2019-06-06 14:21:15 +02:00
|
|
|
/*******************************************************************************
|
|
|
|
* 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>
|
2020-03-02 10:49:41 +01:00
|
|
|
#include <array/NDArray.h>
|
2019-06-06 14:21:15 +02:00
|
|
|
#include <ops/ops.h>
|
2020-03-02 10:49:41 +01:00
|
|
|
#include <helpers/GradCheck.h>
|
[WIP] multi-device support (#80)
* 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
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* 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>
* launch context reorganization
Signed-off-by: raver119 <raver119@gmail.com>
* LaunchContext reorganization
Signed-off-by: raver119 <raver119@gmail.com>
* per-device LaunchContext
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>
* ContextBuffers as separate entity
Signed-off-by: raver119 <raver119@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
* ContextBuffers as separate entity
Signed-off-by: raver119 <raver119@gmail.com>
* 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>
* ContextBuffers as separate entity
Signed-off-by: raver119 <raver119@gmail.com>
* ContextBuffers as separate entity
Signed-off-by: raver119 <raver119@gmail.com>
* Fix functions of OpaqueVariablesSet
* thread-local buffers/affinity
Signed-off-by: raver119 <raver119@gmail.com>
* thread safety for LaunchContext
Signed-off-by: raver119 <raver119@gmail.com>
* more of thread safety
Signed-off-by: raver119 <raver119@gmail.com>
* one more multi threaded test
Signed-off-by: raver119 <raver119@gmail.com>
* 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>
* round robin affinity test
Signed-off-by: raver119 <raver119@gmail.com>
* get rid of legacy CudaContext methods
Signed-off-by: raver119 <raver119@gmail.com>
* get rid of legacy ContextPool classes/methods
Signed-off-by: raver119 <raver119@gmail.com>
* one legacy test removed
Signed-off-by: raver119 <raver119@gmail.com>
* few more fields rearranged
Signed-off-by: raver119 <raver119@gmail.com>
* OpaqueLaunchContext
Signed-off-by: raver119 <raver119@gmail.com>
* OpaqueLaunchContext++
Signed-off-by: raver119 <raver119@gmail.com>
* more of OpaqueLaunchContext methods
Signed-off-by: raver119 <raver119@gmail.com>
* LaunchContext -> CudaContext
Signed-off-by: raver119 <raver119@gmail.com>
* AffinityManger changes
Signed-off-by: raver119 <raver119@gmail.com>
* AffinityManger changes
Signed-off-by: raver119 <raver119@gmail.com>
* cusolver handles
Signed-off-by: raver119 <raver119@gmail.com>
* typo
Signed-off-by: raver119 <raver119@gmail.com>
* cusolver method
Signed-off-by: raver119 <raver119@gmail.com>
* cusolver handle propagated
Signed-off-by: raver119 <raver119@gmail.com>
* blas/solver handles
Signed-off-by: raver119 <raver119@gmail.com>
* one more test
Signed-off-by: raver119 <raver119@gmail.com>
* legacy concat implementations replaced with new CustomOp
Signed-off-by: raver119 <raver119@gmail.com>
* one more test
Signed-off-by: raver119 <raver119@gmail.com>
* concat now uses way more blocks
Signed-off-by: raver119 <raver119@gmail.com>
* print
Signed-off-by: raver119 <raver119@gmail.com>
* no more triple template mmul
Signed-off-by: raver119 <raver119@gmail.com>
* bunch of kernels have dtypes reconsidered
Signed-off-by: raver119 <raver119@gmail.com>
* bunch of kernels have dtypes reconsidered
Signed-off-by: raver119 <raver119@gmail.com>
* bitonic sort reorganized
Signed-off-by: raver119 <raver119@gmail.com>
* bunch of cpu stuff removed from cuda scope
Signed-off-by: raver119 <raver119@gmail.com>
* bunch of cpu stuff removed from cuda scope
Signed-off-by: raver119 <raver119@gmail.com>
