cavis/libnd4j/tests_cpu/layers_tests/DeclarableOpsTests11.cpp

/*******************************************************************************
 * 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
 ******************************************************************************/


//
// Created by raver on 8/4/2018.
//

#include "testlayers.h"
#include <ops/declarable/CustomOperations.h>
#include <NDArray.h>
#include <ops/ops.h>
#include <GradCheck.h>

using namespace nd4j;


class DeclarableOpsTests11 : public testing::Test {
public:

    DeclarableOpsTests11() {
        printf("\n");
        fflush(stdout);
    }
};


TEST_F(DeclarableOpsTests11, test_listdiff_1) {
    auto x = NDArrayFactory::create<int>('c', {4}, {0, 1, 2, 3});
    auto y = NDArrayFactory::create<int>('c',{2}, {3, 1});

    nd4j::ops::listdiff op;
    auto result = op.execute({&x, &y}, {}, {});
    ASSERT_EQ(Status::OK(), result->status());

    delete result;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test1) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-12.49997,-13.04346, -13.63635, -14.28571,-14.99999,-15.78947, -16.66666, -17.64705,-18.75   ,-20.     , -21.42857, -23.07692,
                                   -24.99999,-27.27272, -29.99999, -33.33332,-37.49999,-42.85713, -49.99998, -59.99998,-74.99995,-99.99992,-149.99986,-299.99911});
    NDArray dLdwExp('c', {2,3,4}, {3.21887,  4.96807,  6.10512,  6.80726,  7.15461,  7.19051,  6.93973,  6.41584,  5.62456,  4.56548,  3.2326 ,  1.61444,
                                   -0.30659, -2.55529, -5.16569, -8.18417,-11.67468,-15.72734,-20.47379,-26.11644,-32.9902 ,-41.71318,-53.64824,-73.05434});
    NDArray dLdlExp('c', {2,3,4}, {1.58903, 1.22117, 0.99621, 0.82911, 0.69315, 0.57634, 0.47223, 0.37689, 0.28768, 0.20273, 0.12058, 0.04002,
                                   -0.04002,-0.12058,-0.20273,-0.28768,-0.37689,-0.47223,-0.57634,-0.69315,-0.82911,-0.99621,-1.22117,-1.58903});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {0}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test2) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,1,4}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {2,1,4}, {15.99805, 16.72406, 16.27746,  14.83754,-44.97147,-59.99582,-79.28771,-107.35497});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test3) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-12.49997,-13.04346, -13.63635, -14.28571,-14.99999,-15.78947, -16.66666, -17.64705,-18.75   ,-20.     , -21.42857, -23.07692,
                                   -24.99999,-27.27272, -29.99999, -33.33332,-37.49999,-42.85713, -49.99998, -59.99998,-74.99995,-99.99992,-149.99986,-299.99911});
    NDArray dLdwExp('c', {}, {-227.77286});
    NDArray dLdlExp('c', {2,3,4}, {1.58903, 1.22117, 0.99621, 0.82911, 0.69315, 0.57634, 0.47223, 0.37689, 0.28768, 0.20273, 0.12058, 0.04002,
                                   -0.04002,-0.12058,-0.20273,-0.28768,-0.37689,-0.47223,-0.57634,-0.69315,-0.82911,-0.99621,-1.22117,-1.58903});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test4) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {4.8876 , -46.29156, -186.36887});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);
    // dLdw->printIndexedBuffer();
    // dLdw->printShapeInfo();

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test5) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-1.04166,-1.08696, -1.13636, -1.19048,-1.25   ,-1.31579, -1.38889, -1.47059,-1.5625 ,-1.66667, -1.78571, -1.92308,
                                   -2.08333,-2.27273, -2.5    , -2.77778,-3.125  ,-3.57143, -4.16667, -5.     ,-6.25   ,-8.33333,-12.49999,-24.99993});
    NDArray dLdwExp('c', {2,3,4}, {1.05912, 1.20488, 1.29964, 1.35815, 1.3871 , 1.39009, 1.36919, 1.32553, 1.25959, 1.17133, 1.06026, 0.92541,
                                   0.76533, 0.57794, 0.3604 , 0.10886,-0.18201,-0.51973,-0.91527,-1.38549,-1.95831,-2.68522,-3.67981,-5.29698});
    NDArray dLdlExp('c', {2,3,4}, {0.13242, 0.10176, 0.08302, 0.06909, 0.05776, 0.04803, 0.03935, 0.03141, 0.02397, 0.01689, 0.01005, 0.00334,
                                   -0.00334,-0.01005,-0.01689,-0.02397,-0.03141,-0.03935,-0.04803,-0.05776,-0.06909,-0.08302,-0.10176,-0.13242});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test6) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {6.73432, 2.46939,-9.20372});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test7) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {}, {0.});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test8) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0.     , 0.     ,  0.     ,  0.     ,-1.5    ,-1.57895, -1.66667, -1.76471,-1.875  ,-2.     , -2.14286, -2.30769,
                                  -2.5    ,-2.72727, -3.     , -3.33333,-3.75   ,-4.28571, -5.     , -6.     ,-7.49999,-9.99999,-14.99999,-29.99991});
    NDArray dLdwExp('c', {2,3,4}, {1.56625, 1.74117, 1.85487, 1.92509, 1.95982, 1.96341, 1.93833, 1.88594, 1.80682, 1.70091, 1.56762, 1.4058 ,
                                   1.2137 , 0.98883, 0.72779, 0.42594, 0.07689,-0.32837,-0.80302,-1.36728,-2.05466,-2.92696,-4.12046,-6.06107});
    NDArray dLdlExp('c', {2,3,4}, {0.     , 0.     , 0.     , 0.     , 0.06931, 0.05763, 0.04722, 0.03769, 0.02877, 0.02027, 0.01206, 0.004,
                                  -0.004  ,-0.01206,-0.02027,-0.02877,-0.03769,-0.04722,-0.05763,-0.06931,-0.08291,-0.09962,-0.12212,-0.1589});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.p(0, 0.);
    weights.p(1, 0.);
    weights.p(2, 0.);
    weights.p(3, 0.);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test9) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.52083,-0.54348,-0.56818, -0.59524,-0.625  ,-0.65789,-0.69444, -0.73529,-0.78125,-0.83333,-0.89286, -0.96154,
                                   -1.04167,-1.13636,-1.25   , -1.38889,-1.5625 ,-1.78571,-2.08333, -2.5    ,-3.125  ,-4.16666,-6.24999,-12.49996});
    NDArray dLdwExp('c', {2,3,4}, {0.13412, 0.207  , 0.25438, 0.28364, 0.29811, 0.2996 , 0.28916, 0.26733, 0.23436, 0.19023, 0.13469, 0.06727,
                                  -0.01277,-0.10647,-0.21524,-0.34101,-0.48645,-0.65531,-0.85307,-1.08819,-1.37459,-1.73805,-2.23534,-3.04393});
    NDArray dLdlExp('c', {2,3,4}, {0.06621, 0.05088, 0.04151, 0.03455, 0.02888, 0.02401, 0.01968, 0.0157 , 0.01199, 0.00845, 0.00502, 0.00167,
                                  -0.00167,-0.00502,-0.00845,-0.01199,-0.0157 ,-0.01968,-0.02401,-0.02888,-0.03455,-0.04151,-0.05088,-0.06621});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test10) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,1}, {-9.49054});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test11) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {0.20365,-1.92882,-7.76537});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test12) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, { 0.      , 0.      , 0.      ,  0.      ,-0.75    ,-0.789473,-0.833333, -0.882353,-0.9375  ,-1.      ,-1.071428, -1.153846,
                                -1.25    ,-1.363636,-1.5     , -1.666666,-1.875   ,-2.142857,-2.499999, -2.999999,-3.749997,-4.999997,-7.499993,-14.999956});
    NDArray dLdwExp('c', {2,3,4}, {0.16094, 0.2484 , 0.30526, 0.34036, 0.35773, 0.35953, 0.34699, 0.32079, 0.28123, 0.22827, 0.16163, 0.08072,
                                   -0.01533,-0.12776,-0.25828,-0.40921,-0.58373,-0.78637,-1.02369,-1.30582,-1.64951,-2.08566,-2.68241,-3.65272});
    NDArray dLdlExp('c', {2,3,4}, {0.     , 0.     , 0.     , 0.     , 0.03466, 0.02882, 0.02361, 0.01884, 0.01438, 0.01014, 0.00603, 0.002  ,
                                  -0.002  ,-0.00603,-0.01014,-0.01438,-0.01884,-0.02361,-0.02882,-0.03466,-0.04146,-0.04981,-0.06106,-0.07945});


    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;
    weights.t<double>(3) = 0.;


    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, log_loss_grad_test13) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0.     , 0.     ,  0.     ,  0.     , 0.     , 0.     ,  0.     ,  0.     , 0.     , 0.     ,  0.     ,  0.     ,
                                  -2.08333,-2.27273, -2.5    , -2.77778,-3.125  ,-3.57143, -4.16667, -5.     ,-6.25   ,-8.33333,-12.49999,-24.99993});
    NDArray dLdwExp('c', {2,3,1}, {1.75828,  2.30839,  1.25309, -1.35098, -6.16602,-16.78383});
    NDArray dLdlExp('c', {2,3,4}, {0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     ,
                                   -0.00334,-0.01005,-0.01689,-0.02397,-0.03141,-0.03935,-0.04803,-0.05776,-0.06909,-0.08302,-0.10176,-0.13242});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;

    nd4j::ops::log_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {1e-7}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test1) {

