cavis/libnd4j/tests_cpu/layers_tests/DeclarableOpsTests14.cpp
raver119 24e43e9856
[WIP] build time improvements (#106)
* fix pad javadoc and @see links. (#72)

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* [WIP] More fixes (#73)

* special tests for ConstantTadHelper/ConstantShapeHelper

Signed-off-by: raver119 <raver119@gmail.com>

* release methods for data buffers

Signed-off-by: raver119 <raver119@gmail.com>

* delete temporary buffer Java side

Signed-off-by: raver119 <raver119@gmail.com>

* delete temporary buffer Java side

Signed-off-by: raver119 <raver119@gmail.com>

* delete temporary TadPack C++/Java side (#74)

Signed-off-by: raver119 <raver119@gmail.com>

* Zoo model TF import test updates (#75)

* argLine fix, update compression_gru comment

* updated comment for xception

* undid but commented argLine change

* updated xlnet comment

* copyright headers

* - new NDArray methods like()/ulike() (#77)

- fix for depthwise_conv2d_bp + special test

Signed-off-by: raver119 <raver119@gmail.com>

* upsampling2d fix CUDA

Signed-off-by: raver119 <raver119@gmail.com>

* DL4J trace logging (#79)

* MLN/CG trace logging for debugging

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Tiny tweak

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* strided_slice_bp shape fn leak fix

Signed-off-by: raver119 <raver119@gmail.com>

* SameDiff fixes and naming (#78)

* remove SDVariable inplace methods

* import methods

* npe fix in OpVal

* removed SameDiff inplace ops from tests

* Naming updates, moved to centralized methods in SameDiff, should use op_#:# for everything

* quick fixes

* javadoc

* SDVariable eval with placeholders

* use regex match

* better matching

* fix javadoc. (#76)

* fix javadoc.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* replace most @see with @link s.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* 4 additional tests

Signed-off-by: raver119 <raver119@gmail.com>

* Various DL4J/ND4J fixes (#81)

* #7954 Force refresh of UI when switching tabs on overview page

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8017 Concurrent modification exception (synchronize) fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8033 Don't initialize updater in middle of writing memory crash dump

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8208 Fix shape checks for ND4J int[] creator methods

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #6385 #7992 Keras import naming fixes + cleanup

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8016 Upsampling3D - add NDHWC format support

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Refactor NativeOps.h to export C functions

* Actually export functions from NativeOps.h

* Adapt the Java wrappers in ND4J generated with JavaCPP

* Create C wrappers for some of the C++ classes currently used by ND4J

* remove duplicate code in createBufferDetached. (#83)

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* Keras model import - updater lr fix (#84)

* Keras model import - updater lr fix

Signed-off-by: eraly <susan.eraly@gmail.com>

* Keras model import - updater lr fix, cleanup

Signed-off-by: eraly <susan.eraly@gmail.com>

* Fix functions of OpaqueVariablesSet

* SameDiff Convolution Config validation, better output methods (#82)

* Conv Config validation & tests

Signed-off-by: Ryan Nett <rnett@skymind.io>

* stackOutputs utility method

Signed-off-by: Ryan Nett <rnett@skymind.io>

* use constructor for validation, support negative kernel sizes (infered from weights)

Signed-off-by: Ryan Nett <rnett@skymind.io>

* better output methods

Signed-off-by: Ryan Nett <rnett@skymind.io>

* move output to be with fit and evaluate

Signed-off-by: Ryan Nett <rnett@skymind.io>

* fixes

Signed-off-by: Ryan Nett <rnett@skymind.io>

* more fixes

Signed-off-by: Ryan Nett <rnett@skymind.io>

* refactor duplicate code from pad methods. (#86)

* refactor duplicate code from pad methods.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* replace switch with if.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* Various ND4J/DL4J fixes and improvements (#87)

* Reshape and reallocate - small fixes

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Reshape and reallocate - small fixes

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #6488 ElementWiseVertex broadcast support

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Constructors and broadcast supported it Transforms.max/min

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8054 ElementWiseVertex now supports broadcast inputs

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8057 Nd4j.create overload dtype fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #7551 ND4J Shape validation fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* [WIP] Numpy boolean import (#91)

* numpy bool type

Signed-off-by: raver119 <raver119@gmail.com>

* numpy bool java side

Signed-off-by: raver119 <raver119@gmail.com>

* remove create method with unused parameter. (#89)

* remove create method with unused parameter.