* type conversions moved to generic impl
Signed-off-by: raver119 <raver119@gmail.com>
* cpu data types pass
Signed-off-by: raver119 <raver119@gmail.com>
* non_max_suppression
Signed-off-by: raver119 <raver119@gmail.com>
* sortByValue fix
Signed-off-by: raver119 <raver119@gmail.com>
* ignore all mixed datatype tests for mmul
Signed-off-by: raver119 <raver119@gmail.com>
* special handling of OpProfiler exceptions
Signed-off-by: raver119 <raver119@gmail.com>
* - one failing concat test in cpp
- Nd4j.tile now uses op internally
Signed-off-by: raver119 <raver119@gmail.com>
* get back dtype exception for legacy arrays deserialization
Signed-off-by: raver119 <raver119@gmail.com>
2019-08-14 15:52:34 +02:00
|
|
|
#include <array>
|
2019-06-06 14:21:15 +02:00
|
|
|
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
using namespace sd;
|
2019-06-06 14:21:15 +02:00
|
|
|
|
|
|
|
|
|
|
|
class DeclarableOpsTests15 : public testing::Test {
|
|
|
|
public:
|
|
|
|
|
|
|
|
DeclarableOpsTests15() {
|
|
|
|
printf("\n");
|
|
|
|
fflush(stdout);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_NormalizeMoments_1) {
|
|
|
|
auto d = NDArrayFactory::create<double>('c', {10, 10});
|
|
|
|
auto w = NDArrayFactory::create<double>(10);
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {10});
|
|
|
|
auto y = NDArrayFactory::create<double>('c', {10});
|
|
|
|
|
|
|
|
auto z0 = NDArrayFactory::create<double>('c', {10});
|
|
|
|
auto z1 = NDArrayFactory::create<double>('c', {10});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::normalize_moments op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.execute({&w, &x, &y}, std::vector<NDArray*>{&z0, &z1}, {1e-4}, {}, {});
|
2019-06-06 14:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_Add_1) {
|
|
|
|
auto x = NDArrayFactory::create<int>('c', {5}, {1, 1, 1, 1, 1});
|
|
|
|
auto y = NDArrayFactory::create<int>('c', {5}, {1, 1, 1, 1, 1});
|
|
|
|
auto e = NDArrayFactory::create<int>('c', {5}, {2, 2, 2, 2, 2});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::add op;
|
2019-06-06 14:21:15 +02:00
|
|
|
auto result = op.execute({&x, &y}, {&x}, {}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), result);
|
|
|
|
ASSERT_EQ(e, x);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_Half_assign_1) {
|
|
|
|
auto x = NDArrayFactory::create<float16>('c', {2, 5});
|
|
|
|
int y = 1;
|
|
|
|
x.assign(y);
|
|
|
|
|
|
|
|
ASSERT_EQ(10, x.sumNumber().e<int>(0));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_standarize_1) {
|
2019-12-20 19:11:18 +01:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {5}, {1.f, 1.f, 1.f, 1.f, 1.f});
|
2019-12-20 20:35:39 +01:00
|
|
|
auto e = NDArrayFactory::create<float>('c', {5}, {0.f, 0.f, 0.f, 0.f, 0.f});
|
2019-06-06 14:21:15 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::standardize op;
|
2019-06-06 14:21:15 +02:00
|
|
|
auto result = op.execute({&x}, {&x}, {}, {0}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), result);
|
|
|
|
ASSERT_EQ(e, x);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_standarize_bp_1) {
|
2019-12-05 20:05:33 +01:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {5}, {1.f, 1.f, 1.f, 1.f, 1.f});
|
|
|
|
auto eps = NDArrayFactory::create<float>('c', {5}, {0.f, 0.f, 0.f, 0.f, 0.f});
|
2019-06-06 14:21:15 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::standardize_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x, &eps}, {0});
|
2019-06-06 14:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-09-30 17:24:12 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_1) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {4,4,3});
