x2 = NDArrayFactory::create<int>({2, 4});
auto y2 = NDArrayFactory::create<double>({-1., -1.});
auto y1 = NDArrayFactory::create<double>({0.1f, 5.2f, 4.3f, 7.4f});
auto exp = NDArrayFactory::create<double>({7.4f, 0.1f, -1.f, 5.2f, -1.f, 4.3f});
nd4j::ops::dynamic_stitch op;
auto result = op.execute({&x1, &x2, &y1, &y2}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto output = result->at(0);
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, DynamicStitch_2) {
auto x1 = NDArrayFactory::create<int>({1, 3});
auto x2 = NDArrayFactory::create<int>({5, 0, 2, 4});
auto y1 = NDArrayFactory::create<double>({-1.f, -1.f});
auto y2 = NDArrayFactory::create<double>({0.1f, 5.2f, 4.3f, 7.4f});
auto exp = NDArrayFactory::create<double>({5.2f, -1.f, 4.3f, -1.f, 7.4f, 0.1f});
nd4j::ops::dynamic_stitch op;
auto result = op.execute({&x1, &x2, &y1, &y2}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto output = result->at(0);
// output->printShapeInfo("Output shape> ");
// exp.printShapeInfo("Expected shape> ");
// output->printIndexedBuffer("Output data> ");
// exp.printIndexedBuffer("Expected res>");
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, fusedBatchNorm_test1) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 3, 4});
x.linspace(1);
auto scale = NDArrayFactory::create<double>('c', {4});
scale = 0.5;
auto offset = NDArrayFactory::create<double>('c', {4});
offset = 2.;
auto expY = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {1.20337462, 1.20337462, 1.20337462, 1.20337462, 1.34821558, 1.34821558, 1.34821558, 1.34821558, 1.49305654, 1.49305654, 1.49305654, 1.49305654, 1.63789749, 1.63789749, 1.63789749, 1.63789749, 1.78273857, 1.78273857, 1.78273857, 1.78273857, 1.92757952, 1.92757952, 1.92757952, 1.92757952, 2.0724206 , 2.0724206 , 2.0724206 , 2.0724206 , 2.21726155, 2.21726155, 2.21726155, 2.21726155, 2.36210251, 2.36210251, 2.36210251, 2.36210251, 2.50694346, 2.50694346, 2.50694346, 2.50694346, 2.65178442, 2.65178442, 2.65178442, 2.65178442, 2.79662538, 2.79662538, 2.79662538, 2.79662538});
auto expBatchMean = NDArrayFactory::create<double>('c', {4}, {23., 24., 25., 26.});
auto expBatchVar = NDArrayFactory::create<double>('c', {4}, {208.00001526, 208.00001526, 208.00001526, 208.00001526});
nd4j::ops::fused_batch_norm op;
auto results = op.execute({&x, &scale, &offset}, {}, {0,1});
auto y = results->at(0);
auto batchMean = results->at(1);
auto batchVar = results->at(2);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expY.isSameShape(y));
ASSERT_TRUE(expBatchMean.isSameShape(batchMean));
ASSERT_TRUE(expBatchVar.isSameShape(batchVar));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, fusedBatchNorm_test2) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 3, 4});
x.linspace(1);
auto scale = NDArrayFactory::create<double>('c', {4});
scale = 0.5;
auto offset = NDArrayFactory::create<double>('c', {4});
offset = 2.;
auto expY = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {1.20347691, 1.20347691, 1.20347691, 1.20347691, 1.34829926, 1.34829926, 1.34829926, 1.34829926, 1.49312162, 1.49312162, 1.49312162, 1.49312162, 1.6379441 , 1.6379441 , 1.6379441 , 1.6379441 , 1.78276646, 1.78276646, 1.78276646, 1.78276646, 1.92758882, 1.92758882, 1.92758882, 1.92758882, 2.0724113 , 2.0724113 , 2.0724113 , 2.0724113 , 2.21723366, 2.21723366, 2.21723366, 2.21723366, 2.36205602, 2.36205602, 2.36205602, 2.36205602, 2.50687838, 2.50687838, 2.50687838, 2.50687838, 2.65170074, 2.65170074, 2.65170074, 2.65170074, 2.79652309, 2.79652309, 2.79652309, 2.79652309});