* removed more unused methods.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* removing more unused code.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* last removal of unused code.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* remove createSparse methods. (#92)

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* Various ND4J/DL4J fixes (#90)

* Deprecate Old*Op instances

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8063 #8054 Broadcast exceptions + cleanup inplace ops

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Small fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* Remove bad test condition

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #7993 Fix shape function issue in crop_and_resize op

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* DL4J SameDiff lambda layer fix

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8029 Fix for pnorm backprop math

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8038 Fix Op profiler NaN/Inf triggering + add tests (#93)

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* createUninitializedDetached refactoring. (#94)

* wip

* update interface, add null implementations.

* Breaking one test in a weird way.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* createUninitializedDetached refactored.

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* cuda build fix for issues introduced by recent refactoring

Signed-off-by: raver119 <raver119@gmail.com>

* [WIP] More of CUDA (#95)

* initial commit

Signed-off-by: raver119 <raver119@gmail.com>

* Implementation of hashcode cuda helper. Working edition.

* Fixed parallel test input arangements.

* Fixed tests for hashcode op.

* Fixed shape calculation for image:crop_and_resize op and test.

* NativeOps tests. Initial test suite.

* Added tests for indexReduce methods.

* Added test on execBroadcast with NDArray as dimensions.

* Added test on execBroadcastBool with NDArray as dimensions.

* Added tests on execPairwiseTransform and execPairwiseTransofrmBool.

* Added tests for execReduce with scalar results.

* Added reduce tests for non-empty dims array.

* Added tests for reduce3.

* Added tests for execScalar.

* Added tests for execSummaryStats.

* - provide cpu/cuda code for batch_to_space
- testing it

Signed-off-by: Yurii <yurii@skymind.io>

* - remove old test for batch_to_space (had wrong format and numbers were not checked)

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed complilation errors with test.

* Added test for execTransformFloat.

* Added test for execTransformSame.

* Added test for execTransformBool.

* Added test for execTransformStrict.

* Added tests for execScalar/execScalarBool with TADs.

* Added test for flatten.

* - provide cpu/cuda code for space_to_Batch operaion

Signed-off-by: Yurii <yurii@skymind.io>

* Added test for concat.

* comment unnecessary stuff in s_t_b

Signed-off-by: Yurii <yurii@skymind.io>

* Added test for specialConcat.

* Added tests for memcpy/set routines.

* Fixed pullRow cuda test.

* Added pullRow test.

* Added average test.

* - correct typo in NDArray::applyPairwiseTransform(nd4j::pairwise::BoolOps op...)

Signed-off-by: Yurii <yurii@skymind.io>

* - debugging and fixing cuda tests in JavaInteropTests file

Signed-off-by: Yurii <yurii@skymind.io>

* - correct some tests

Signed-off-by: Yurii <yurii@skymind.io>

* Added test for shuffle.

* Fixed ops declarations.

* Restored omp and added shuffle test.

* Added convertTypes test.

* Added tests for execRandom. Eliminated usage of RandomBuffer with NativeOps.

* Added sort tests.

* Added tests for execCustomOp.

* - further debuging and fixing tests terminated with crash

Signed-off-by: Yurii <yurii@skymind.io>

* Added tests for calculateOutputShapes.

* Addded Benchmarks test.

* Commented benchmark tests.

* change assertion

Signed-off-by: raver119 <raver119@gmail.com>

* Added tests for apply_sgd op. Added cpu helper for that op.

* Implement cuda helper for aplly_sgd op. Fixed tests for NativeOps.

* Added test for assign broadcastable.

* Added tests for assign_bp op.

* Added tests for axpy op.

* - assign/execScalar/execTransformAny signature change
- minor test fix

Signed-off-by: raver119 <raver119@gmail.com>

* Fixed axpy op.

* meh

Signed-off-by: raver119 <raver119@gmail.com>

* - fix tests for nativeOps::concat

Signed-off-by: Yurii <yurii@skymind.io>

* sequential transform/scalar

Signed-off-by: raver119 <raver119@gmail.com>

* allow nested parallelism

Signed-off-by: raver119 <raver119@gmail.com>

* assign_bp leak fix

Signed-off-by: raver119 <raver119@gmail.com>

* block setRNG fix

Signed-off-by: raver119 <raver119@gmail.com>

* enable parallelism by default

Signed-off-by: raver119 <raver119@gmail.com>

* enable nested parallelism by default

Signed-off-by: raver119 <raver119@gmail.com>

* Added cuda implementation for row_count helper.