|
2019-12-03 07:40:45 +01:00
|
|
|
NDArray factor = NDArrayFactory::create<double>(2.);
|
|
|
|
auto e = NDArrayFactory::create<double>('c', {4,4,3}, {-21.5, -20.5, -19.5, -15.5, -14.5, -13.5, -9.5, -8.5, -7.5, -3.5, -2.5, -1.5,
|
|
|
|
2.5, 3.5, 4.5, 8.5, 9.5, 10.5, 14.5, 15.5, 16.5, 20.5, 21.5, 22.5,
|
|
|
|
26.5, 27.5, 28.5, 32.5, 33.5, 34.5, 38.5, 39.5, 40.5, 44.5, 45.5, 46.5,
|
|
|
|
50.5, 51.5, 52.5, 56.5, 57.5, 58.5, 62.5, 63.5, 64.5, 68.5, 69.5, 70.5});
|
|
|
|
|
|
|
|
|
2019-09-30 17:24:12 +02:00
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x, &factor}, {}, {}, {});
|
2019-09-30 17:24:12 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
2019-12-03 07:40:45 +01:00
|
|
|
|
2019-09-30 17:24:12 +02:00
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_2) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 4,4,3});
|
|
|
|
auto e = NDArrayFactory::create<float>('c', {1, 4,4,3}, {
|
2019-11-30 14:02:07 +01:00
|
|
|
-21.5f, -20.5f, -19.5f, -15.5f, -14.5f, -13.5f, -9.5f, -8.5f, -7.5f, -3.5f, -2.5f, -1.5f,
|
|
|
|
2.5f, 3.5f, 4.5f, 8.5f, 9.5f, 10.5f, 14.5f, 15.5f, 16.5f, 20.5f, 21.5f, 22.5f,
|
|
|
|
26.5f, 27.5f, 28.5f, 32.5f, 33.5f, 34.5f, 38.5f, 39.5f, 40.5f, 44.5f, 45.5f, 46.5f,
|
|
|
|
50.5f, 51.5f, 52.5f, 56.5f, 57.5f, 58.5f, 62.5f, 63.5f, 64.5f, 68.5f, 69.5f, 70.5f
|
2019-09-30 17:24:12 +02:00
|
|
|
});
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.});
|
2019-09-30 17:24:12 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printIndexedBuffer("Adjusted Constrast");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-10-01 10:44:27 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_3) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 4,4,3});
|
|
|
|
auto e = NDArrayFactory::create<float>('c', {1, 4,4,3}, {
|
2019-11-30 14:02:07 +01:00
|
|
|
-21.5f, -20.5f, -19.5f, -15.5f, -14.5f, -13.5f, -9.5f, -8.5f, -7.5f, -3.5f, -2.5f, -1.5f,
|
|
|
|
2.5f, 3.5f, 4.5f, 8.5f, 9.5f, 10.5f, 14.5f, 15.5f, 16.5f, 20.5f, 21.5f, 22.5f,
|
|
|
|
26.5f, 27.5f, 28.5f, 32.5f, 33.5f, 34.5f, 38.5f, 39.5f, 40.5f, 44.5f, 45.5f, 46.5f,
|
|
|
|
50.5f, 51.5f, 52.5f, 56.5f, 57.5f, 58.5f, 62.5f, 63.5f, 64.5f, 68.5f, 69.5f, 70.5f
|
2019-10-01 10:44:27 +02:00
|
|
|
});
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast_v2 op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.});
|
2019-10-01 10:44:27 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printIndexedBuffer("Adjusted Constrast");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_4) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {4, 4, 3});
|
|
|
|
auto e = NDArrayFactory::create<double>('c', {4, 4, 3}, {
|
|
|
|
-21.5, -20.5, -19.5, -15.5, -14.5, -13.5, -9.5, -8.5, -7.5, -3.5, -2.5, -1.5,
|
|
|
|
2.5, 3.5, 4.5, 8.5, 9.5, 10.5, 14.5, 15.5, 16.5, 20.5, 21.5, 22.5,
|
|
|
|
26.5, 27.5, 28.5, 32.5, 33.5, 34.5, 38.5, 39.5, 40.5, 44.5, 45.5, 46.5,
|
|
|
|
50.5, 51.5, 52.5, 56.5, 57.5, 58.5, 62.5, 63.5, 64.5, 68.5, 69.5, 70.5
|
|
|
|
});
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast_v2 op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.}, {}, {});
|
2019-10-01 10:44:27 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printIndexedBuffer("Adjusted Constrast");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
2019-12-06 16:58:37 +01:00
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_5) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {1, 3, 4});
|
|
|
|
auto e = NDArrayFactory::create<double>('c', {1, 3, 4}, {
|
|
|
|
-3., -2., -1., 0., 5., 6., 7., 8., 13., 14., 15., 16.
|
|
|
|
});