    NDArray input    = NDArrayFactory::create<double>('c', {1, 7, 7, 1}, {
             1, 2.1, 3.15, 4.2, 5.15,  6.1,   7,
             8, 9.1,  10.,  11, 12.9, 13.1,  14,
            15, 16.,  17.,  18,   19,  20.,  21,
            22, 23.,  24.,  25,   26,   27,  28,
            30,  31,   32,  33,  34.,   35,  36,
            37,  38,   39,  40,  41.,   42,  43,
            44,  45,   46,  47,  48.,   49,  50
    });
    NDArray expected = NDArrayFactory::create<double>('c', {1, 30, 30, 1}, {
        1.         ,1.1976162  ,1.4174359  ,1.6775769  ,1.9961575  ,2.3283265 ,
        2.550918   ,2.7360606  ,2.9655411  ,3.2929654  ,3.5441515  ,3.7380352 ,
        3.948995   ,4.248106   ,4.5073795  ,4.6843743  ,4.8572845  ,5.104302  ,
        5.3869915  ,5.581401   ,5.7539616  ,5.974285   ,6.272836   ,6.5204263 ,
        6.718899   ,6.8871036  ,7.039068   ,7.099216   ,7.0784245  ,7.0281887 ,
        2.247592   ,2.446947   ,2.6694887  ,2.9312382  ,3.248216   ,3.5745337 ,
        3.78931    ,3.9656973  ,4.186417   ,4.5046535  ,4.740569   ,4.9217057 ,
        5.133866   ,5.459533   ,5.7744613  ,6.0197873  ,6.254011   ,6.535633  ,
        6.8097296  ,6.9607787  ,7.0749416  ,7.241601   ,7.5094895  ,7.7499495 ,
        7.954571   ,8.131972   ,8.286526   ,8.346463   ,8.325745   ,8.275683  ,
        3.6286845  ,3.830573   ,4.0569587  ,4.3211575  ,4.6364856  ,4.9556503 ,
        5.160583   ,5.3258467  ,5.535462   ,5.84216    ,6.058749   ,6.223753  ,
        6.437597   ,6.797369   ,7.1836042  ,7.5164022  ,7.8290343  ,8.154773  ,
        8.417635   ,8.512958   ,8.5521     ,8.649708   ,8.87788    ,9.108794  ,
        9.320926   ,9.509781   ,9.667375   ,9.72694    ,9.706349   ,9.656599  ,
        5.276778   ,5.480438   ,5.709702   ,5.9754477  ,6.288551   ,6.6005697 ,
        6.796207   ,6.9511423  ,7.1503997  ,7.4461427  ,7.644651   ,7.794562  ,
        8.009684   ,8.400473   ,8.851847   ,9.26469    ,9.649218,  10.015648  ,
        10.268647  ,10.313368  ,10.2843275 ,10.319379  ,10.512033  ,10.734956 ,
        10.954604  ,11.154507  ,11.315369  ,11.374779  ,11.354242  ,11.304622 ,
        7.325373   ,7.5284843  ,7.757575   ,8.022221   ,8.331997   ,8.638187  ,
        8.827649   ,8.976217   ,9.168955   ,9.45726    ,9.6442375  ,9.784517  ,
        9.999621,  10.407702  ,10.896234,  11.355122,  11.781423,  12.172186  ,
        12.420712  ,12.4374485 ,12.370511  ,12.371386  ,12.545973  ,12.766424 ,
        12.992249  ,13.20012   ,13.364252  ,13.424109  ,13.40342   ,13.353425 ,
        9.493208   ,9.692467   ,9.9169445,  10.176801,  10.482199,  10.78547   ,
        10.974367  ,11.123442  ,11.31637   ,11.603645  ,11.790616  ,11.930889 ,
        12.144082  ,12.546447  ,13.024898  ,13.4723    ,13.889232  ,14.276275 ,
        14.528972  ,14.555555  ,14.50145   ,14.515459  ,14.700572  ,14.927055 ,
        15.156046  ,15.366046  ,15.532901  ,15.594008  ,15.5728855 ,15.521847 ,
        10.970133  ,11.163599  ,11.380694  ,11.633735  ,11.935032  ,12.238887 ,
        12.43254   ,12.588294  ,12.787534  ,13.079956  ,13.27752   ,13.426631 ,
        13.636713  ,14.013844  ,14.441672  ,14.827978  ,15.191209  ,15.549808 ,
        15.81343   ,15.881828  ,15.883522  ,15.950411  ,16.16933   ,16.40794  ,
        16.636436  ,16.842583  ,17.010887  ,17.07363   ,17.05194   ,16.999537 ,
        12.219155  ,12.406129  ,12.614796  ,12.860335  ,13.157928  ,13.464224 ,
        13.665207  ,13.830567  ,14.039036  ,14.339629  ,14.552863  ,14.715049 ,
        14.921564  ,15.264454  ,15.622843  ,15.924977  ,16.213829  ,16.532364 ,
        16.8099    ,16.934835  ,17.012146  ,17.150164  ,17.413412  ,17.666712 ,
        17.892765  ,18.09207   ,18.261044  ,18.325531  ,18.303238  ,18.249378 ,
        13.7663965 ,13.947391  ,14.148263  ,14.386917  ,14.681246  ,14.990087 ,
        15.198166  ,15.372728  ,15.590062  ,15.898583  ,16.126892  ,16.301655 ,
        16.50487   ,16.815214  ,17.107498  ,17.329458  ,17.547403  ,17.827654 ,
        18.118288  ,18.296928  ,18.4461    ,18.651634  ,18.956806  ,19.22382  ,
        19.447308  ,19.639887  ,19.809319  ,19.875397  ,19.852556  ,19.797365 ,
        15.9419365 ,16.118704  ,16.314133  ,16.547867  ,16.839561  ,17.14954  ,
        17.361883  ,17.542162  ,17.764957  ,18.078188  ,18.315733  ,18.498205 ,
        18.699116  ,18.988684  ,19.238989  ,19.410137  ,19.583265  ,19.839512 ,
        20.13878   ,20.35177   ,20.546844  ,20.795671  ,21.128067  ,21.404358 ,
        21.626736  ,21.8155    ,21.98561   ,22.052843  ,22.029604  ,21.973448 ,
        17.53522   ,17.71077   ,17.904636  ,18.13695   ,18.42784   ,18.738056 ,
        18.951529  ,19.133352  ,19.357613  ,19.672083  ,19.912102  ,20.096638 ,
        20.296894  ,20.580765  ,20.819603  ,20.976887  ,21.137802  ,21.387535 ,
        21.689209  ,21.911621  ,22.119276  ,22.37999   ,22.71991   ,22.998823 ,
        23.22097   ,23.40876   ,23.57911   ,23.646685  ,23.623325  ,23.566887 ,
        18.746353  ,18.922657  ,19.117487  ,19.350685  ,19.64207   ,19.952137 ,
        20.164913  ,20.345781  ,20.569134  ,20.88284   ,21.12133   ,21.30459  ,
        21.505253  ,21.792645  ,22.038572  ,22.204426  ,22.37289   ,22.626648 ,
        22.926834  ,23.143423  ,23.343302  ,23.596668  ,23.931936  ,24.209232 ,
        24.431519  ,24.619913  ,24.79011   ,24.857473  ,24.83419   ,24.777927 ,
        20.16656   ,20.344206  ,20.540766  ,20.775532  ,21.067804  ,21.377607 ,
        21.589132  ,21.768297  ,21.99003   ,22.302366  ,22.538124  ,22.719105 ,
        22.920494  ,23.214176  ,23.472767  ,23.653934  ,23.83589   ,24.096842 ,
        24.394371  ,24.600555  ,24.786541  ,25.026773  ,25.353731  ,25.62813  ,
        25.850672  ,26.04014   ,26.210072  ,26.277063  ,26.253906  ,26.197956 ,
        22.363024  ,22.54125   ,22.738552  ,22.973991  ,23.266647  ,23.57634  ,
        23.787327  ,23.96576   ,24.186796  ,24.498543  ,24.733124  ,24.913122 ,
        25.114826  ,25.411213  ,25.675262  ,25.863028  ,26.050789  ,26.314838 ,
        26.611223  ,26.812925  ,26.992926  ,27.227505  ,27.550882  ,27.824034 ,
        28.046684  ,28.236614  ,28.406433  ,28.473265  ,28.450163  ,28.394344 ,
        24.429443  ,24.60767   ,24.80497   ,25.04041   ,25.333065  ,25.642756 ,
        25.853743  ,26.032173  ,26.25321   ,26.564959  ,26.79954   ,26.97954  ,
        27.181242  ,27.47763   ,27.74168   ,27.929441  ,28.117207  ,28.381254 ,
        28.677637  ,28.879343  ,29.059345  ,29.293922  ,29.617298  ,29.890451 ,
        30.113104  ,30.303034  ,30.472853  ,30.539684  ,30.516582  ,30.460762 ,
        26.        ,26.178228  ,26.375526  ,26.61097   ,26.903624  ,27.213314 ,
        27.424305  ,27.602734  ,27.823772  ,28.135519  ,28.3701    ,28.550098 ,
        28.7518    ,29.04819   ,29.312237  ,29.5       ,29.687763  ,29.951813 ,
        30.2482    ,30.449903  ,30.629902  ,30.864483  ,31.187859  ,31.461012 ,
        31.683659  ,31.873592  ,32.043407  ,32.11024   ,32.087135  ,32.03132  ,
        27.570559  ,27.748787  ,27.946087  ,28.181528  ,28.474184  ,28.783876 ,
        28.994865  ,29.173294  ,29.39433   ,29.70608   ,29.940659  ,30.120655 ,
        30.32236   ,30.618746  ,30.882797  ,31.070557  ,31.25832   ,31.522371 ,
        31.818754  ,32.02046   ,32.20046   ,32.43504   ,32.758415  ,33.031567 ,
        33.25422   ,33.44415   ,33.613964  ,33.680794  ,33.657696  ,33.60188  ,
        29.636976  ,29.815207  ,30.0125    ,30.247944  ,30.5406    ,30.85029  ,
        31.061283  ,31.239712  ,31.46075   ,31.7725    ,32.00708   ,32.187077 ,
        32.38878   ,32.685165  ,32.949215  ,33.13698   ,33.32474   ,33.58879  ,
        33.885178  ,34.086884  ,34.26688   ,34.501457  ,34.824837  ,35.09799  ,
        35.320637  ,35.510574  ,35.68039   ,35.747215  ,35.724117  ,35.6683   ,
        31.83344   ,32.011665  ,32.20897   ,32.444412  ,32.73707   ,33.046757 ,
        33.257744  ,33.436176  ,33.657207  ,33.96896   ,34.203537  ,34.383537 ,
        34.58524   ,34.88163   ,35.145676  ,35.33344   ,35.521206  ,35.785255 ,
        36.081642  ,36.28334   ,36.46334   ,36.69792   ,37.021297  ,37.294453 ,
        37.517097  ,37.707027  ,37.876846  ,37.94368   ,37.920578  ,37.864758 ,
        33.253647  ,33.431873  ,33.62917   ,33.864613  ,34.15727   ,34.466957 ,
        34.677948  ,34.856377  ,35.077415  ,35.38916   ,35.623745  ,35.803745 ,
        36.005447  ,36.301834  ,36.565884  ,36.753647  ,36.941406  ,37.205456 ,
        37.50184   ,37.703545  ,37.883545  ,38.118122  ,38.4415    ,38.714653 ,
        38.9373    ,39.127235  ,39.297054  ,39.363884  ,39.340782  ,39.28496  ,
        34.464783  ,34.64301   ,34.840305  ,35.075752  ,35.368404  ,35.6781   ,
        35.889088  ,36.067516  ,36.28855   ,36.6003    ,36.834885  ,37.014877 ,
        37.216583  ,37.51297   ,37.77702   ,37.964783  ,38.152546  ,38.416595 ,
        38.71298   ,38.914684  ,39.094685  ,39.32926   ,39.652645  ,39.925793 ,
        40.14844   ,40.338375  ,40.508194  ,40.575024  ,40.55192   ,40.496105 ,
        36.058067  ,36.23629   ,36.43359   ,36.669033  ,36.961685  ,37.271378 ,
        37.48237   ,37.6608    ,37.881836  ,38.19359   ,38.42817   ,38.608162 ,
        38.809868  ,39.10625   ,39.3703    ,39.558064  ,39.74583   ,40.00988  ,
        40.306267  ,40.50797   ,40.68797   ,40.92255   ,41.245926  ,41.519077 ,
        41.741722  ,41.931652  ,42.101475  ,42.168304  ,42.145203  ,42.089386 ,
        38.315002  ,38.493233  ,38.690533  ,38.925976  ,39.218628  ,39.52832  ,
        39.739307  ,39.917736  ,40.138775  ,40.45052   ,40.685104  ,40.865097 ,
        41.066803  ,41.36319   ,41.627243  ,41.815002  ,42.002766  ,42.26682  ,
        42.5632    ,42.764908  ,42.944904  ,43.179485  ,43.50286   ,43.776016 ,
        43.998665  ,44.188595  ,44.358418  ,44.425247  ,44.402145  ,44.34633  ,
        40.22708   ,40.40531   ,40.602608  ,40.83805   ,41.130707  ,41.440395 ,
        41.651382  ,41.82982   ,42.050854  ,42.3626    ,42.597183  ,42.77718  ,
        42.97888   ,43.27527   ,43.53932   ,43.72708   ,43.914845  ,44.178894 ,
        44.47528   ,44.676983  ,44.856983  ,45.09156   ,45.41494   ,45.68809  ,
        45.91074   ,46.100674  ,46.270493  ,46.337322  ,46.31422   ,46.2584   ,
        41.785618  ,41.963844  ,42.161144  ,42.396584  ,42.68924   ,42.998936 ,
        43.209923  ,43.388355  ,43.609394  ,43.921143  ,44.15572   ,44.335716 ,
        44.53742   ,44.833805  ,45.09786   ,45.285614  ,45.473377  ,45.737427 ,
        46.033817  ,46.235523  ,46.415524  ,46.650105  ,46.973476  ,47.24663  ,
        47.469276  ,47.65921   ,47.82903   ,47.895855  ,47.872753  ,47.81694  ,
        43.11514   ,43.293365  ,43.490665  ,43.726105  ,44.018764  ,44.328457 ,
        44.539444  ,44.717873  ,44.93891   ,45.25066   ,45.48524   ,45.665237 ,
        45.86694   ,46.163326  ,46.427376  ,46.615143  ,46.802902  ,47.066956 ,
        47.363342  ,47.56505   ,47.74505   ,47.979626  ,48.302998  ,48.576153 ,
        48.798798  ,48.98873   ,49.158546  ,49.225376  ,49.202282  ,49.146458 ,
        44.303867  ,44.482094  ,44.679394  ,44.914833  ,45.207493  ,45.51718  ,
        45.72817   ,45.9066    ,46.12764   ,46.439384  ,46.673965  ,46.853966 ,
        47.055668  ,47.352055  ,47.6161    ,47.803867  ,47.99163   ,48.25568  ,
        48.552063  ,48.75377   ,48.933773  ,49.16835   ,49.491726  ,49.764877 ,
        49.987526  ,50.17746   ,50.347275  ,50.4141    ,50.391006  ,50.335186 ,
        44.771675  ,44.949905  ,45.1472    ,45.382645  ,45.6753    ,45.98499  ,
        46.195976  ,46.374413  ,46.595448  ,46.907196  ,47.141773  ,47.321774 ,
        47.523476  ,47.819862  ,48.08391   ,48.27168   ,48.459446  ,48.72349  ,
        49.019882  ,49.22158   ,49.401585  ,49.63616   ,49.959538  ,50.232693 ,
        50.455338  ,50.64527   ,50.81509   ,50.88192   ,50.858818  ,50.803    ,
        44.609966  ,44.788193  ,44.985493  ,45.220936  ,45.51359   ,45.82328  ,
        46.03427   ,46.2127    ,46.433743  ,46.74549   ,46.98007   ,47.160065 ,
        47.36177   ,47.658157  ,47.922207  ,48.10997   ,48.297733  ,48.561783 ,
        48.858166  ,49.059875  ,49.239872  ,49.47445   ,49.79783   ,50.07098  ,
        50.293625  ,50.48356   ,50.653378  ,50.720203  ,50.6971    ,50.64128  ,
        44.219246  ,44.397472  ,44.594772  ,44.83021   ,45.122868  ,45.43256  ,
        45.643543  ,45.82198   ,46.04302   ,46.354763  ,46.589344  ,46.76934  ,
        46.971046  ,47.267433  ,47.531483  ,47.719242  ,47.907005  ,48.17105  ,
        48.467438  ,48.66914   ,48.849144  ,49.08372   ,49.4071    ,49.680256 ,
        49.902905  ,50.092834  ,50.262653  ,50.329483  ,50.30638   ,50.25057});