auto expBatchMean = NDArrayFactory::create<double>('c', {4}, {23., 24., 25., 26.});
auto expBatchVar = NDArrayFactory::create<double>('c', {4}, {208.00001526, 208.00001526, 208.00001526, 208.00001526});
nd4j::ops::fused_batch_norm op;
auto results = op.execute({&x, &scale, &offset}, {0.05}, {0,1});
auto y = results->at(0);
auto batchMean = results->at(1);
auto batchVar = results->at(2);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expY.isSameShape(y));
ASSERT_TRUE(expBatchMean.isSameShape(batchMean));
ASSERT_TRUE(expBatchVar.isSameShape(batchVar));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, fusedBatchNorm_test3) {
auto x = NDArrayFactory::create<double>('c', {2, 4, 2, 3});
x.linspace(1);
auto scale = NDArrayFactory::create<double>('c', {4});
scale = 0.5;
auto offset = NDArrayFactory::create<double>('c', {4});
offset = 2.;
auto expY = NDArrayFactory::create<double>('c', {2, 4, 2, 3}, {1.20337462, 1.20337462, 1.20337462, 1.20337462, 1.34821558, 1.34821558, 1.34821558, 1.34821558, 1.49305654, 1.49305654, 1.49305654, 1.49305654, 1.63789749, 1.63789749, 1.63789749, 1.63789749, 1.78273857, 1.78273857, 1.78273857, 1.78273857, 1.92757952, 1.92757952, 1.92757952, 1.92757952, 2.0724206 , 2.0724206 , 2.0724206 , 2.0724206 , 2.21726155, 2.21726155, 2.21726155, 2.21726155, 2.36210251, 2.36210251, 2.36210251, 2.36210251, 2.50694346, 2.50694346, 2.50694346, 2.50694346, 2.65178442, 2.65178442, 2.65178442, 2.65178442, 2.79662538, 2.79662538, 2.79662538, 2.79662538});
auto expBatchMean = NDArrayFactory::create<double>('c', {4}, {23., 24., 25., 26.});
auto expBatchVar = NDArrayFactory::create<double>('c', {4}, {208.00001526, 208.00001526, 208.00001526, 208.00001526});
nd4j::ops::fused_batch_norm op;
auto results = op.execute({&x, &scale, &offset}, {}, {1,1});
auto y = results->at(0);
auto batchMean = results->at(1);
auto batchVar = results->at(2);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expY.isSameShape(y));
ASSERT_TRUE(expBatchMean.isSameShape(batchMean));
ASSERT_TRUE(expBatchVar.isSameShape(batchVar));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, fusedBatchNorm_test4) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 3, 4});
x.linspace(1);
std::vector<Nd4jLong> shape = {4};
auto scale = NDArrayFactory::create<double>('c', shape);
auto offset = NDArrayFactory::create<double>('c', shape);
auto mean = NDArrayFactory::create<double>('c', shape);
auto variance = NDArrayFactory::create<double>('c', shape);
scale = 0.5;
offset = 2.;
mean = 25.;
variance = 5.;
auto expY = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {-3.36602688, -3.14244223, -2.91885757, -2.6952734 , -2.47168875, -2.24810457, -2.02451992, -1.80093551, -1.57735109, -1.35376668, -1.13018227, -0.90659785, -0.68301344, -0.45942879, -0.23584437, -0.01225996, 0.21132445, 0.43490887, 0.65849328, 0.88207781, 1.10566223, 1.32924664, 1.55283117, 1.77641559, 2. , 2.22358441, 2.44716883, 2.67075348, 2.89433765, 3.11792231, 3.34150672, 3.56509113, 3.78867555, 4.01225996, 4.23584461, 4.45942879, 4.68301344, 4.90659809, 5.13018227, 5.35376644, 5.57735109, 5.80093575, 6.02451992, 6.24810457, 6.47168875, 6.6952734 , 6.91885757, 7.14244223});