* Added implementation for tnse gains op helper.

* - take into account possible situations when input arrays are empty in reduce_ cuda stuff

Signed-off-by: Yurii <yurii@skymind.io>

* Implemented tsne/edge_forces op cuda-based helper. Parallelized cpu-based helper for edge_forces.

* Added kernel for tsne/symmetrized op heleper.

* Implementation of tsne/symmetrized op cuda helper. Working edition.

* Eliminated waste printfs.

* Added test for broadcastgradientargs op.

* host-only fallback for empty reduce float

Signed-off-by: raver119 <raver119@gmail.com>

* - some tests fixes

Signed-off-by: Yurii <yurii@skymind.io>

* - correct the rest of reduce_ stuff

Signed-off-by: Yurii <yurii@skymind.io>

* - further correction of reduce_ stuff

Signed-off-by: Yurii <yurii@skymind.io>

* Added test for Cbow op. Also added cuda implementation for cbow helpers.

* - improve code of stack operation for scalar case

Signed-off-by: Yurii <yurii@skymind.io>

* - provide cuda kernel for gatherND operation

Signed-off-by: Yurii <yurii@skymind.io>

* Implementation of cbow helpers with cuda kernels.

* minor tests tweaks

Signed-off-by: raver119 <raver119@gmail.com>

* minor tests tweaks

Signed-off-by: raver119 <raver119@gmail.com>

* - further correction of cuda stuff

Signed-off-by: Yurii <yurii@skymind.io>

* Implementatation of cbow op helper with cuda kernels. Working edition.

* Skip random testing for cudablas case.

* lstmBlockCell context fix

Signed-off-by: raver119 <raver119@gmail.com>

* Added tests for ELU and ELU_BP ops.

* Added tests for eq_scalar, gt_scalar, gte_scalar and lte_scalar ops.

* Added tests for neq_scalar.

* Added test for noop.

* - further work on clipbynorm_bp

Signed-off-by: Yurii <yurii@skymind.io>

* - get rid of concat op call, use instead direct concat helper call

Signed-off-by: Yurii <yurii@skymind.io>

* lstmBlockCell context fix

Signed-off-by: raver119 <raver119@gmail.com>

* Added tests for lrelu and lrelu_bp.

* Added tests for selu and selu_bp.

* Fixed lrelu derivative helpers.

* - some corrections in lstm

Signed-off-by: Yurii <yurii@skymind.io>

* operator * result shape fix

Signed-off-by: raver119 <raver119@gmail.com>

* - correct typo in lstmCell

Signed-off-by: Yurii <yurii@skymind.io>

* few tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* CUDA inverse broadcast bool fix

Signed-off-by: raver119 <raver119@gmail.com>

* disable MMAP test for CUDA

Signed-off-by: raver119 <raver119@gmail.com>

* BooleanOp syncToDevice

Signed-off-by: raver119 <raver119@gmail.com>

* meh

Signed-off-by: raver119 <raver119@gmail.com>

* additional data types for im2col/col2im

Signed-off-by: raver119 <raver119@gmail.com>

* Added test for firas_sparse op.

* one more RandomBuffer test excluded

Signed-off-by: raver119 <raver119@gmail.com>

* Added tests for flatten op.

* Added test for Floor op.

* bunch of tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* mmulDot tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* more tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* Implemented floordiv_bp op and tests.

* Fixed scalar case with cuda implementation for bds.

* - work on cuda kernel for clip_by_norm backprop op is completed

Signed-off-by: Yurii <yurii@skymind.io>

* Eliminate cbow crach.

* more tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* more tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* Eliminated abortion with batched nlp test.

* more tests fixed

Signed-off-by: raver119 <raver119@gmail.com>

* Fixed shared flag initializing.

* disabled bunch of cpu workspaces tests

Signed-off-by: raver119 <raver119@gmail.com>

* scalar operators fix: missing registerSpecialUse call

Signed-off-by: raver119 <raver119@gmail.com>

* Fixed logdet for cuda and tests.

* - correct clipBynorm_bp

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed crop_and_resize shape datatype.