    auto size = NDArrayFactory::create<int>({30, 30});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());
    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 30x30");
//    expected.printBuffer("Expect for 30x30");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}
TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test2) {

    NDArray input    = NDArrayFactory::create<double>('c', {2, 5, 4, 3});
    NDArray expected = NDArrayFactory::create<double>('c', {2, 10, 8, 3}, {
            1.        ,  2.       ,3.       ,2.21875,   3.21875,   4.21875,   4. ,     5.        , 6.        ,5.5,
            6.5,       7.5,       7.,        8.,        9.        ,8.78125,   9.78125, 10.78125,  10.,       11. ,
            12.,  10.28125  ,     11.28125  ,12.28125,  5.875,     6.875,     7.875,    7.09375,   8.09375   ,9.09375,
            8.875,     9.875,    10.875,    10.375,    11.375,      12.375    ,11.875    ,12.875 ,   13.875, 13.65625,
            14.65625,  15.65625, 14.875    ,15.875    ,16.875 ,   15.15625,  16.15625,  17.15625,  13.,      14.,
            15.       ,14.21875,  15.21875,  16.21875,  16.,       17.,     18.       ,17.5      ,18.5 ,     19.5,
            19.,       20.,       21.,       20.78125  ,21.78125  ,22.78125,  22.,       23. ,      24. ,    22.28125,
            23.28125  ,24.28125  ,19. ,      20.,       21.,       20.21875,  21.21875,  22.21875  ,22.       ,23.,
            24. ,      23.5,      24.5,      25.5,      25.       ,26.       ,27.,       26.78125 , 27.78125,  28.78125,
            28.,       29.       ,30.       ,28.28125,  29.28125,  30.28125,  25.,       26.,       27.       ,26.21875,
            27.21875,  28.21875,  28.,       29.,       30.,       29.5      ,30.5      ,31.5 ,     31.,       32.,
            33.,       32.78125,  33.78125  ,34.78125  ,34.,       35.,      36.,       34.28125,  35.28125,   36.28125,
            31.       ,32.,       33. ,      32.21875,  33.21875,  34.21875, 34.       ,35.       ,36.,       35.5,
            36.5 ,     37.5 ,     37.,       38.       ,39.       ,38.78125,  39.78125,  40.78125,  40.,       41.,
            42.       ,40.28125  ,41.28125,  42.28125,  37. ,      38.,       39.,       38.21875  ,39.21875  ,40.21875,
            40. ,      41.  ,     42.   ,    41.5,      42.5,      43.5      ,43.,       44.,       45.,      44.78125,
            45.78125,  46.78125  ,46.       ,47.    ,   48. ,      46.28125 , 47.28125,  48.28125,   44.125    ,45.125,
            46.125,    45.34375,  46.34375,  47.34375,  47.125,    48.125    ,49.125    ,48.625,    49.625 ,   50.625,
            50.125 ,   51.125,    52.125    ,51.90625  ,52.90625,  53.90625,  53.125,    54.125,    55.125,    53.40625,
            54.40625  ,55.40625,  49.       ,50.      , 51.       ,50.21875,  51.21875  ,52.21875  ,52.       ,53.,
            54.       ,53.5 ,     54.5,      55.5      ,55.       ,56.       ,57.       ,56.78125  ,57.78125,  58.78125,
            58.       ,59.       ,60.       ,58.28125  ,59.28125  ,60.28125,  50.125,    51.125    ,52.125    ,51.34375,
            52.34375  ,53.34375  ,53.125,    54.125,    55.125    ,54.625    ,55.625    ,56.625    ,56.125    ,57.125,
            58.125,    57.90625  ,58.90625  ,59.90625  ,59.125    ,60.125    ,61.125,    59.40625,  60.40625  ,61.40625,
            61.       ,62.       ,63.       ,62.21875,  63.21875,  64.21875  ,64.       ,65.       ,66.       ,65.5 ,
            66.5,      67.5,      67.       ,68.       ,69.       ,68.78125  ,69.78125  ,70.78125  ,70.,       71.  ,
            72.       ,70.28125  ,71.28125  ,72.28125  ,65.875    ,66.875,    67.875    ,67.09375  ,68.09375  ,69.09375,
            68.875    ,69.875    ,70.875,    70.375    ,71.375    ,72.375    ,71.875    ,72.875    ,73.875    ,73.65625,
            74.65625  ,75.65625  ,74.875    ,75.875,    76.875    ,75.15625  ,76.15625,
            77.15625  ,73.       ,74.       ,75.,       74.21875  ,75.21875  ,76.21875,
            76.       ,77.       ,78.       ,77.5      ,78.5      ,79.5      ,79.,
            80.       ,81.       ,80.78125  ,81.78125,  82.78125 ,82.       ,83.,
            84.       ,82.28125  ,83.28125  ,84.28125,  79.      ,80.       ,81.,
            80.21875  ,81.21875  ,82.21875  ,82.,       83.      ,84.       ,83.5,
            84.5      ,85.5      ,85.       ,86.,       87.      ,86.78125  ,87.78125,
            88.78125  ,88.       ,89.       ,90.,       88.28125 ,89.28125  ,90.28125,
            85.       ,86.       ,87.       ,86.21875,  87.21875 ,88.21875  ,88.,
            89.       ,90.       ,89.5      ,90.5,      91.5     ,91.       ,92.,
            93.       ,92.78125  ,93.78125  ,94.78125,  94.      ,95.       ,96.,
            94.28125  ,95.28125  ,96.28125  ,91.,       92.      ,93.       ,92.21875,
            93.21875  ,94.21875  ,94.       ,95.,       96.      ,95.5      ,96.5,
            97.5      ,97.       ,98.       ,99.,       98.78125 ,99.78125 ,100.78125,
            100.      ,101.      ,102.      ,100.28125, 101.28125 ,102.28125,  97.,
            98.       ,99.       ,98.21875  ,99.21875, 100.21875 ,100.,      101.,
            102.      ,101.5     ,102.5     ,103.5,     103.      ,104.,      105.,
            104.78125 ,105.78125 ,106.78125 ,106.,      107.      ,108.,      106.28125,
            107.28125 ,108.28125 ,104.125   ,105.125,   106.125   ,105.34375, 106.34375,
            107.34375 ,107.125   ,108.125   ,109.125,   108.625   ,109.625,   110.625,
            110.125   ,111.125   ,112.125   ,111.90625, 112.90625 ,113.90625, 113.125,
            114.125   ,115.125   ,113.40625 ,114.40625, 115.40625 ,109.,      110.,
            111.      ,110.21875 ,111.21875 ,112.21875, 112.,      113.,      114.,
            113.5     ,114.5     ,115.5     ,115.,      116.,      117.,      116.78125,
            117.78125 ,118.78125 ,118.      ,119.,      120.,      118.28125, 119.28125,
            120.28125 ,110.125   ,111.125   ,112.125,   111.34375, 112.34375, 113.34375,
            113.125   ,114.125   ,115.125   ,114.625,   115.625,   116.625,   116.125,
            117.125   ,118.125   ,117.90625, 118.90625, 119.90625, 119.125,   120.125,
            121.125   ,119.40625 ,120.40625, 121.40625});    //input = 1.f;
    input.linspace(1);
    auto size = NDArrayFactory::create<int>({10, 8});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 10x8");
//    expected.printBuffer("Expect for 10x8");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}

TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test3) {

    NDArray input    = NDArrayFactory::create<double>('c', {1, 3, 3, 4});
    NDArray expected = NDArrayFactory::create<double>('c', {1, 6, 6, 4}, {
            1.    ,2.     ,3.     ,4.,
            2.625 ,3.625  ,4.625  ,5.625,
            5.    ,6.     ,7.     ,8.,
            7.375 ,8.375  ,9.375, 10.375,
            9.    ,10.    ,11.    ,12.,
            9.375 ,10.375 ,11.375 ,12.375,

            5.875  ,6.875  ,7.875 , 8.875 ,
            7.5    ,8.5    ,9.5   , 10.5  ,
            9.875  ,10.875 ,11.875, 12.875,
            12.25  ,13.25  ,14.25 , 15.25 ,
            13.875 ,14.875 ,15.875, 16.875,
            14.25  ,15.25  ,16.25 , 17.25 ,

            13.    ,14.    ,15.    ,16.,
            14.625  ,15.625 ,16.625 ,17.625,
            17.     ,18.    ,19.    ,20.,
            19.375  ,20.375 ,21.375 ,22.375,
            21.     ,22.    ,23.    ,24.,
            21.375  ,22.375 ,23.375 ,24.375,

            20.125 ,21.125 ,22.125 ,23.125,
            21.75   ,22.75  ,23.75  ,24.75,
            24.125  ,25.125 ,26.125 ,27.125,
            26.5    ,27.5   ,28.5   ,29.5,
            28.125  ,29.125 ,30.125 ,31.125,
            28.5    ,29.5   ,30.5   ,31.5,

            25.   , 26.   , 27.   , 28.,
            26.625 ,27.625 ,28.625 ,29.625,
            29.    ,30.    ,31.    ,32.,
            31.375 ,32.375 ,33.375 ,34.375,
            33.    ,34.    ,35.    ,36.,
            33.375 ,34.375 ,35.375 ,36.375,

            26.125, 27.125, 28.125, 29.125,
            27.75  ,28.75  ,29.75  ,30.75,
            30.125 ,31.125 ,32.125 ,33.125,
            32.5   ,33.5   ,34.5   ,35.5,
            34.125 ,35.125 ,36.125 ,37.125,
            34.5   ,35.5   ,36.5   ,37.5
    });
    input.linspace(1);
    auto size = NDArrayFactory::create<int>({6, 6});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 6x6");
//    expected.printBuffer("Expect for 6x6");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}

TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test4) {

    NDArray input    = NDArrayFactory::create<double>('c', {1, 3, 4, 3});
    NDArray expected = NDArrayFactory::create<double>('c', {1, 6, 8, 3}, {
            1. ,      2.    ,   3.    ,
             2.21875  ,3.21875  ,4.21875,
             4.       ,5.       ,6.     ,
             5.5      ,6.5      ,7.5    ,
             7.       ,8.       ,9.     ,
             8.78125  ,9.78125, 10.78125,
            10.      ,11.,      12.     ,
            10.28125 ,11.28125, 12.28125,

             5.875   , 6.875   , 7.875  ,
             7.09375 , 8.09375 , 9.09375,
             8.875   , 9.875   ,10.875  ,
            10.375   ,11.375   ,12.375  ,
            11.875   ,12.875   ,13.875  ,
            13.65625 ,14.65625 ,15.65625,
            14.875   ,15.875   ,16.875  ,
            15.15625 ,16.15625 ,17.15625,

            13.,      14.,      15.,
            14.21875 ,15.21875 ,16.21875,
            16.      ,17.      ,18.     ,
            17.5     ,18.5     ,19.5    ,
            19.      ,20.      ,21.     ,
            20.78125 ,21.78125 ,22.78125,
            22.      ,23.      ,24.     ,
            22.28125 ,23.28125 ,24.28125,

            20.125 ,  21.125 ,  22.125,
            21.34375 ,22.34375 ,23.34375,
            23.125   ,24.125   ,25.125  ,
            24.625   ,25.625   ,26.625  ,
            26.125   ,27.125   ,28.125  ,
            27.90625 ,28.90625 ,29.90625,
            29.125   ,30.125   ,31.125  ,
            29.40625 ,30.40625 ,31.40625,

            25.      ,26.      ,27.     ,
            26.21875 ,27.21875 ,28.21875,
            28.      ,29.      ,30.     ,
            29.5     ,30.5     ,31.5    ,
            31.      ,32.      ,33.     ,
            32.78125 ,33.78125 ,34.78125,
            34.      ,35.      ,36.     ,
            34.28125 ,35.28125 ,36.28125,

            26.125   ,27.125 ,  28.125  ,
            27.34375 ,28.34375 ,29.34375,
            29.125   ,30.125   ,31.125  ,
            30.625   ,31.625   ,32.625  ,
            32.125   ,33.125   ,34.125  ,
            33.90625 ,34.90625 ,35.90625,
            35.125   ,36.125   ,37.125  ,
            35.40625 ,36.40625 ,37.40625 });
    input.linspace(1);
    auto size = NDArrayFactory::create<int>({6, 8});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 6x8");
//    expected.printBuffer("Expect for 6x8");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}

TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test5) {

    NDArray input    = NDArrayFactory::create<double>('c', {1, 4, 4, 3});
    NDArray expected = NDArrayFactory::create<double>('c', {1, 8, 8, 3}, {
            1.       ,2.      , 3.      , 2.21875 , 3.21875 , 4.21875 , 4.      , 5.      ,
            6.       ,5.5     , 6.5     , 7.5     , 7.      , 8.      , 9.      , 8.78125 ,
            9.78125  ,10.78125 ,10.     ,11.      ,12.      ,10.28125 ,11.28125 ,12.28125 ,
            5.875    ,6.875   , 7.875   , 7.09375 , 8.09375 , 9.09375 , 8.875   , 9.875   ,
            10.875   ,10.375  , 11.375  , 12.375  , 11.875  , 12.875  , 13.875  , 13.65625,
            14.65625 ,15.65625, 14.875  , 15.875  , 16.875  , 15.15625, 16.15625, 17.15625,
            13.      ,14.     , 15.     , 14.21875, 15.21875, 16.21875, 16.     , 17.     ,
            18.      ,17.5    , 18.5    , 19.5    , 19.     , 20.     , 21.     , 20.78125,
            21.78125 ,22.78125, 22.     , 23.     , 24.     , 22.28125, 23.28125, 24.28125,
            19.      ,20.     , 21.     , 20.21875, 21.21875, 22.21875, 22.     , 23.     ,
            24.      ,23.5    , 24.5    , 25.5    , 25.     , 26.     , 27.     , 26.78125,
            27.78125 ,28.78125, 28.     , 29.     , 30.     , 28.28125, 29.28125, 30.28125,
            25.      ,26.     , 27.     , 26.21875, 27.21875, 28.21875, 28.     , 29.     ,
            30.      ,29.5    , 30.5    , 31.5    , 31.     , 32.     , 33.     , 32.78125,
            33.78125 ,34.78125, 34.     , 35.     , 36.     , 34.28125, 35.28125, 36.28125,
            32.125   ,33.125  , 34.125  , 33.34375, 34.34375, 35.34375, 35.125  , 36.125  ,
            37.125   ,36.625  , 37.625  , 38.625  , 38.125  , 39.125  , 40.125  , 39.90625,
            40.90625 ,41.90625, 41.125  , 42.125  , 43.125  , 41.40625, 42.40625, 43.40625,
            37.      ,38.     , 39.     , 38.21875, 39.21875, 40.21875, 40.     , 41.     ,
            42.      ,41.5    , 42.5    , 43.5    , 43.     , 44.     , 45.     , 44.78125,
            45.78125 ,46.78125, 46.     , 47.     , 48.     , 46.28125, 47.28125, 48.28125,
            38.125   ,39.125  , 40.125  , 39.34375, 40.34375, 41.34375, 41.125  , 42.125  ,
            43.125   ,42.625  , 43.625  , 44.625  , 44.125  , 45.125  , 46.125  , 45.90625,
            46.90625 ,47.90625, 47.125  , 48.125  , 49.125  , 47.40625, 48.40625, 49.40625,
  });
    input.linspace(1);
    auto size = NDArrayFactory::create<int>({8, 8});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 8x8");
//    expected.printBuffer("Expect for 8x8");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}

TEST_F(DeclarableOpsTests11, ImageResizeBicubic_Test6) {

    NDArray input    = NDArrayFactory::create<double>('c', {7, 7, 1}, {
             1, 2.1, 3.15, 4.2, 5.15,  6.1,   7,
             8, 9.1,  10.,  11, 12.9, 13.1,  14,
            15, 16.,  17.,  18,   19,  20.,  21,
            22, 23.,  24.,  25,   26,   27,  28,
            30,  31,   32,  33,  34.,   35,  36,
            37,  38,   39,  40,  41.,   42,  43,
            44,  45,   46,  47,  48.,   49,  50
    });