auto expBatchMean = NDArrayFactory::create<double>('c', shape, {0., 0., 0., 0.});
auto expBatchVar = NDArrayFactory::create<double>('c', shape, {0., 0., 0., 0.});
nd4j::ops::fused_batch_norm op;
auto results = op.execute({&x, &scale, &offset}, {}, {0,1});
auto y = results->at(0);
auto batchMean = results->at(1);
auto batchVar = results->at(2);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expY.isSameShape(y));
ASSERT_TRUE(expBatchMean.isSameShape(batchMean));
ASSERT_TRUE(expBatchVar.isSameShape(batchVar));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, fusedBatchNorm_test5) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 3, 4});
x.linspace(1);
std::vector<Nd4jLong> shape = {4};
auto scale = NDArrayFactory::create<double>('c', shape);
auto offset = NDArrayFactory::create<double>('c', shape);
auto mean = NDArrayFactory::create<double>('c', shape);
auto variance = NDArrayFactory::create<double>('c', shape);
scale = 0.5;
offset = 2.;
mean = 25.;
variance = 5.;
auto expY = NDArrayFactory::create<double>('c', {2, 2, 3, 4}, {-3.33992958e+00, -3.11743259e+00, -2.89493513e+00, -2.67243814e+00, -2.44994116e+00, -2.22744417e+00, -2.00494719e+00, -1.78244996e+00, -1.55995297e+00, -1.33745599e+00, -1.11495876e+00, -8.92461777e-01, -6.69964790e-01, -4.47467566e-01, -2.24970579e-01, -2.47359276e-03, 2.20023513e-01, 4.42520618e-01, 6.65017605e-01, 8.87514710e-01, 1.11001182e+00, 1.33250880e+00, 1.55500591e+00, 1.77750289e+00, 2.00000000e+00, 2.22249699e+00, 2.44499421e+00, 2.66749120e+00, 2.88998818e+00, 3.11248541e+00, 3.33498240e+00, 3.55747938e+00, 3.77997637e+00, 4.00247383e+00, 4.22497082e+00, 4.44746780e+00, 4.66996479e+00, 4.89246178e+00, 5.11495876e+00, 5.33745575e+00, 5.55995274e+00, 5.78244972e+00, 6.00494719e+00, 6.22744417e+00, 6.44994116e+00, 6.67243814e+00, 6.89493513e+00, 7.11743259e+00});
auto expBatchMean = NDArrayFactory::create<double>('c', shape, {0., 0., 0., 0.});
auto expBatchVar = NDArrayFactory::create<double>('c', shape, {0., 0., 0., 0.});
nd4j::ops::fused_batch_norm op;
auto results = op.execute({&x, &scale, &offset}, {0.05}, {0,1});
auto y = results->at(0);
auto batchMean = results->at(1);
auto batchVar = results->at(2);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expY.isSameShape(y));
ASSERT_TRUE(expBatchMean.isSameShape(batchMean));
ASSERT_TRUE(expBatchVar.isSameShape(batchVar));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, confusion_matrix_test1) {
auto labels = NDArrayFactory::create<Nd4jLong>('c', {1, 3}, {1, 2, 4});
auto predictions = NDArrayFactory::create<Nd4jLong>('c', {1, 3}, {2, 2, 4});
auto expected = NDArrayFactory::create<Nd4jLong>('c', {5, 5}, {0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1});
nd4j::ops::confusion_matrix op;
auto results = op.execute({&labels, &predictions}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
auto output = results->at(0);
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, confusion_matrix_test2) {
auto labels = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {1, 2});
auto predictions = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {0, 2});
auto expected = NDArrayFactory::create<Nd4jLong>('c', {3, 3}, {0, 0, 0, 1, 0, 0, 0, 0, 1});
nd4j::ops::confusion_matrix op;
auto results = op.execute({&labels, &predictions}, {}, {3});