* - correct some mmul tests

Signed-off-by: Yurii <yurii@skymind.io>

* build fix

Signed-off-by: raver119 <raver119@gmail.com>

* exclude two methods for JNI

Signed-off-by: raver119 <raver119@gmail.com>

* exclude two methods for JNI

Signed-off-by: raver119 <raver119@gmail.com>

* exclude two methods for JNI (#97)

Signed-off-by: raver119 <raver119@gmail.com>

* temporary stack fix

Signed-off-by: raver119 <raver119@gmail.com>

* couple of legacy groups reorganized into separate compialtion units

Signed-off-by: raver119 <raver119@gmail.com>

* wrong include

Signed-off-by: raver119 <raver119@gmail.com>

* wrong include

Signed-off-by: raver119 <raver119@gmail.com>

* ReductionLoops_float split

Signed-off-by: raver119 <raver119@gmail.com>

* maximum

Signed-off-by: raver119 <raver119@gmail.com>

* some more rearrangements

Signed-off-by: raver119 <raver119@gmail.com>

* spare ifdef

Signed-off-by: raver119 <raver119@gmail.com>

* mirror pad

Signed-off-by: raver119 <raver119@gmail.com>

* - reduce_float split
- mcmodel

Signed-off-by: raver119 <raver119@gmail.com>

* bad include fix

Signed-off-by: raver119 <raver119@gmail.com>

* norelax

Signed-off-by: raver119 <raver119@gmail.com>

* norelax

Signed-off-by: raver119 <raver119@gmail.com>

* norelax

Signed-off-by: raver119 <raver119@gmail.com>

* norelax

Signed-off-by: raver119 <raver119@gmail.com>

* norelax

Signed-off-by: raver119 <raver119@gmail.com>

* norelax gone

Signed-off-by: raver119 <raver119@gmail.com>

* get back sm

Signed-off-by: raver119 <raver119@gmail.com>

* fix couple of tests for msvc

Signed-off-by: raver119 <raver119@gmail.com>

* fix couple of tests for msvc

Signed-off-by: raver119 <raver119@gmail.com>

* compress-all

Signed-off-by: raver119 <raver119@gmail.com>

* reduced arch list

Signed-off-by: raver119 <raver119@gmail.com>

* compress-all

Signed-off-by: raver119 <raver119@gmail.com>

* reduced arch list

Signed-off-by: raver119 <raver119@gmail.com>

* all compute capabilities option for tests

Signed-off-by: raver119 <raver119@gmail.com>
2019-08-07 17:49:13 +03:00

453 lines
14 KiB
C++

/*******************************************************************************
* 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 DeclarableOpsTests14 : public testing::Test {
public:
DeclarableOpsTests14() {
printf("\n");
fflush(stdout);
}
};
TEST_F(DeclarableOpsTests14, Test_Validation_Edge_1) {
auto x = NDArrayFactory::create<int>('c', {2}, {2, 2});
auto exp = NDArrayFactory::create('c', {2, 2}, Environment::getInstance()->defaultFloatDataType());
exp.assign(4.0f);
nd4j::ops::fill op;
auto result = op.execute({&x}, {4.0f},{}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(exp, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, Test_Reshape_CF_1) {
auto x = NDArrayFactory::create<double>('f', {2, 3}, {1.0, 4.0, 2.0, 5.0, 3.0, 6.0});
auto e = NDArrayFactory::create<double>('f', {3, 2}, {1.0, 3.0, 5.0, 2.0, 4.0, 6.0});
x.printShapeInfo("x shape");
x.printBuffer("x buffr");
x.printIndexedBuffer("x indxd");
auto r = x.reshape('c', {3, 2});
r.printIndexedBuffer("r pre-s");
r.streamline('f');
nd4j::ops::reshape op;
auto result = op.execute({&x}, {}, {3, 2}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
delete result;
}
TEST_F(DeclarableOpsTests14, Test_Inf_Comparison_1) {
auto x = NDArrayFactory::create<double>('c', {5}, {1, 2, 3, std::numeric_limits<double>::infinity(), 5});