    NDArray expected = NDArrayFactory::create<double>('c', {30, 30, 1}, {
        1.         ,1.1976162  ,1.4174359  ,1.6775769  ,1.9961575  ,2.3283265 ,
        2.550918   ,2.7360606  ,2.9655411  ,3.2929654  ,3.5441515  ,3.7380352 ,
        3.948995   ,4.248106   ,4.5073795  ,4.6843743  ,4.8572845  ,5.104302  ,
        5.3869915  ,5.581401   ,5.7539616  ,5.974285   ,6.272836   ,6.5204263 ,
        6.718899   ,6.8871036  ,7.039068   ,7.099216   ,7.0784245  ,7.0281887 ,
        2.247592   ,2.446947   ,2.6694887  ,2.9312382  ,3.248216   ,3.5745337 ,
        3.78931    ,3.9656973  ,4.186417   ,4.5046535  ,4.740569   ,4.9217057 ,
        5.133866   ,5.459533   ,5.7744613  ,6.0197873  ,6.254011   ,6.535633  ,
        6.8097296  ,6.9607787  ,7.0749416  ,7.241601   ,7.5094895  ,7.7499495 ,
        7.954571   ,8.131972   ,8.286526   ,8.346463   ,8.325745   ,8.275683  ,
        3.6286845  ,3.830573   ,4.0569587  ,4.3211575  ,4.6364856  ,4.9556503 ,
        5.160583   ,5.3258467  ,5.535462   ,5.84216    ,6.058749   ,6.223753  ,
        6.437597   ,6.797369   ,7.1836042  ,7.5164022  ,7.8290343  ,8.154773  ,
        8.417635   ,8.512958   ,8.5521     ,8.649708   ,8.87788    ,9.108794  ,
        9.320926   ,9.509781   ,9.667375   ,9.72694    ,9.706349   ,9.656599  ,
        5.276778   ,5.480438   ,5.709702   ,5.9754477  ,6.288551   ,6.6005697 ,
        6.796207   ,6.9511423  ,7.1503997  ,7.4461427  ,7.644651   ,7.794562  ,
        8.009684   ,8.400473   ,8.851847   ,9.26469    ,9.649218,  10.015648  ,
        10.268647  ,10.313368  ,10.2843275 ,10.319379  ,10.512033  ,10.734956 ,
        10.954604  ,11.154507  ,11.315369  ,11.374779  ,11.354242  ,11.304622 ,
        7.325373   ,7.5284843  ,7.757575   ,8.022221   ,8.331997   ,8.638187  ,
        8.827649   ,8.976217   ,9.168955   ,9.45726    ,9.6442375  ,9.784517  ,
        9.999621,  10.407702  ,10.896234,  11.355122,  11.781423,  12.172186  ,
        12.420712  ,12.4374485 ,12.370511  ,12.371386  ,12.545973  ,12.766424 ,
        12.992249  ,13.20012   ,13.364252  ,13.424109  ,13.40342   ,13.353425 ,
        9.493208   ,9.692467   ,9.9169445,  10.176801,  10.482199,  10.78547   ,
        10.974367  ,11.123442  ,11.31637   ,11.603645  ,11.790616  ,11.930889 ,
        12.144082  ,12.546447  ,13.024898  ,13.4723    ,13.889232  ,14.276275 ,
        14.528972  ,14.555555  ,14.50145   ,14.515459  ,14.700572  ,14.927055 ,
        15.156046  ,15.366046  ,15.532901  ,15.594008  ,15.5728855 ,15.521847 ,
        10.970133  ,11.163599  ,11.380694  ,11.633735  ,11.935032  ,12.238887 ,
        12.43254   ,12.588294  ,12.787534  ,13.079956  ,13.27752   ,13.426631 ,
        13.636713  ,14.013844  ,14.441672  ,14.827978  ,15.191209  ,15.549808 ,
        15.81343   ,15.881828  ,15.883522  ,15.950411  ,16.16933   ,16.40794  ,
        16.636436  ,16.842583  ,17.010887  ,17.07363   ,17.05194   ,16.999537 ,
        12.219155  ,12.406129  ,12.614796  ,12.860335  ,13.157928  ,13.464224 ,
        13.665207  ,13.830567  ,14.039036  ,14.339629  ,14.552863  ,14.715049 ,
        14.921564  ,15.264454  ,15.622843  ,15.924977  ,16.213829  ,16.532364 ,
        16.8099    ,16.934835  ,17.012146  ,17.150164  ,17.413412  ,17.666712 ,
        17.892765  ,18.09207   ,18.261044  ,18.325531  ,18.303238  ,18.249378 ,
        13.7663965 ,13.947391  ,14.148263  ,14.386917  ,14.681246  ,14.990087 ,
        15.198166  ,15.372728  ,15.590062  ,15.898583  ,16.126892  ,16.301655 ,
        16.50487   ,16.815214  ,17.107498  ,17.329458  ,17.547403  ,17.827654 ,
        18.118288  ,18.296928  ,18.4461    ,18.651634  ,18.956806  ,19.22382  ,
        19.447308  ,19.639887  ,19.809319  ,19.875397  ,19.852556  ,19.797365 ,
        15.9419365 ,16.118704  ,16.314133  ,16.547867  ,16.839561  ,17.14954  ,
        17.361883  ,17.542162  ,17.764957  ,18.078188  ,18.315733  ,18.498205 ,
        18.699116  ,18.988684  ,19.238989  ,19.410137  ,19.583265  ,19.839512 ,
        20.13878   ,20.35177   ,20.546844  ,20.795671  ,21.128067  ,21.404358 ,
        21.626736  ,21.8155    ,21.98561   ,22.052843  ,22.029604  ,21.973448 ,
        17.53522   ,17.71077   ,17.904636  ,18.13695   ,18.42784   ,18.738056 ,
        18.951529  ,19.133352  ,19.357613  ,19.672083  ,19.912102  ,20.096638 ,
        20.296894  ,20.580765  ,20.819603  ,20.976887  ,21.137802  ,21.387535 ,
        21.689209  ,21.911621  ,22.119276  ,22.37999   ,22.71991   ,22.998823 ,
        23.22097   ,23.40876   ,23.57911   ,23.646685  ,23.623325  ,23.566887 ,
        18.746353  ,18.922657  ,19.117487  ,19.350685  ,19.64207   ,19.952137 ,
        20.164913  ,20.345781  ,20.569134  ,20.88284   ,21.12133   ,21.30459  ,
        21.505253  ,21.792645  ,22.038572  ,22.204426  ,22.37289   ,22.626648 ,
        22.926834  ,23.143423  ,23.343302  ,23.596668  ,23.931936  ,24.209232 ,
        24.431519  ,24.619913  ,24.79011   ,24.857473  ,24.83419   ,24.777927 ,
        20.16656   ,20.344206  ,20.540766  ,20.775532  ,21.067804  ,21.377607 ,
        21.589132  ,21.768297  ,21.99003   ,22.302366  ,22.538124  ,22.719105 ,
        22.920494  ,23.214176  ,23.472767  ,23.653934  ,23.83589   ,24.096842 ,
        24.394371  ,24.600555  ,24.786541  ,25.026773  ,25.353731  ,25.62813  ,
        25.850672  ,26.04014   ,26.210072  ,26.277063  ,26.253906  ,26.197956 ,
        22.363024  ,22.54125   ,22.738552  ,22.973991  ,23.266647  ,23.57634  ,
        23.787327  ,23.96576   ,24.186796  ,24.498543  ,24.733124  ,24.913122 ,
        25.114826  ,25.411213  ,25.675262  ,25.863028  ,26.050789  ,26.314838 ,
        26.611223  ,26.812925  ,26.992926  ,27.227505  ,27.550882  ,27.824034 ,
        28.046684  ,28.236614  ,28.406433  ,28.473265  ,28.450163  ,28.394344 ,
        24.429443  ,24.60767   ,24.80497   ,25.04041   ,25.333065  ,25.642756 ,
        25.853743  ,26.032173  ,26.25321   ,26.564959  ,26.79954   ,26.97954  ,
        27.181242  ,27.47763   ,27.74168   ,27.929441  ,28.117207  ,28.381254 ,
        28.677637  ,28.879343  ,29.059345  ,29.293922  ,29.617298  ,29.890451 ,
        30.113104  ,30.303034  ,30.472853  ,30.539684  ,30.516582  ,30.460762 ,
        26.        ,26.178228  ,26.375526  ,26.61097   ,26.903624  ,27.213314 ,
        27.424305  ,27.602734  ,27.823772  ,28.135519  ,28.3701    ,28.550098 ,
        28.7518    ,29.04819   ,29.312237  ,29.5       ,29.687763  ,29.951813 ,
        30.2482    ,30.449903  ,30.629902  ,30.864483  ,31.187859  ,31.461012 ,
        31.683659  ,31.873592  ,32.043407  ,32.11024   ,32.087135  ,32.03132  ,
        27.570559  ,27.748787  ,27.946087  ,28.181528  ,28.474184  ,28.783876 ,
        28.994865  ,29.173294  ,29.39433   ,29.70608   ,29.940659  ,30.120655 ,
        30.32236   ,30.618746  ,30.882797  ,31.070557  ,31.25832   ,31.522371 ,
        31.818754  ,32.02046   ,32.20046   ,32.43504   ,32.758415  ,33.031567 ,
        33.25422   ,33.44415   ,33.613964  ,33.680794  ,33.657696  ,33.60188  ,
        29.636976  ,29.815207  ,30.0125    ,30.247944  ,30.5406    ,30.85029  ,
        31.061283  ,31.239712  ,31.46075   ,31.7725    ,32.00708   ,32.187077 ,
        32.38878   ,32.685165  ,32.949215  ,33.13698   ,33.32474   ,33.58879  ,
        33.885178  ,34.086884  ,34.26688   ,34.501457  ,34.824837  ,35.09799  ,
        35.320637  ,35.510574  ,35.68039   ,35.747215  ,35.724117  ,35.6683   ,
        31.83344   ,32.011665  ,32.20897   ,32.444412  ,32.73707   ,33.046757 ,
        33.257744  ,33.436176  ,33.657207  ,33.96896   ,34.203537  ,34.383537 ,
        34.58524   ,34.88163   ,35.145676  ,35.33344   ,35.521206  ,35.785255 ,
        36.081642  ,36.28334   ,36.46334   ,36.69792   ,37.021297  ,37.294453 ,
        37.517097  ,37.707027  ,37.876846  ,37.94368   ,37.920578  ,37.864758 ,
        33.253647  ,33.431873  ,33.62917   ,33.864613  ,34.15727   ,34.466957 ,
        34.677948  ,34.856377  ,35.077415  ,35.38916   ,35.623745  ,35.803745 ,
        36.005447  ,36.301834  ,36.565884  ,36.753647  ,36.941406  ,37.205456 ,
        37.50184   ,37.703545  ,37.883545  ,38.118122  ,38.4415    ,38.714653 ,
        38.9373    ,39.127235  ,39.297054  ,39.363884  ,39.340782  ,39.28496  ,
        34.464783  ,34.64301   ,34.840305  ,35.075752  ,35.368404  ,35.6781   ,
        35.889088  ,36.067516  ,36.28855   ,36.6003    ,36.834885  ,37.014877 ,
        37.216583  ,37.51297   ,37.77702   ,37.964783  ,38.152546  ,38.416595 ,
        38.71298   ,38.914684  ,39.094685  ,39.32926   ,39.652645  ,39.925793 ,
        40.14844   ,40.338375  ,40.508194  ,40.575024  ,40.55192   ,40.496105 ,
        36.058067  ,36.23629   ,36.43359   ,36.669033  ,36.961685  ,37.271378 ,
        37.48237   ,37.6608    ,37.881836  ,38.19359   ,38.42817   ,38.608162 ,
        38.809868  ,39.10625   ,39.3703    ,39.558064  ,39.74583   ,40.00988  ,
        40.306267  ,40.50797   ,40.68797   ,40.92255   ,41.245926  ,41.519077 ,
        41.741722  ,41.931652  ,42.101475  ,42.168304  ,42.145203  ,42.089386 ,
        38.315002  ,38.493233  ,38.690533  ,38.925976  ,39.218628  ,39.52832  ,
        39.739307  ,39.917736  ,40.138775  ,40.45052   ,40.685104  ,40.865097 ,
        41.066803  ,41.36319   ,41.627243  ,41.815002  ,42.002766  ,42.26682  ,
        42.5632    ,42.764908  ,42.944904  ,43.179485  ,43.50286   ,43.776016 ,
        43.998665  ,44.188595  ,44.358418  ,44.425247  ,44.402145  ,44.34633  ,
        40.22708   ,40.40531   ,40.602608  ,40.83805   ,41.130707  ,41.440395 ,
        41.651382  ,41.82982   ,42.050854  ,42.3626    ,42.597183  ,42.77718  ,
        42.97888   ,43.27527   ,43.53932   ,43.72708   ,43.914845  ,44.178894 ,
        44.47528   ,44.676983  ,44.856983  ,45.09156   ,45.41494   ,45.68809  ,
        45.91074   ,46.100674  ,46.270493  ,46.337322  ,46.31422   ,46.2584   ,
        41.785618  ,41.963844  ,42.161144  ,42.396584  ,42.68924   ,42.998936 ,
        43.209923  ,43.388355  ,43.609394  ,43.921143  ,44.15572   ,44.335716 ,
        44.53742   ,44.833805  ,45.09786   ,45.285614  ,45.473377  ,45.737427 ,
        46.033817  ,46.235523  ,46.415524  ,46.650105  ,46.973476  ,47.24663  ,
        47.469276  ,47.65921   ,47.82903   ,47.895855  ,47.872753  ,47.81694  ,
        43.11514   ,43.293365  ,43.490665  ,43.726105  ,44.018764  ,44.328457 ,
        44.539444  ,44.717873  ,44.93891   ,45.25066   ,45.48524   ,45.665237 ,
        45.86694   ,46.163326  ,46.427376  ,46.615143  ,46.802902  ,47.066956 ,
        47.363342  ,47.56505   ,47.74505   ,47.979626  ,48.302998  ,48.576153 ,
        48.798798  ,48.98873   ,49.158546  ,49.225376  ,49.202282  ,49.146458 ,
        44.303867  ,44.482094  ,44.679394  ,44.914833  ,45.207493  ,45.51718  ,
        45.72817   ,45.9066    ,46.12764   ,46.439384  ,46.673965  ,46.853966 ,
        47.055668  ,47.352055  ,47.6161    ,47.803867  ,47.99163   ,48.25568  ,
        48.552063  ,48.75377   ,48.933773  ,49.16835   ,49.491726  ,49.764877 ,
        49.987526  ,50.17746   ,50.347275  ,50.4141    ,50.391006  ,50.335186 ,
        44.771675  ,44.949905  ,45.1472    ,45.382645  ,45.6753    ,45.98499  ,
        46.195976  ,46.374413  ,46.595448  ,46.907196  ,47.141773  ,47.321774 ,
        47.523476  ,47.819862  ,48.08391   ,48.27168   ,48.459446  ,48.72349  ,
        49.019882  ,49.22158   ,49.401585  ,49.63616   ,49.959538  ,50.232693 ,
        50.455338  ,50.64527   ,50.81509   ,50.88192   ,50.858818  ,50.803    ,
        44.609966  ,44.788193  ,44.985493  ,45.220936  ,45.51359   ,45.82328  ,
        46.03427   ,46.2127    ,46.433743  ,46.74549   ,46.98007   ,47.160065 ,
        47.36177   ,47.658157  ,47.922207  ,48.10997   ,48.297733  ,48.561783 ,
        48.858166  ,49.059875  ,49.239872  ,49.47445   ,49.79783   ,50.07098  ,
        50.293625  ,50.48356   ,50.653378  ,50.720203  ,50.6971    ,50.64128  ,
        44.219246  ,44.397472  ,44.594772  ,44.83021   ,45.122868  ,45.43256  ,
        45.643543  ,45.82198   ,46.04302   ,46.354763  ,46.589344  ,46.76934  ,
        46.971046  ,47.267433  ,47.531483  ,47.719242  ,47.907005  ,48.17105  ,
        48.467438  ,48.66914   ,48.849144  ,49.08372   ,49.4071    ,49.680256 ,
        49.902905  ,50.092834  ,50.262653  ,50.329483  ,50.30638   ,50.25057});

    auto size = NDArrayFactory::create<int>({30, 30});
    nd4j::ops::resize_bicubic op;
    auto results = op.execute({&input, &size}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());
    NDArray* result = results->at(0);

//    result->printBuffer("Resized to 30x30");
//    expected.printBuffer("Expect for 30x30");
    ASSERT_TRUE(expected.isSameShape(result));
    ASSERT_TRUE(expected.equalsTo(result));
    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, summaryStatsData_test1) {

    functions::summarystats::SummaryStatsData<double> var1;
    functions::summarystats::SummaryStatsData<double> var2;
    var2.n = var2.mean = var2.M2 = var2.M3 = var2.M4 = var2.bias = 5;

    functions::summarystats::SummaryStatsData<double>* arr = new functions::summarystats::SummaryStatsData<double>[2];
    arr[0] = var1;
    arr[1] = var2;
    arr[0] = arr[1];

    functions::summarystats::SummaryStatsData<double> var3(var1);