ASSERT_EQ(Status::OK(), results->status());
auto output = results->at(0);
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, confusion_matrix_test3) {
auto labels = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {1, 2});
auto predictions = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {0, 2});
auto weights = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {100, 200});
auto expected = NDArrayFactory::create<Nd4jLong>('c', {3, 3}, {0, 0, 0, 100, 0, 0, 0, 0, 200});
nd4j::ops::confusion_matrix op;
auto results = op.execute({&labels, &predictions, &weights}, {}, {3});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, confusion_matrix_test4) {
auto labels = NDArrayFactory::create<int>('c', {1, 2}, {1, 2});
auto predictions = NDArrayFactory::create<int>('c', {1, 2}, {0, 2});
auto weights = NDArrayFactory::create<double>('c', {1, 2}, {100, 200});
auto expected = NDArrayFactory::create<double>('c', {3, 3}, {0, 0, 0, 100, 0, 0, 0, 0, 200});
nd4j::ops::confusion_matrix op;
auto results = op.execute({&labels, &predictions, &weights}, {}, {3, nd4j::DataType::DOUBLE});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expected.isSameShape(output));
ASSERT_TRUE(expected.equalsTo(output));
delete results;
}
///////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, ZeroFraction_1) {
auto x = NDArrayFactory::create<double>('c', {3, 4, 2}, {0, 20, 30, 0, 50, 0,
70, 0, 90, 0, 11, 12,
13, 14, 15, 16, 17, 18,
19, 0, 21, 22, 23, 24});
nd4j::ops::zero_fraction op;
auto res = op.execute({&x}, {}, {});
ASSERT_EQ(Status::OK(), res->status());
ASSERT_TRUE(res->at(0)->isScalar());
ASSERT_EQ(res->at(0)->e<double>(0), 0.25);
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, ZeroFraction_2) {
auto x = NDArrayFactory::create<double>('c', {2, 2, 2}, {5.5, 0., 0.3, 5.5, 8.6, 0., 0., 0.4});
nd4j::ops::zero_fraction op;
auto res = op.execute({&x}, {}, {});
ASSERT_EQ(Status::OK(), res->status());
ASSERT_TRUE(res->at(0)->isScalar());
ASSERT_EQ(res->at(0)->e<double>(0), 0.375);
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, ZeroFraction_3) {
auto x = NDArrayFactory::create<double>('f', {2, 2, 2}, {5.5, 0., 0.3, 5.5, 8.6, 0., 0., 0.4});
nd4j::ops::zero_fraction op;
auto res = op.execute({&x}, {}, {});
ASSERT_EQ(Status::OK(), res->status());
ASSERT_TRUE(res->at(0)->isScalar());
ASSERT_EQ(res->at(0)->e<double>(0), 0.375);
delete res;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, XWPlusB_1) {
auto x = NDArrayFactory::create<double>('c', {2,3}, { 1.f, 11.f, 3.f, 14.f, 5.f, 6.f});
auto y = NDArrayFactory::create<double>('c', {3,2}, { 11.f, 3.f, 4.f, 5.f, 6.f, 2.f});
auto b = NDArrayFactory::create<double>({100.f, 200.f});
auto exp = NDArrayFactory::create<double>('c', {2,2}, {173.f, 264.f, 310.f, 279.f});
nd4j::ops::xw_plus_b op;
auto result = op.execute({&x, &y, &b}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto output = result->at(0);
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, StopGradient_1) {
auto x = NDArrayFactory::create<double>('c', {2,3}, { 1.f, 11.f, 3.f, 14.f, 5.f, 6.f});
nd4j::ops::stop_gradient op;
auto result = op.execute({&x}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto output = result->at(0);
// output->printShapeInfo("Output shape> ");
// x.printShapeInfo("Expected shape> ");
// output->printIndexedBuffer("Output data> ");