auto y = NDArrayFactory::create<double>('c', {5}, {1, 2, 3, std::numeric_limits<double>::infinity(), 5});
ASSERT_EQ(x, y);
}
TEST_F(DeclarableOpsTests14, Test_Inf_Comparison_2) {
auto x = NDArrayFactory::create<double>('c', {5}, {1, 2, 3, std::numeric_limits<double>::infinity(), 5});
auto y = NDArrayFactory::create<double>('c', {5}, {1, 2, 3, -std::numeric_limits<double>::infinity(), 5});
ASSERT_NE(x, y);
}
TEST_F(DeclarableOpsTests14, Multiply_test) {
for(int k=2;k<10;k++){
nd4j_printf("k=%d\n", k);
NDArray x = NDArrayFactory::create<double>('c', {k, 1});
NDArray y = NDArrayFactory::create<double>('c', {k});
NDArray e = NDArrayFactory::create<double>('c', {k, k});
x.assign(1.0);
y.assign(1.0);
e.assign(1.0);
nd4j::ops::multiply op;
auto result = op.execute({&x, &y}, {}, {});
auto f = result->at(0);
NDArray r = *f;
ASSERT_EQ(e, r);
ASSERT_EQ(e, *f);
delete result;
}
}
TEST_F(DeclarableOpsTests14, Test_EvalReductionShape_1) {
auto x = NDArrayFactory::create<int>('c', {3}, {5, 3, 4});
auto y = NDArrayFactory::create<int>('c', {1}, {1});
auto e = NDArrayFactory::create<Nd4jLong>('c', {2}, {5, 4});
nd4j::ops::evaluate_reduction_shape op;
auto result = op.execute({&x, &y}, {}, {}, {false, false});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
z->printIndexedBuffer("Reduced shape");
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, Test_EvalReductionShape_2) {
auto x = NDArrayFactory::create<int>('c', {3}, {5, 3, 4});
auto y = NDArrayFactory::create<int>('c', {1}, {1});
auto e = NDArrayFactory::create<Nd4jLong>('c', {3}, {5, 1, 4});
nd4j::ops::evaluate_reduction_shape op;
auto result = op.execute({&x, &y}, {}, {}, {true, false});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, Test_Reduce_Min_Small_0) {
auto x = NDArrayFactory::create<float>('c', {3, 4}, {-999.f, 0.2236f, 0.7973f, 0.0962f, 0.7231f, 0.3381f, -0.7301f, 0.9115f, -0.5094f, 0.9749f, -2.1340f, 0.6023f});
auto z = NDArrayFactory::create<float>('c', {4});
auto e = NDArrayFactory::create<float>('c', {4}, {-999.f, 0.2236f, -2.1340f, 0.0962f});
nd4j::ops::reduce_min op;
op.execute({&x}, {&z}, {}, {0}, {});
//z.printIndexedBuffer("Z");
ASSERT_EQ(e, z);
}
TEST_F(DeclarableOpsTests14, Test_Reduce_Min_Small_1) {
auto x = NDArrayFactory::create<float>('c', {3, 4}, {-999.f, 0.2236f, 0.7973f, 0.0962f, 0.7231f, 0.3381f, -0.7301f, 0.9115f, -0.5094f, 0.9749f, -2.1340f, 0.6023f});
auto z = NDArrayFactory::create<float>('c', {3});
auto e = NDArrayFactory::create<float>('c', {3}, {-999.f, -0.7301f, -2.1340f});
nd4j::ops::reduce_min op;
op.execute({&x}, {&z}, {}, {1}, {});
//z.printIndexedBuffer("Z");
ASSERT_EQ(e, z);
}
TEST_F(DeclarableOpsTests14, Test_Diag_Zeros_1) {
auto x = NDArrayFactory::create<double>('c', {2}, {1, 2});
auto z = NDArrayFactory::create<double>('c', {2, 2}, {-119, -119, -119, -119});
auto exp = NDArrayFactory::create<double>('c', {2, 2}, {1, 0, 0, 2});
nd4j::ops::diag op;
auto status = op.execute({&x}, {&z}, {}, {}, {});
ASSERT_EQ(Status::OK(), status);
ASSERT_EQ(exp, z);
}
TEST_F(DeclarableOpsTests14, Test_scalar_broadcast_1) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {5, 10});
auto e = NDArrayFactory::create<float>('c', {5, 10});
e.assign(1.0);
nd4j::ops::add op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
}
TEST_F(DeclarableOpsTests14, Test_scalar_broadcast_2) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {5, 10});
auto e = NDArrayFactory::create<float>('c', {5, 10});
y.assign(2.0f);
e.assign(-1.0f);