    ASSERT_TRUE(arr[0].n == arr[0].mean && arr[0].M2 == arr[0].M3 && arr[0].n == 5);
    ASSERT_TRUE(arr[1].n == arr[1].mean && arr[1].M2 == arr[1].M3 && arr[1].n == 5);
    ASSERT_TRUE(var3.n == var3.mean && var3.M2 == var3.M3 && var3.n == 0);

    delete []arr;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test1) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.96, -1.92, -2.88, -3.84, -4.8 , -5.76, -6.72, -7.68, -8.64, -9.6 ,-10.56,-11.52,
                                   -12.48,-13.44,-14.4 ,-15.36,-16.32,-17.28,-18.24,-19.2 ,-20.16,-21.12,-22.08,-23.04});
    NDArray dLdwExp('c', {2,3,4}, {0.9216 ,  3.6864 ,  8.2944 , 14.7456 , 23.04   , 33.1776 , 45.1584 , 58.9824 , 74.6496 , 92.16   ,111.51361,132.7104 ,
                                   155.75038,180.63359,207.35999,235.9296 ,266.34238,298.59842,332.6976 ,368.64001,406.4256 ,446.05444,487.5264 ,530.84161});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto dLdp = results->at(0);
    auto dLdw = results->at(1);
    auto dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test2) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,1,4}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {2,1,4}, {98.61121,129.024  , 164.9664 , 206.4384 , 828.51837,925.28644,1027.58398,1135.41113});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test3) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.96, -1.92, -2.88, -3.84, -4.8 , -5.76, -6.72, -7.68, -8.64, -9.6 ,-10.56,-11.52,
                                   -12.48,-13.44,-14.4 ,-15.36,-16.32,-17.28,-18.24,-19.2 ,-20.16,-21.12,-22.08,-23.04});
    NDArray dLdwExp('c', {}, {4515.84});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test4) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {807.32153, 1426.63684, 2281.88159});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test5) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.08,-0.16,-0.24,-0.32,-0.4 ,-0.48,-0.56,-0.64,-0.72,-0.8 ,-0.88,-0.96,
                                   -1.04,-1.12,-1.2 ,-1.28,-1.36,-1.44,-1.52,-1.6 ,-1.68,-1.76,-1.84,-1.92});
    NDArray dLdwExp('c', {2,3,4}, {-15.6032,-15.3728,-14.9888,-14.4512,-13.76  ,-12.9152,-11.9168,-10.7648, -9.4592, -8.    , -6.3872, -4.6208,
                                   -2.7008, -0.6272,  1.6   ,  3.9808,  6.5152,  9.2032, 12.0448, 15.04  , 18.1888, 21.4912, 24.9472, 28.5568});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test6) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {-58.16319, -6.5536 , 64.71682});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test7) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {}, {0.});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test8) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0. ,0. ,0. ,0. ,-0.48 ,-0.576,-0.672,-0.768,-0.864,-0.96 ,-1.056,-1.152,
                                 -1.248,-1.344,-1.44 ,-1.536,-1.632,-1.728,-1.824,-1.92 ,-2.016,-2.112,-2.208,-2.304});
    NDArray dLdwExp('c', {2,3,4}, {-22.3488 ,-22.07232,-21.61152,-20.9664 ,-20.13696,-19.1232 ,-17.92512,-16.54272,-14.976  ,-13.22496,-11.2896 , -9.16992,
                                   -6.86592, -4.3776 , -1.70496,  1.152  ,  4.19328,  7.41888, 10.8288 , 14.42304, 18.2016 , 22.16449, 26.31168, 30.6432 });

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.p(0, 0.);
    weights.p(1, 0.);
    weights.p(2, 0.);
    weights.p(3, 0.);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test9) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.04,-0.08,-0.12,-0.16,-0.2 ,-0.24,-0.28,-0.32,-0.36,-0.4 ,-0.44,-0.48,
                                   -0.52,-0.56,-0.6 ,-0.64,-0.68,-0.72,-0.76,-0.8 ,-0.84,-0.88,-0.92,-0.96});
    NDArray dLdwExp('c', {2,3,4}, {0.0384, 0.1536, 0.3456, 0.6144, 0.96  , 1.3824, 1.8816, 2.4576, 3.1104, 3.84  , 4.6464, 5.5296,
                                    6.4896, 7.5264, 8.64  , 9.8304,11.0976,12.4416,13.8624,15.36  ,16.9344,18.5856,20.3136,22.1184});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test10) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,1}, {188.16});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test11) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {33.6384 ,59.4432 ,95.07841});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test12) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0.,0.,0.,0., -0.24 ,-0.288,-0.336,-0.384,-0.432,-0.48 ,-0.528,-0.576,
                                  -0.624,-0.672,-0.72 ,-0.768,-0.816,-0.864,-0.912,-0.96 ,-1.008,-1.056,-1.104,-1.152});
    NDArray dLdwExp('c', {2,3,4}, {0.04608, 0.18432, 0.41472, 0.73728, 1.152  , 1.65888, 2.25792, 2.94912, 3.73248, 4.608  , 5.57568, 6.63552,
                                   7.78752, 9.03168,10.368  ,11.79648,13.31712,14.92992,16.63488,18.432  ,20.32128,22.30272,24.37632,26.54208});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;
    weights.t<double>(3) = 0.;

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, mean_sqerr_loss_grad_test13) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
                                  -1.04,-1.12,-1.2 ,-1.28,-1.36,-1.44,-1.52,-1.6 ,-1.68,-1.76,-1.84,-1.92});
    NDArray dLdwExp('c', {2,3,1}, {2.304  , 13.3632 , 34.2528 , 64.97279,105.5232 ,155.90401});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;

    nd4j::ops::mean_sqerr_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

TEST_F(DeclarableOpsTests11, SquaredSubtractTest_Test1) {
    auto x = NDArrayFactory::create<float>('c', {4}, {0, 1, 2, 3});
    auto y = NDArrayFactory::create<float>('c',{4}, {3, 2, 1, 0});
    auto exp = NDArrayFactory::create<float>('c', {4}, {9, 1,1, 9});
    nd4j::ops::squaredsubtract op;
    auto result = op.execute({&x, &y}, {}, {});
    ASSERT_EQ(Status::OK(), result->status());
    ASSERT_TRUE(exp.equalsTo(result->at(0)));

    delete result;
}

TEST_F(DeclarableOpsTests11, SquaredSubtractTest_Test2) {
    auto x = NDArrayFactory::create<float>('c', {2, 4}, {0, 1, 2, 3, 0, 1, 2, 3});
    auto y = NDArrayFactory::create<float>('c',{4}, {3, 2, 1, 0});
    auto exp = NDArrayFactory::create<float>('c', {2, 4}, {9, 1,1, 9, 9, 1, 1, 9});
    nd4j::ops::squaredsubtract op;
    auto result = op.execute({&x, &y}, {}, {});
    ASSERT_EQ(Status::OK(), result->status());
    ASSERT_TRUE(exp.equalsTo(result->at(0)));
    delete result;
}

TEST_F(DeclarableOpsTests11, SquaredSubtractTest_Test3) {
    auto x = NDArrayFactory::create<float>('c', {2, 4}, {0, 1, 2, 3, 0, 1, 2, 3});
    auto y = NDArrayFactory::create<float>('c',{4}, {3, 2, 1, 0});
    auto exp = NDArrayFactory::create<float>('c', {2, 4}, {-6, -4, 6, 24, -30, -12, 14, 48});
    auto eps = NDArrayFactory::create<float>('c', {2, 4}, {1,2,3,4,5,6,7,8});
    nd4j::ops::squaredsubtract_bp op;
    auto result = op.execute({&x, &y, &eps}, {}, {});
    ASSERT_EQ(Status::OK(), result->status());
    ASSERT_TRUE(exp.equalsTo(result->at(0)));
    delete result;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test1) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,
                                   -0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5});
    NDArray dLdwExp('c', {2,3,4}, {0.96, 1.92, 2.88, 3.84, 4.8 , 5.76, 6.72, 7.68, 8.64, 9.6 ,10.56,11.52,
                                  12.48,13.44,14.4 ,15.36,16.32,17.28,18.24,19.2 ,20.16,21.12,22.08,23.04});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto dLdp = results->at(0);
    auto dLdw = results->at(1);
    auto dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test2) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,1,4}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {2,1,4}, {14.4 , 17.28, 20.16, 23.04, 48.96, 51.84, 54.72, 57.6});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test3) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,
                                   -0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5});
    NDArray dLdwExp('c', {}, {288.});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test4) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {65.28, 96., 126.72001});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test5) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,
                                   -0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167,-0.04167});
    NDArray dLdwExp('c', {2,3,4}, {-0.92,-0.84,-0.76,-0.68,-0.6 ,-0.52,-0.44,-0.36,-0.28,-0.2 ,-0.12,-0.04,
                                     0.04, 0.12, 0.2 , 0.28, 0.36, 0.44, 0.52, 0.6 , 0.68, 0.76, 0.84, 0.92});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test6) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {-2.56, 0., 2.56});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test7) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {}, {0.});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test8) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.  ,-0.  ,-0.  ,-0.  ,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,
                                   -0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05,-0.05});
    NDArray dLdwExp('c', {2,3,4}, {-1.296,-1.2  ,-1.104,-1.008,-0.912,-0.816,-0.72 ,-0.624,-0.528,-0.432,-0.336,-0.24 ,
                                    -0.144,-0.048, 0.048, 0.144, 0.24 , 0.336, 0.432, 0.528, 0.624, 0.72 , 0.816, 0.912});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.p(0, 0.);
    weights.p(1, 0.);
    weights.p(2, 0.);
    weights.p(3, 0.);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test9) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.02083, -0.02083, -0.02083, -0.02083,-0.02083, -0.02083, -0.02083, -0.02083,-0.02083, -0.02083, -0.02083, -0.02083,
                                   -0.02083, -0.02083, -0.02083, -0.02083,-0.02083, -0.02083, -0.02083, -0.02083,-0.02083, -0.02083, -0.02083, -0.02083});
    NDArray dLdwExp('c', {2,3,4}, {0.04, 0.08, 0.12, 0.16, 0.2 , 0.24, 0.28, 0.32,0.36, 0.4 , 0.44, 0.48,
                                   0.52, 0.56, 0.6 , 0.64,0.68, 0.72, 0.76, 0.8 ,0.84, 0.88, 0.92, 0.96});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test10) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,1}, {12.});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test11) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {2.72, 4., 5.28});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test12) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0., 0., 0., 0., -0.025, -0.025, -0.025, -0.025,-0.025, -0.025, -0.025, -0.025,
                                   -0.025, -0.025, -0.025, -0.025,-0.025, -0.025, -0.025, -0.025,-0.025, -0.025, -0.025, -0.025});
    NDArray dLdwExp('c', {2,3,4}, {0.048, 0.096, 0.144, 0.192,0.24 , 0.288, 0.336, 0.384,0.432, 0.48 , 0.528, 0.576,
                                   0.624, 0.672, 0.72 , 0.768,0.816, 0.864, 0.912, 0.96 ,1.008, 1.056, 1.104, 1.152});

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;
    weights.t<double>(3) = 0.;

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, absolute_difference_loss_grad_test13) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray predictions('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0., 0., 0., 0., 0., 0., 0., 0.,0., 0., 0., 0.,
                                  -0.04167, -0.04167, -0.04167, -0.04167,-0.04167, -0.04167, -0.04167, -0.04167,-0.04167, -0.04167, -0.04167, -0.04167});
    NDArray dLdwExp('c', {2,3,1}, {0.8 ,2.08,3.36,4.64,5.92,7.2 });

    predictions.linspace(0.04, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;

    nd4j::ops::absolute_difference_loss_grad op;
    auto results = op.execute({&predictions, &weights, &labels}, {}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdpExp.isSameShape(-*dLdl));
    ASSERT_TRUE(dLdpExp.equalsTo(-*dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_1) {