// x.printIndexedBuffer("Expected res>");
ASSERT_TRUE(x.isSameShape(output));
ASSERT_TRUE(x.equalsTo(output));
delete result;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, StopGradient_2) {
auto x = NDArrayFactory::create<double>('f', {2,3}, { 1.f, 11.f, 3.f, 14.f, 5.f, 6.f});
nd4j::ops::stop_gradient op;
auto result = op.execute({&x}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto output = result->at(0);
// output->printShapeInfo("Output shape> ");
// x.printShapeInfo("Expected shape> ");
// output->printIndexedBuffer("Output data> ");
// x.printIndexedBuffer("Expected res>");
ASSERT_TRUE(x.isSameShape(output));
ASSERT_TRUE(x.equalsTo(output));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test1) {
auto input = NDArrayFactory::create<double>('c', {3, 3, 3}, {-1, 1, -2, 2, -3, 3, -4, 4, -5,5 ,-6,6, -7,7, -8,8, -9,9, -10,10, -11,11, -12,12, -13,13, 14});
auto expOutput = NDArrayFactory::create<double>('c', {3, 3, 3}, {-2.16985e+00,-1.69846e-01,-3.16985e+00, -1.31507e+00,-6.31507e+00,-3.15072e-01, -8.00046e+00,-4.58767e-04,-9.00046e+00, -1.31327e+00,-1.23133e+01,-3.13266e-01, -1.40000e+01,-1.13743e-06,-1.50000e+01, -1.31326e+00,-1.83133e+01,-3.13262e-01, -2.00000e+01,-2.81941e-09,-2.10000e+01, -1.31326e+00,-2.43133e+01,-3.13262e-01, -2.73133e+01,-1.31326e+00,-3.13262e-01});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test2) {
auto input = NDArrayFactory::create<double>('c', {3, 3, 3}, {-1, 1, -2, 2, -3, 3, -4, 4, -5,5 ,-6,6, -7,7, -8,8, -9,9, -10,10, -11,11, -12,12, -13,13, 14});
auto expOutput = NDArrayFactory::create<double>('c', {3, 3, 3}, {-3.05095e+00,-3.04946e+00,-5.00705e+00, -5.09458e-02,-7.04946e+00,-7.04851e-03, -6.05095e+00,-4.94556e-02,-8.00705e+00, -3.04859e+00,-1.30000e+01,-3.04859e+00, -1.50486e+01,-2.37286e-06,-1.70486e+01, -4.85876e-02,-1.60000e+01,-4.85874e-02, -2.10000e+01,-3.04859e+00,-2.51269e+01, -7.96007e-10,-2.50486e+01,-2.12693e+00, -2.40000e+01,-4.85874e-02,-1.26928e-01});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {1}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test3) {
auto input = NDArrayFactory::create<double>('c', {3, 3, 3}, {-1, 1, -2, 2, -3, 3, -4, 4, -5,5 ,-6,6, -7,7, -8,8, -9,9, -10,10, -11,11, -12,12, -13,13, 14});
auto expOutput = NDArrayFactory::create<double>('c', {3, 3, 3}, {-2.16985e+00,-1.69846e-01,-3.16985e+00, -1.31507e+00,-6.31507e+00,-3.15072e-01, -8.00046e+00,-4.58767e-04,-9.00046e+00, -1.31327e+00,-1.23133e+01,-3.13266e-01, -1.40000e+01,-1.13743e-06,-1.50000e+01, -1.31326e+00,-1.83133e+01,-3.13262e-01, -2.00000e+01,-2.81941e-09,-2.10000e+01, -1.31326e+00,-2.43133e+01,-3.13262e-01, -2.73133e+01,-1.31326e+00,-3.13262e-01});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {2}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test5) {
auto input = NDArrayFactory::create<double>('c', {3, 3}, {-1, 1, -2, 2, -3, 3, -4, 4, 5});
auto expOutput = NDArrayFactory::create<double>('c', {3, 3}, {-2.16985, -0.16985, -3.16985, -1.31507, -6.31507, -0.31507, -9.31335, -1.31335, -0.31335});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test6) {
auto input = NDArrayFactory::create<double>('c', {3, 3}, {-1, 1, -2, 2, -3, 3, -4, 4, 5});
auto expOutput = NDArrayFactory::create<double>('c', {3, 3}, {-3.05095,-3.04946,-7.12773, -0.05095,-7.04946,-2.12773, -6.05095,-0.04946,-0.12773});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test7) {