nd4j::ops::subtract op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_fill_1) {
auto x = NDArrayFactory::empty<int>();
auto y = NDArrayFactory::create<int>(1);
nd4j::ops::fill op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(y, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, test_lstmBlockCell_1) {
auto a = NDArrayFactory::create<double>('c', {1, 5}, {0.7787856f, 0.80119777f, 0.72437465f, 0.23089433f, 0.72714126f});
auto b = NDArrayFactory::create<double>('c', {1, 3});
auto c = NDArrayFactory::create<double>('c', {1, 3});
auto d = NDArrayFactory::create<double>('c', {8, 12}, {-0.15320599,-0.120416045,0.33126968,0.13921785,-0.32313538,-0.43956736,0.4756174,0.4335605,-0.5450856,-0.3943429,-0.28687626,0.068032146,-0.2793799,0.17298919,-0.36553562,-0.097853184,-0.2544747,-0.39872527,-0.14556861,-0.31479517,0.2559092,0.47166896,-0.31330687,0.47313118,0.5134543,-0.4678212,-0.12853557,0.26142156,0.43472284,-0.42842552,-0.1895876,0.538689,0.508651,-0.020272732,0.112327516,0.2704304,-0.046546757,0.32570732,-0.15148133,-0.19145513,0.18631572,-0.024152994,0.41603214,-0.3421499,0.0106860995,-0.2966229,-0.36713937,0.25841123,0.0843398,0.49082482,0.10800403,0.1874243,-0.26379472,-0.22531849,0.24924624,0.23119557,0.49940765,-0.051413506,0.20315129,-0.41888732,0.44097036,0.40453392,0.013338983,0.23434466,0.23942488,0.47894,-0.19898453,0.09253675,-0.032358468,-0.15213022,-0.3441009,-0.15600958,-0.08235118,0.12165731,-0.4481289,-0.4842423,-0.45797008,-0.4606034,0.08163166,-0.2981107,0.50207126,0.44195646,0.13850057,0.072246075,-0.34388685,0.030900061,0.35821778,0.47900867,0.5094063,0.23683065,0.18020362,-0.1369732,0.015235603,0.2786904,0.07954317,0.12543976});
auto e = NDArrayFactory::create<double>('c', {3});
auto f = NDArrayFactory::create<double>('c', {3});
auto g = NDArrayFactory::create<double>('c', {3});
auto h = NDArrayFactory::create<double>('c', {12});
auto z0 = NDArrayFactory::create<double>('c', {1, 3});
auto z1 = NDArrayFactory::create<double>('c', {1, 3});
auto z2 = NDArrayFactory::create<double>('c', {1, 3});
auto z3 = NDArrayFactory::create<double>('c', {1, 3});
auto z4 = NDArrayFactory::create<double>('c', {1, 3});
auto z5 = NDArrayFactory::create<double>('c', {1, 3});
auto z6 = NDArrayFactory::create<double>('c', {1, 3});
nd4j::ops::lstmBlockCell op;
auto result = op.execute({&a, &b, &c, &d, &e, &f, &g, &h}, {&z0, &z1, &z2, &z3, &z4, &z5, &z6}, {1.0, -1.0}, {0}, {});
ASSERT_EQ(Status::OK(), result);
}
TEST_F(DeclarableOpsTests14, test_empty_stack_1) {
auto x = NDArrayFactory::create<float>('c', {0});
auto e = NDArrayFactory::create<float>('c', {1, 0});
nd4j::ops::stack op;
auto result = op.execute({&x}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
nd4j::ops::reduce_min sumOp;
auto res2 = sumOp.execute({&e}, {1.}, {1});
ASSERT_EQ(res2->status(), Status::OK());
auto out = res2->at(0);
ASSERT_EQ(out->e<float>(0), DataTypeUtils::infOrMax<float>());
delete res2;
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_stack_2) {
auto x = NDArrayFactory::empty<float>();
auto e = NDArrayFactory::create<float>('c', {0});
nd4j::ops::stack op;
auto result = op.execute({&x}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_stack_3) {
auto x = NDArrayFactory::empty<float>();
auto e = NDArrayFactory::create<float>('c', {2, 0});
nd4j::ops::stack op;
auto result = op.execute({&x, &x}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_stack_4) {
auto x = NDArrayFactory::create<float>('c', {0});