    NDArray x = NDArrayFactory::create<bfloat16>('c', {2,3,4});
    NDArray y = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(1);
    y.linspace(1);
    exp.linspace(2,2);
    nd4j::ops::add op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_2) {

    NDArray x = NDArrayFactory::create<float16>('c', {2,3,4});
    NDArray y = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp = NDArrayFactory::create<float16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(1);
    y.linspace(1);
    exp.linspace(2,2);
    nd4j::ops::add op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_3) {

    NDArray x('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray y('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(1);
    y.linspace(1);
    exp.linspace(2,2);
    nd4j::ops::add op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test1) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.25999, -0.755  , -1.25   , -1.745  , -2.24001, -2.73502, -3.23004, -3.72508, -4.22014, -4.71523, -5.21034, -5.70548,
                                   -6.20066, -6.69587, -7.19113, -7.68643, -8.18177, -8.67717, -9.17262, -9.66813,-10.1637 ,-10.65932,-11.15501,-11.65077});
    NDArray dLdwExp('c', {2,3,4}, {0.73395,  0.75335,  0.69315,  0.55335,  0.33395,  0.03495, -0.34366, -0.80186, -1.33967, -1.95708, -2.65411, -3.43074,
                                  -4.28698, -5.22285, -6.23833, -7.33343, -8.50815, -9.76251,-11.0965 ,-12.51013,-14.00341,-15.57633,-17.2289 ,-18.96113});
    NDArray dLdlExp('c', {2,3,4}, {0.04, 0.02,-0.  ,-0.02,-0.04,-0.06,-0.08,-0.1 ,-0.12,-0.14,-0.16,-0.18,
                                   -0.2 ,-0.22,-0.24,-0.26,-0.28,-0.3 ,-0.32,-0.34,-0.36,-0.38,-0.4 ,-0.42});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test2) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,1,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.18499,-0.53   ,-0.875  ,-1.22   ,-1.56501,-1.91002,-2.25504,-2.60008,-2.94514,-3.29023,-3.63534,-3.98048,
                                   -4.32566,-4.67087,-5.01613,-5.36143,-5.70677,-6.05217,-6.39762,-6.74313,-7.0887 ,-7.43432,-7.78001,-8.12577});
    NDArray dLdwExp('c', {2,1,4}, {0.43622, -0.19079, -0.98462, -1.94525,-18.09855,-20.72768,-23.52373,-26.48669});
    NDArray dLdlExp('c', {2,3,4}, {0.028,  0.014, -0.   , -0.014,-0.028, -0.042, -0.056, -0.07 ,-0.084, -0.098, -0.112, -0.126,
                                   -0.14 , -0.154, -0.168, -0.182,-0.196, -0.21 , -0.224, -0.238,-0.252, -0.266, -0.28 , -0.294});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test3) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.18499,-0.53   ,-0.875  ,-1.22   ,-1.56501,-1.91002,-2.25504,-2.60008,-2.94514,-3.29023,-3.63534,-3.98048,
                                   -4.32566,-4.67087,-5.01613,-5.36143,-5.70677,-6.05217,-6.39762,-6.74313,-7.0887 ,-7.43432,-7.78001,-8.12577});
    NDArray dLdwExp('c', {}, {-91.52109});
    NDArray dLdlExp('c', {2,3,4}, {0.028,  0.014, -0., -0.014,-0.028, -0.042, -0.056, -0.07 ,-0.084, -0.098, -0.112, -0.126,
                                   -0.14 , -0.154, -0.168, -0.182,-0.196, -0.21 , -0.224, -0.238,-0.252, -0.266, -0.28 , -0.294});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test4) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {-12.54779,-28.13393,-50.83936});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test5) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.01542,-0.04417,-0.07292,-0.10167,-0.13042,-0.15917,-0.18792,-0.21667,-0.24543,-0.27419,-0.30294,-0.33171,
                                   -0.36047,-0.38924,-0.41801,-0.44679,-0.47556,-0.50435,-0.53314,-0.56193,-0.59072,-0.61953,-0.64833,-0.67715});
    NDArray dLdwExp('c', {2,3,4}, {0.37794, 0.37906, 0.37554, 0.36739, 0.35461, 0.33719, 0.31514, 0.28846, 0.25714, 0.22119, 0.18061, 0.13539,
                                   0.08553, 0.03104,-0.02808,-0.09184,-0.16023,-0.23326,-0.31093,-0.39323,-0.48017,-0.57175,-0.66796,-0.76881});
    NDArray dLdlExp('c', {2,3,4}, {0.00233, 0.00117,-0.,-0.00117,-0.00233,-0.0035 ,-0.00467,-0.00583,-0.007  ,-0.00817,-0.00933,-0.0105,
                                   -0.01167,-0.01283,-0.014  ,-0.01517,-0.01633,-0.0175 ,-0.01867,-0.01983,-0.021  ,-0.02217,-0.02333,-0.0245});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test6) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {1.4966 , 0.19776,-1.69436});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test7) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights(nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {}, {0.});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test8) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, { 0.     , 0.     , 0.     , 0.     ,-0.1565 ,-0.191  ,-0.2255 ,-0.26001,-0.29451,-0.32902,-0.36353,-0.39805,
                                   -0.43257,-0.46709,-0.50161,-0.53614,-0.57068,-0.60522,-0.63976,-0.67431,-0.70887,-0.74343,-0.778  ,-0.81258});
    NDArray dLdwExp('c', {2,3,4}, {0.54353, 0.54487, 0.54065, 0.53087, 0.51553, 0.49463, 0.46817, 0.43615, 0.39857, 0.35543, 0.30672, 0.25246,
                                   0.19264, 0.12725, 0.0563 ,-0.02021,-0.10228,-0.18992,-0.28312,-0.38188,-0.48621,-0.5961 ,-0.71156,-0.83258});
    NDArray dLdlExp('c', {2,3,4}, {-0.    ,-0.    , 0.    , 0.    ,-0.0028,-0.0042,-0.0056,-0.007 ,-0.0084,-0.0098,-0.0112,-0.0126,
                                  -0.014 ,-0.0154,-0.0168,-0.0182,-0.0196,-0.021 ,-0.0224,-0.0238,-0.0252,-0.0266,-0.028 ,-0.0294});
    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.p(0, 0.);
    weights.p(1, 0.);
    weights.p(2, 0.);
    weights.p(3, 0.);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test9) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.00771, -0.02208, -0.03646, -0.05083,-0.06521, -0.07958, -0.09396, -0.10834,-0.12271, -0.13709, -0.15147, -0.16585,
                                   -0.18024, -0.19462, -0.20901, -0.22339,-0.23778, -0.25217, -0.26657, -0.28096,-0.29536, -0.30976, -0.32417, -0.33857});
    NDArray dLdwExp('c', {2,3,4}, {0.03008,  0.03064,  0.02888,  0.02481, 0.01841,  0.00971, -0.00132, -0.01466,-0.03032, -0.0483 , -0.06859, -0.0912 ,
                                   -0.11612, -0.14337, -0.17293, -0.20481,-0.23901, -0.27552, -0.31435, -0.35551,-0.39898, -0.44476, -0.49287, -0.5433 });
    NDArray dLdlExp('c', {2,3,4}, {0.00117,  0.00058, -0.     , -0.00058,-0.00117, -0.00175, -0.00233, -0.00292,-0.0035 , -0.00408, -0.00467, -0.00525,
                                   -0.00583, -0.00642, -0.007  , -0.00758,-0.00817, -0.00875, -0.00933, -0.00992,-0.0105 , -0.01108, -0.01167, -0.01225});
    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test10) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,1}, {-3.81338});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test11) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdwExp('c', {1,3,1}, {-0.52282,-1.17225,-2.11831});

    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdw = results->at(1);

    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test12) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0.     ,  0.     ,  0.     ,  0.     ,-0.07825, -0.0955 , -0.11275, -0.13   ,-0.14726, -0.16451, -0.18177, -0.19902,
                                   -0.21628, -0.23354, -0.25081, -0.26807,-0.28534, -0.30261, -0.31988, -0.33716,-0.35443, -0.37172, -0.389  , -0.40629});
    NDArray dLdwExp('c', {2,3,4}, {0.0361 ,  0.03677,  0.03466,  0.02977, 0.0221 ,  0.01165, -0.00158, -0.01759,-0.03638, -0.05795, -0.08231, -0.10944,
                                   -0.13935, -0.17204, -0.20752, -0.24577,-0.28681, -0.33063, -0.37723, -0.42661,-0.47877, -0.53372, -0.59144, -0.65196});
    NDArray dLdlExp('c', {2,3,4}, {-0.    , -0.    ,  0.    ,  0.    ,-0.0014, -0.0021, -0.0028, -0.0035,-0.0042, -0.0049, -0.0056, -0.0063,
                                   -0.007 , -0.0077, -0.0084, -0.0091,-0.0098, -0.0105, -0.0112, -0.0119,-0.0126, -0.0133, -0.014 , -0.0147});
    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;
    weights.t<double>(3) = 0.;


    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sigm_cross_entropy_loss_grad_test13) {

    NDArray labels('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2,3,1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {0.     ,  0.     ,  0.     ,  0.     , 0.     ,  0.     ,  0.     ,  0.     , 0.     ,  0.     ,  0.     ,  0.     ,
                                   -0.36047, -0.38924, -0.41801, -0.44679,-0.47556, -0.50435, -0.53314, -0.56193,-0.59072, -0.61953, -0.64833, -0.67715});
    NDArray dLdwExp('c', {2,3,1}, {0.22882, 0.02428,-0.4768 ,-1.27447,-2.36878,-3.75981,});
    NDArray dLdlExp('c', {2,3,4}, {-0.     , -0.     ,  0.     ,  0.     , 0.     ,  0.     ,  0.     ,  0.     , 0.     ,  0.     ,  0.     ,  0.,
                                    -0.01167, -0.01283, -0.014  , -0.01517,-0.01633, -0.0175 , -0.01867, -0.01983,-0.021  , -0.02217, -0.02333, -0.0245});
    logits.linspace(-0.08, 0.04);
    labels.linspace(1);
    weights.assign(0.5);
    weights.t<double>(0) = 0.;
    weights.t<double>(1) = 0.;
    weights.t<double>(2) = 0.;

    nd4j::ops::sigm_cross_entropy_loss_grad op;
    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));
    ASSERT_TRUE(dLdlExp.isSameShape(dLdl));
    ASSERT_TRUE(dLdlExp.equalsTo(dLdl));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_4) {

    NDArray x = NDArrayFactory::create<float>('c', {2,3,4});
    NDArray y = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp = NDArrayFactory::create<float>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(1);
    y.linspace(1);
    exp.linspace(2,2);
    nd4j::ops::add op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_5) {

    NDArray x = NDArrayFactory::create<float>('c', {2,3,4});
    NDArray y = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp = NDArrayFactory::create<float>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(2, 2);
    y.linspace(1);
    exp.linspace(1);
    nd4j::ops::subtract op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

///////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, BFloat16_Test_6) {

    NDArray x = NDArrayFactory::create<bfloat16>('c', {2,3,4});
    NDArray y = NDArrayFactory::create<double>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);
    NDArray exp = NDArrayFactory::create<bfloat16>('c', {2,3,4});//('c', {2,3,4}, nd4j::DataType::BFLOAT16);

    x.linspace(2, 2);
    y.linspace(1);
    exp.linspace(1);
    nd4j::ops::subtract op;
    auto results = op.execute({&x, &y}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto res = results->at(0);
    ASSERT_TRUE(res->equalsTo(exp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test1) {

    NDArray labels('c', {2,4}, {0,0,1,0, 0,1,0,0}, nd4j::DataType::INT32);
    NDArray logits('c', {2,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,4}, {0.1176,  0.1224, -0.3726,  0.1326, 0.1176, -0.3776,  0.1274,  0.1326});
    NDArray dLdwExp('c', {2}, {1.36729, 1.40729});

    logits.linspace(-0.08, 0.04);
    weights.assign(0.5);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test2) {