auto input = NDArrayFactory::create<double>('c', {1, 5}, {-1, 1, -2, 2, 3});
auto expOutput = NDArrayFactory::create<double>('c', {1, 5}, {-4.42414, -2.42414, -5.42414, -1.42414, -0.42414});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test8) {
auto input = NDArrayFactory::create<double>('c', {1, 5}, {-1, 1, -2, 2, 3});
auto expOutput = NDArrayFactory::create<double>('c', {1, 5}, {0, 0, 0, 0, 0});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test9) {
auto input = NDArrayFactory::create<double>('c', {5, 1}, {-1, 1, -2, 2, 3});
auto expOutput = NDArrayFactory::create<double>('c', {5, 1}, {0, 0, 0, 0, 0});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test10) {
auto input = NDArrayFactory::create<double>('c', {5, 1}, {-1, 1, -2, 2, 3});
auto expOutput = NDArrayFactory::create<double>('c', {5, 1}, {-4.42414, -2.42414, -5.42414, -1.42414, -0.42414});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test11) {
auto input = NDArrayFactory::create<double>('c', {5}, {-1, 1, -2, 2, 3});
auto expOutput = NDArrayFactory::create<double>('c', {5}, {-4.42414, -2.42414, -5.42414, -1.42414, -0.42414});
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_test12) {
auto input = NDArrayFactory::create<double>('c', {1, 4}, {0.1869, -1.4918, -0.6497, -0.8864});
auto expOutput = NDArrayFactory::create<double>('c', {1, 4}, {-0.6738, -2.3525, -1.5104, -1.7472});
for (int i = 0; i < 10; ++i)
{
nd4j::ops::log_softmax op;
auto results = op.execute({&input}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto z = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(expOutput.isSameShape(z));
ASSERT_TRUE(expOutput.equalsTo(z, 1e-4));
delete results;
}
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_bp_test1) {
auto input = NDArrayFactory::create<double>('c', {2, 2}, {1,2,3,4});
auto epsilon = NDArrayFactory::create<double>('c', {2, 2}, {0.1, 0.2, 0.3, 0.4});
auto exp = NDArrayFactory::create<double>('c', {2, 2}, {-0.07311,0.02689, -0.07311,0.02689});
nd4j::ops::log_softmax_bp op;
auto results = op.execute({&input, &epsilon}, {}, {}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, log_softmax_bp_test2) {
auto input = NDArrayFactory::create<double>('c', {2, 2}, {1,2,3,4});
auto epsilon = NDArrayFactory::create<double>('c', {2, 2}, {0.1, 0.2, 0.3, 0.4});
auto exp = NDArrayFactory::create<double>('c', {2, 2}, {-0.17616, -0.17616, 0.02384, 0.02384});
nd4j::ops::log_softmax_bp op;
auto results = op.execute({&input, &epsilon}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, ELU_1) {
auto input = NDArrayFactory::create<double>('c', {2, 2, 2}, { -1., 2. , 1.5, -1.4, 1., 2., 2., 1.});
auto exp = NDArrayFactory::create<double>('c', {2, 2, 2}, { -0.63212055, 2. , 1.5, -0.753403, 1., 2., 2., 1.});
auto res = NDArrayFactory::create<double>('c', {2, 2, 2});
input.applyScalar(nd4j::scalar::ELU, 1.f, &res);
ASSERT_TRUE(res.equalsTo(&exp));
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, L2_Loss_1) {
auto input = NDArrayFactory::create<double>('c', {2, 2, 2}, { -1., 2. , 1.5, -1.4, 1., 2., 2., 1.});
double exp(9.605);
nd4j::ops::l2_loss op;
auto results = op.execute({&input}, {}, {});
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(output->isScalar());
ASSERT_EQ(output->e<double>(0), exp);
delete results;
}