auto e = NDArrayFactory::create<float>('c', {2, 0});
nd4j::ops::stack op;
auto result = op.execute({&x, &x}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_reduce_min_1) {
auto e = NDArrayFactory::create<float>('c', {1, 0});
nd4j::ops::reduce_min sumOp;
auto res2 = sumOp.execute({&e}, {1.}, {1});
ASSERT_EQ(res2->status(), Status::OK());
auto out = res2->at(0);
ASSERT_EQ(out->e<float>(0), DataTypeUtils::infOrMax<float>());
delete res2;
}
TEST_F(DeclarableOpsTests14, test_empty_reduce_max_1) {
auto e = NDArrayFactory::create<float>('c', {1, 0});
nd4j::ops::reduce_max sumOp;
auto res2 = sumOp.execute({&e}, {1.}, {1});
ASSERT_EQ(res2->status(), Status::OK());
auto out = res2->at(0);
ASSERT_EQ(out->e<float>(0), -DataTypeUtils::infOrMax<float>());
delete res2;
}
TEST_F(DeclarableOpsTests14, test_empty_reduce_sum_1) {
auto e = NDArrayFactory::create<float>('c', {1, 0});
nd4j::ops::reduce_sum sumOp;
auto res2 = sumOp.execute({&e}, {1.}, {1});
ASSERT_EQ(res2->status(), Status::OK());
auto out = res2->at(0);
ASSERT_EQ(out->e<float>(0), 0.f);
delete res2;
}
TEST_F(DeclarableOpsTests14, test_empty_reduce_mean_1) {
auto e = NDArrayFactory::create<float>('c', {1, 0});
nd4j::ops::reduce_mean sumOp;
auto res2 = sumOp.execute({&e}, {1.}, {1});
ASSERT_EQ(res2->status(), Status::OK());
auto out = res2->at(0);
// out->printShapeInfo("ReduceMean empty shape with keep dims");
// out->printIndexedBuffer("ReduceMean scalar");
ASSERT_TRUE(std::isnan(out->e<float>(0)));
delete res2;
}
TEST_F(DeclarableOpsTests14, Test_StridedSliceZeros_1) {
auto matrix = NDArrayFactory::create<double>('c', {1, 2, 0, 4});
auto b = NDArrayFactory::create<int>('c', {3}, {0, 0, 0});
auto e = NDArrayFactory::create<int>('c', {3}, {2,0,2});
auto s = NDArrayFactory::create<int>('c', {3}, {1,1,1});
auto exp = NDArrayFactory::create<double>('c', {1,0,0,4});
matrix.linspace(1);
nd4j::ops::strided_slice op;
auto result = op.execute({&matrix, &b, &e, &s}, {}, {0, 0, 0, 0, 0});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
delete result;
}
TEST_F(DeclarableOpsTests14, Test_StridedSliceZeros_2) {
auto matrix = NDArrayFactory::create<double>('c', {1, 2, 0, 4});
auto b = NDArrayFactory::create<int>('c', {3}, {0, 0, 0});
auto e = NDArrayFactory::create<int>('c', {3}, {2,0,2});
auto s = NDArrayFactory::create<int>('c', {3}, {1,1,1});
auto exp = NDArrayFactory::create<double>('c', {0,0,4});
matrix.linspace(1);
nd4j::ops::strided_slice op;
auto result = op.execute({&matrix, &b, &e, &s}, {}, {0, 0, 0, 0, 1});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_argmax_1) {
auto x = NDArrayFactory::create<float>('c', {1, 0});
auto y = NDArrayFactory::create<int>(0);
auto e = NDArrayFactory::create<Nd4jLong>('c', {0});
nd4j::ops::argmax op;
//nd4j::ops::reduce_max op;
auto result = op.execute({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
z->printShapeInfo("Z");
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests14, test_empty_argmax_2) {
auto x = NDArrayFactory::create<float>('c', {1, 0});
auto y = NDArrayFactory::create<int>(1);
nd4j::ops::argmax op;
try {
auto result = op.execute({&x, &y}, {&y}, {}, {}, {});
ASSERT_TRUE(false);
} catch (std::exception &e) {
//
}
}
TEST_F(DeclarableOpsTests14, test_empty_tanh_5) {
auto x = NDArrayFactory::create<float>('c', {32, 0});
nd4j::ops::tanh op;
auto result = op.execute({&x}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(x.isSameShape(z));
ASSERT_EQ(x, *z);
delete result;
}