    NDArray labels('c', {4}, {0,0,1,0}, nd4j::DataType::INT32);
    NDArray logits('c', {4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {4}, {0.125,  0.125, -0.375,  0.125});
    NDArray dLdwExp('c', {1}, {1.38629});

    logits = 2.;
    weights.assign(0.5);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test3) {

    NDArray labels('c', {4}, {0,0,1,0}, nd4j::DataType::INT32);
    NDArray logits('c', {4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {}, {0}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {4}, {0.125,  0.125, -0.375,  0.125});
    NDArray dLdwExp('c', {}, {1.38629});

    logits = 2.;
    weights.assign(0.5);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test4) {

    NDArray labels('c', {4}, {0,0,1,0}, nd4j::DataType::INT32);
    NDArray logits('c', {4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {}, {0}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {4}, {0.23521,  0.2448 , -0.7452 ,  0.26519});
    NDArray dLdwExp('c', {}, {0.});

    logits.linspace(-0.08, 0.04);
    weights = 0.5;

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test5) {

    NDArray labels('c', {4}, {0,0,1,0}, nd4j::DataType::INT32);
    NDArray logits('c', {4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {4}, {0.1176,  0.1224, -0.3726,  0.1326});
    NDArray dLdwExp('c', {1}, {1.36729});

    logits.linspace(-0.08, 0.04);
    weights = 0.5;

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test6) {

    NDArray labels('c', {2,4}, {0,0,1,0, 0,1,0,0}, nd4j::DataType::INT32);
    NDArray logits('c', {2,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {2}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,4}, {0.0801,  0.0849, -0.2601,  0.0951, 0.0801, -0.2651,  0.0899,  0.0951});
    NDArray dLdwExp('c', {2}, {-0.014000, 0.014000});

    logits.linspace(-0.08, 0.04);
    weights.assign(0.5);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.3}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test7) {

    NDArray labels('c', {2,3,4}, {1,0,0,0, 0,1,0,0, 0,0,1,0, 0,0,0,1, 1,0,0,0, 0,1,0,0}, nd4j::DataType::INT32);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,3}, {0.5, 0., 1.5});

    NDArray dLdpExp('c', {2,3,4}, {-0.0956 , 0.0306 , 0.03185, 0.03315, 0.,-0., 0., 0., 0.0882 , 0.0918 ,-0.27945, 0.09945,
                                   0.0294 , 0.0306 , 0.03185,-0.09185,-0., 0., 0., 0., 0.0882 ,-0.2832 , 0.09555, 0.09945});
    NDArray dLdwExp('c', {1,3}, {0.69365, 0.71365, 0.69365});

    logits.linspace(-0.08, 0.04);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {3});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmax_cross_entropy_loss_grad_test8) {

    NDArray labels('c', {2,3,4,5}, {1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,
                                    0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,
                                    0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0}, nd4j::DataType::INT32);

    NDArray logits('c', {2,3,4,5}, nd4j::DataType::DOUBLE);
    NDArray weights('c', {1,1,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4,5}, {-0.03399, 0.00799, 0.00832, 0.00866, 0.00901, 0.00768,-0.03367, 0.00832, 0.00866, 0.00901, 0.00768, 0.00799,-0.03335,
                                    0.00866, 0.00901, 0.00768, 0.00799, 0.00832,-0.03301, 0.00901, 0.00768, 0.00799, 0.00832, 0.00866,-0.03265,-0.03399,
                                    0.00799, 0.00832, 0.00866, 0.00901, 0.00768,-0.03367, 0.00832, 0.00866, 0.00901, 0.00768, 0.00799,-0.03335, 0.00866,
                                    0.00901, 0.00768, 0.00799, 0.00832,-0.03301, 0.00901, 0.00768, 0.00799, 0.00832, 0.00866,-0.03265,-0.03399, 0.00799,
                                    0.00832, 0.00866, 0.00901, 0.00768,-0.03367, 0.00832, 0.00866, 0.00901, 0.00768, 0.00799,-0.03335, 0.00866, 0.00901,
                                    0.00768, 0.00799, 0.00832,-0.03301, 0.00901, 0.00768, 0.00799, 0.00832, 0.00866,-0.03265,-0.03399, 0.00799, 0.00832,
                                    0.00866, 0.00901, 0.00768,-0.03367, 0.00832, 0.00866, 0.00901, 0.00768, 0.00799,-0.03335, 0.00866, 0.00901, 0.00768,
                                    0.00799, 0.00832,-0.03301, 0.00901, 0.00768, 0.00799, 0.00832, 0.00866,-0.03265,-0.03399, 0.00799, 0.00832, 0.00866,
                                    0.00901, 0.00768,-0.03367, 0.00832, 0.00866, 0.00901, 0.00768, 0.00799,-0.03335, 0.00866, 0.00901, 0.00768, 0.00799, 0.00832,-0.03301, 0.00901});

    NDArray dLdwExp('c', {1,1,4}, {0.005,  0.00167, -0.00167, -0.005});
    logits.linspace(-0.08, 0.04);
    weights.assign(0.5);

    nd4j::ops::softmax_cross_entropy_loss_grad op;

    auto results = op.execute({&logits, &weights, &labels}, {0.}, {2});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);
    auto *dLdw = results->at(1);
    auto *dLdl = results->at(2);

    // dLdp->printIndexedBuffer();

    // ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    // ASSERT_TRUE(dLdpExp.equalsTo(dLdp));
    ASSERT_TRUE(dLdwExp.isSameShape(dLdw));
    ASSERT_TRUE(dLdwExp.equalsTo(dLdw));

    delete results;
}

////////////////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, SafeDivideMixed_Test1) {

    NDArray labels('c', {2, 3}, {1.0, 2.0, 3.0, -1.0, 2.0, 1.0});
    auto sumDiff = labels.reduceAlongDims(reduce::Sum, {1}, true);

    NDArray numOfNonZero(sumDiff.getShapeInfo(), nd4j::DataType::INT64, false);
    numOfNonZero.assign(1);
    sumDiff.applyPairwiseTransform(pairwise::SafeDivide, &numOfNonZero, &sumDiff, nullptr);
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test1) {

    NDArray labels('c', {2,3,4}, {1,0,0,0, 0,1,0,0, 0,0,1,0, 0,0,0,1, 1,0,0,0, 0,1,0,0});
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.76479, 0.2448, 0.2548, 0.26519, 0.23521,-0.7552, 0.2548, 0.26519, 0.23521, 0.2448,-0.7452, 0.26519,
                                   0.23521, 0.2448, 0.2548,-0.73481,-0.76479, 0.2448, 0.2548, 0.26519, 0.23521,-0.7552, 0.2548, 0.26519});
    logits.linspace(-0.08, 0.04);

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test2) {

    NDArray labels('c', {2,3,4}, {1,0,0,0, 0,1,0,1, 0,0,1,0, 0,0,0,1, 1,0,1,0, 0,1,0,0});
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.71836,  0.28164,  0.28164,  0.28164, 0.33051, -0.66949,  0.33051, -0.66949, 0.38785,  0.38785, -0.61215,  0.38785,
                                    0.28164,  0.28164,  0.28164, -0.71836,-0.66949,  0.33051, -0.66949,  0.33051, 0.38785, -0.61215,  0.38785,  0.38785});
    logits.linspace(-0.08, 0.04);

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test3) {

    NDArray labels('c', {2,3}, {1,0,0, 0,1,1});
    NDArray logits('c', {2,3}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3}, {-0.52996,  0.47004,  0.47004, 0.52996, -0.47004, -0.47004});
    logits.linspace(-0.08, 0.04);

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test4) {

    NDArray labels('c', {2,1}, {1,1});
    NDArray logits('c', {2,1}, {-0.04, 0.04});

    NDArray dLdpExp('c', {2,1}, {0., 0.});

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {1});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test5) {

    NDArray labels('c', {2,1}, {1,0});
    NDArray logits('c', {2,1}, {-0.04, 0.04});

    NDArray dLdpExp('c', {2,1}, {-0.51999, 0.51999});

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test6) {

    NDArray labels('c', {1,2}, {1,1});
    NDArray logits('c', {1,2}, {-0.04, 0.04});

    NDArray dLdpExp('c', {1,2}, {0, 0});

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test7) {

    NDArray labels('c', {2}, {0,1});
    NDArray logits('c', {2}, {-0.04, 0.04});

    NDArray dLdpExp('c', {2}, {0.48001, -0.48001});

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, softmaxCrossEntropyWithLogits_grad_test8) {

    NDArray labels('c', {1}, {1});
    NDArray logits('c', {1}, {0.04});

    NDArray dLdpExp('c', {1}, {0});

    nd4j::ops::softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&logits, &labels}, {}, {0});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, Multiply_BP_Test1) {

    NDArray x('c', {3,4,5}, nd4j::DataType::DOUBLE);
    NDArray y('c', {1,1,1}, nd4j::DataType::DOUBLE);

    NDArray dLdp('c', {3,4,5}, nd4j::DataType::DOUBLE);
    NDArray dLdpExp('c', {3,4,5}, nd4j::DataType::DOUBLE);

    x.assign(1.0);//linspace(0.1, 0.1);
    y.assign(1.0);
    dLdp.assign(1.0);
    dLdpExp.assign(1.0);
    nd4j::ops::multiply_bp op;

    auto results = op.execute({&x, &y, &dLdp}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdo = results->at(0);
    ASSERT_TRUE(dLdpExp.isSameShape(dLdo));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdo));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sparseSoftmaxCrossEntropyWithLogits_grad_test1) {

    NDArray labels('c', {2}, {2,1}, nd4j::DataType::INT64);
    NDArray logits('c', {2,3}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3}, {0.30061,  0.33222, -0.63283, 0.30061, -0.66778,  0.36717});

    logits.linspace(0.1, 0.1);

    nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&labels, &logits}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sparseSoftmaxCrossEntropyWithLogits_grad_test2) {

    NDArray labels('c', {2}, {0,1}, nd4j::DataType::INT64);
    NDArray logits('c', {2,3}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3}, {-0.69939,  0.33222,  0.36717, 0.30061, -0.66778,  0.36717});

    logits.linspace(-0.1, 0.1);

    nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&labels, &logits}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sparseSoftmaxCrossEntropyWithLogits_grad_test3) {

    NDArray labels('c', {}, {1}, nd4j::DataType::INT64);
    NDArray logits('c', {2}, {-0.2, 0.3});

    NDArray dLdpExp('c', {2}, {0.37754, -0.37754});

    nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&labels, &logits}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sparseSoftmaxCrossEntropyWithLogits_grad_test4) {

    NDArray labels('c', {2,3}, {0,1,1, 3,3,2}, nd4j::DataType::INT64);
    NDArray logits('c', {2,3,4}, nd4j::DataType::DOUBLE);

    NDArray dLdpExp('c', {2,3,4}, {-0.78616,  0.23633,  0.26118,  0.28865, 0.21384, -0.76367,  0.26118,  0.28865, 0.21384, -0.76367,  0.26118,  0.28865,
                                  0.21384,  0.23633,  0.26118, -0.71135, 0.21384,  0.23633,  0.26118, -0.71135, 0.21384,  0.23633, -0.73882,  0.28865});
    logits.linspace(-0.5, 0.1);

    nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&labels, &logits}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}

/////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests11, sparseSoftmaxCrossEntropyWithLogits_grad_test5) {

    NDArray labels('c', {1,1}, {0}, nd4j::DataType::INT64);
    NDArray logits('c', {1,1,2}, {-0.3,0.2});

    NDArray dLdpExp('c', {1,1,2}, {-0.62246,  0.62246});

    nd4j::ops::sparse_softmax_cross_entropy_loss_with_logits_grad op;

    auto results = op.execute({&labels, &logits}, {}, {});

    ASSERT_EQ(ND4J_STATUS_OK, results->status());

    auto *dLdp = results->at(0);

    ASSERT_TRUE(dLdpExp.isSameShape(dLdp));
    ASSERT_TRUE(dLdpExp.equalsTo(dLdp));

    delete results;
}