TEST_F(DeclarableOpsTests5, L2_Loss_2) {
auto x = NDArrayFactory::create<double>(0.7787855863571167);
auto e = NDArrayFactory::create<double>(0.303254);
nd4j::ops::l2_loss op;
auto results = op.execute({&x}, {}, {});
ASSERT_EQ(Status::OK(), results->status());
auto z = results->at(0);
ASSERT_EQ(e, *z);
delete results;
}
TEST_F(DeclarableOpsTests5, L2_Loss_3) {
auto x = NDArrayFactory::create<double>(0.7787855863571167);
auto e = NDArrayFactory::create<double>(0.303254);
auto z = NDArrayFactory::create<double>(0.0);
nd4j::ops::l2_loss op;
auto status = op.execute({&x}, {&z} , {}, {}, {});
ASSERT_EQ(Status::OK(), status);
ASSERT_EQ(e, z);
}
//////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, LogPoissonLoss_1) {
auto weights = NDArrayFactory::create<double>('c', {1, 1}, {1});
auto input = NDArrayFactory::create<double>('c', {2, 2, 2}, { -1., 2. , 1.5, -1.4, 1., 2., 2., 1.});
auto targets = NDArrayFactory::create<double>('c', {2, 2, 2}, {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0});
auto exp = NDArrayFactory::create<double>('c', {2, 2, 2}, {1.3678794, 5.389056, 2.981689, 1.6465969, 1.7182817, 5.389056, 5.389056, 1.7182817});
nd4j::ops::log_poisson_loss op;
auto results = op.execute({&input, &weights, &targets}, {}, {0}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, LogPoissonLoss_2) {
auto weights = NDArrayFactory::create<double>('c', {1, 1}, {1});
auto input = NDArrayFactory::create<double>('c', {2, 2, 2}, { -1., 2. , 1.5, -1.4, 1., 2., 2., 1.});
auto targets = NDArrayFactory::create<double>('c', {2, 2, 2}, {2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0});
auto exp = NDArrayFactory::create<double>('c', {2, 2, 2}, {3.0196857, 4.0408626, 2.1334953, 3.6984034, 1.3700882, 4.0408626, 4.0408626, 1.3700882});
nd4j::ops::log_poisson_loss op;
auto results = op.execute({&input, &weights, &targets}, {}, {0, 1}, {}, false, nd4j::DataType::DOUBLE);
auto output = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
ASSERT_TRUE(exp.isSameShape(output));
ASSERT_TRUE(exp.equalsTo(output));
delete results;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, NormalizeMoments_1) {
auto means = NDArrayFactory::create<double>('c', {2, 3, 4}, { 11., 3., 14., 5.,
6., 9., 3.5, 7.,
21., 3., 14., 15.,
6., 9., 3.5, 7.,
11., 13., 14., 5.,
16., 9., 13.5, 7.});
auto deviance = NDArrayFactory::create<double>('c', {2, 3, 4}, { 21., 13., 24., 15.,
16., 19., 13.5, 17.,
31., 13., 24., 25.,
16., 19., 13.5, 17.,
21., 23., 24., 15.,
26., 19., 23.5, 17.});
auto counts = NDArrayFactory::create<double>(2.0);
auto expMeans = NDArrayFactory::create<double>('c', {2, 3, 4}, {
5.5, 1.5, 7., 2.5,
3., 4.5, 1.75, 3.5,
10.5, 1.5, 7., 7.5,
3., 4.5, 1.75, 3.5,
5.5, 6.5, 7., 2.5,
8., 4.5, 6.75, 3.5});
auto expDeviance = NDArrayFactory::create<double>('c', {2, 3, 4}, {
-19.75, 4.25, -37., 1.25,
-1., -10.75, 3.6875, -3.75,
-94.75, 4.25, -37., -43.75,
-1., -10.75, 3.6875, -3.75,
-19.75, -30.75, -37., 1.25,
-51., -10.75, -33.8125, -3.75});
nd4j::ops::normalize_moments op;
auto results = op.execute({&counts, &means, &deviance}, {0.0}, {});
ASSERT_EQ(Status::OK(), results->status());
ASSERT_EQ(results->size(), 2);
auto outputMeans = results->at(0);
auto outputDeviance = results->at(1);
ASSERT_TRUE(expMeans.isSameShape(outputMeans));
ASSERT_TRUE(expMeans.equalsTo(outputMeans));
ASSERT_TRUE(expMeans.isSameShape(outputDeviance));
ASSERT_TRUE(expDeviance.equalsTo(outputDeviance));
delete results;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, NormalizeMoments_2) {
auto means = NDArrayFactory::create<double>('c', {3, 2, 4}, { 11., 3., 14., 5.,
6., 9., 3.5, 7.,
21., 3., 14., 15.,
6., 9., 3.5, 7.,
11., 13., 14., 5.,
16., 9., 13.5, 7.});
auto deviance = NDArrayFactory::create<double>('c', {3, 2, 4}, { 21., 13., 24., 15.,
16., 19., 13.5, 17.,
31., 13., 24., 25.,
16., 19., 13.5, 17.,
21., 23., 24., 15.,
26., 19., 23.5, 17.});
auto counts = NDArrayFactory::create<double>(12.0);
auto expMeans = NDArrayFactory::create<double>('c', {3, 2, 4}, { 0.9166667, 0.25, 1.1666667, 0.4166667,
0.5, 0.75, 0.2916667, 0.5833334,
1.75, 0.25, 1.1666667, 1.25,
0.5, 0.75, 0.2916667, 0.5833334,
0.9166667, 1.0833334, 1.1666667, 0.4166667,
1.3333334, 0.75, 1.125, 0.5833334});
auto expDeviance = NDArrayFactory::create<double>('c', {3, 2, 4}, {
0.9097222, 1.0208334, 0.6388887, 1.0763888,
1.0833334, 1.0208334, 1.0399306, 1.076389,
-0.4791665, 1.0208334, 0.6388887, 0.5208335,
1.0833334, 1.0208334, 1.0399306, 1.076389,
0.9097222, 0.7430556, 0.6388887, 1.0763888,
0.38888884, 1.0208334, 0.6927084, 1.076389});
nd4j::ops::normalize_moments op;
auto results = op.execute({&counts, &means, &deviance}, {0.0}, {});
ASSERT_EQ(Status::OK(), results->status());
ASSERT_EQ(results->size(), 2);
auto outputMeans = results->at(0);
auto outputDeviance = results->at(1);
ASSERT_TRUE(expMeans.isSameShape(outputMeans));
ASSERT_TRUE(expMeans.equalsTo(outputMeans));
ASSERT_TRUE(expMeans.isSameShape(outputDeviance));
ASSERT_TRUE(expDeviance.equalsTo(outputDeviance));
delete results;
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests5, NormalizeMoments_3) {
auto means = NDArrayFactory::create<double>('c', {3, 2, 4}, { 11., 3., 14., 5.,
6., 9., 3.5, 7.,
21., 3., 14., 15.,
6., 9., 3.5, 7.,
11., 13., 14., 5.,
16., 9., 13.5, 7.});
auto deviance = NDArrayFactory::create<double>('c', {3, 2, 4}, { 21., 13., 24., 15.,
16., 19., 13.5, 17.,
31., 13., 24., 25.,
16., 19., 13.5, 17.,
21., 23., 24., 15.,
26., 19., 23.5, 17.});
auto counts = NDArrayFactory::create<double>(12.0);
double shift = 10.0;
auto expMeans = NDArrayFactory::create<double>('c', {3, 2, 4}, { 10.9166667, 10.25, 11.1666667, 10.4166667,
10.5, 10.75, 10.2916667, 10.5833334,
11.75, 10.25, 11.1666667, 11.25,
10.5, 10.75, 10.2916667, 10.5833334,
10.9166667, 11.0833334, 11.1666667, 10.4166667,
11.3333334, 10.75, 11.125, 10.5833334});
auto expDeviance = NDArrayFactory::create<double>('c', {3, 2, 4}, {
0.9097222, 1.0208334, 0.6388887, 1.0763888,
1.0833334, 1.0208334, 1.0399306, 1.076389,
-0.4791665, 1.0208334, 0.6388887, 0.5208335,
1.0833334, 1.0208334, 1.0399306, 1.076389,
0.9097222, 0.7430556, 0.6388887, 1.0763888,
0.38888884, 1.0208334, 0.6927084, 1.076389});
nd4j::ops::normalize_moments op;
auto results = op.execute({&counts, &means, &deviance}, {shift}, {});
ASSERT_EQ(Status::OK(), results->status());
ASSERT_EQ(results->size(), 2);
auto outputMeans = results->at(0);
auto outputDeviance = results->at(1);
ASSERT_TRUE(expMeans.isSameShape(outputMeans));
ASSERT_TRUE(expMeans.equalsTo(outputMeans));
ASSERT_TRUE(expMeans.isSameShape(outputDeviance));
ASSERT_TRUE(expDeviance.equalsTo(outputDeviance));
delete results;
}
Reference in New Issue View Git Blame Copy Permalink