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast_v2 op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.}, {}, {});
|
2019-12-06 16:58:37 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printIndexedBuffer("Adjusted Constrast");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
|
|
|
* public void testAdjustContrast1() {
|
|
|
|
INDArray in = Nd4j.createFromArray(new float[]{0.7788f,0.8012f,0.7244f,0.2309f,0.7271f,0.1804f,
|
|
|
|
0.5056f,0.8925f,0.5461f,0.9234f,0.0856f,0.7938f,0.6591f,0.5555f,0.1596f,0.3087f,0.1548f,0.4695f,
|
|
|
|
0.9939f,0.6113f,0.6765f,0.1800f,0.6750f,0.2246f,0.0509f,0.4601f,0.8284f,0.2354f,0.9752f,0.8361f,
|
|
|
|
0.2585f,0.4189f,0.7028f,0.7679f,0.5373f,0.7234f,0.2690f,0.0062f,0.0327f,0.0644f,0.8428f,0.7494f,
|
|
|
|
0.0755f,0.6245f,0.3491f,0.5793f,0.5730f,0.1822f,0.6420f,0.9143f,0.3019f,
|
|
|
|
0.3574f,0.1704f,0.8395f,0.5468f,0.0744f,0.9011f,0.6574f,0.4124f,0.2445f,0.4248f,0.5219f,
|
|
|
|
0.6952f,0.4900f,0.2158f,0.9549f,0.1386f,0.1544f,0.5365f,0.0134f,0.4163f,0.1456f,0.4109f,
|
|
|
|
0.2484f, 0.3330f,0.2974f,0.6636f,0.3808f,0.8664f, 0.1896f, 0.7530f, 0.7215f, 0.6612f, 0.7270f,
|
|
|
|
0.5704f,0.2666f,0.7453f,0.0444f,0.3024f,0.4850f,0.7982f,0.0965f,0.7843f,0.5075f,
|
|
|
|
0.0844f,0.8370f,0.6103f,0.4604f,0.6087f, 0.8594f, 0.4599f, 0.6714f, 0.2744f, 0.1981f, 0.4143f,
|
|
|
|
0.7821f,0.3505f,0.5040f,0.1180f,0.8307f,0.1817f,0.8442f,0.5074f,0.4471f,0.5105f,0.6666f,
|
|
|
|
0.2576f,0.2341f,0.6801f,0.2652f,0.5394f,0.4690f,0.6146f,0.1210f,0.2576f,0.0769f,0.4643f,
|
|
|
|
0.1628f,0.2026f,0.3774f,0.0506f,0.3462f,0.5720f,0.0838f,0.4228f,0.0588f,0.5362f,0.4756f,
|
|
|
|
0.2530f,0.1778f,0.0751f,0.8977f,0.3648f,0.3065f,0.4739f,0.7014f,0.4473f,0.5171f,0.1744f,
|
|
|
|
0.3487f,0.7759f,0.9491f,0.2072f,0.2182f,0.6520f,0.3092f,0.9545f,0.1881f,0.9579f,0.1785f,
|
|
|
|
0.9636f,0.4830f,0.6569f,0.3353f,0.9997f,0.5869f,0.5747f,0.0238f,0.2943f,0.5248f,0.5879f,
|
|
|
|
.7266f,0.1965f,0.9167f,0.9726f,0.9206f,0.0519f,0.2997f,0.0039f,0.7652f,0.5498f,
|
|
|
|
0.3794f,0.3791f,0.3528f,0.2873f,0.8082f,0.4732f,0.4399f,0.6606f,0.5991f,0.0034f,0.4874f
|
|
|
|
}).reshape(8,8,3,1);
|
|
|
|
INDArray out = Nd4j.create(DataType.FLOAT, in.shape());
|
|
|
|
INDArray[] res = Nd4j.exec(new AdjustContrast(in, 2.0, out));
|
|
|
|
assertArrayEquals(out.shape(), in.shape());
|
|
|
|
//assertEquals(expected, out);
|
|
|
|
}
|
|
|
|
* */
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_6) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {8,8, 3, 1}, {0.7788f,0.8012f,0.7244f,0.2309f,0.7271f,0.1804f,
|
|
|
|
0.5056f,0.8925f,0.5461f,0.9234f,0.0856f,0.7938f,0.6591f,0.5555f,0.1596f,0.3087f,0.1548f,0.4695f,
|
|
|
|
0.9939f,0.6113f,0.6765f,0.1800f,0.6750f,0.2246f,0.0509f,0.4601f,0.8284f,0.2354f,0.9752f,0.8361f,
|
|
|
|
0.2585f,0.4189f,0.7028f,0.7679f,0.5373f,0.7234f,0.2690f,0.0062f,0.0327f,0.0644f,0.8428f,0.7494f,
|
|
|
|
0.0755f,0.6245f,0.3491f,0.5793f,0.5730f,0.1822f,0.6420f,0.9143f,0.3019f,
|
|
|
|
0.3574f,0.1704f,0.8395f,0.5468f,0.0744f,0.9011f,0.6574f,0.4124f,0.2445f,0.4248f,0.5219f,
|
|
|
|
0.6952f,0.4900f,0.2158f,0.9549f,0.1386f,0.1544f,0.5365f,0.0134f,0.4163f,0.1456f,0.4109f,
|
|
|
|
0.2484f, 0.3330f,0.2974f,0.6636f,0.3808f,0.8664f, 0.1896f, 0.7530f, 0.7215f, 0.6612f, 0.7270f,
|
|
|
|
0.5704f,0.2666f,0.7453f,0.0444f,0.3024f,0.4850f,0.7982f,0.0965f,0.7843f,0.5075f,
|
|
|
|
0.0844f,0.8370f,0.6103f,0.4604f,0.6087f, 0.8594f, 0.4599f, 0.6714f, 0.2744f, 0.1981f, 0.4143f,
|
|
|
|
0.7821f,0.3505f,0.5040f,0.1180f,0.8307f,0.1817f,0.8442f,0.5074f,0.4471f,0.5105f,0.6666f,
|
|
|
|
0.2576f,0.2341f,0.6801f,0.2652f,0.5394f,0.4690f,0.6146f,0.1210f,0.2576f,0.0769f,0.4643f,
|
|
|
|
0.1628f,0.2026f,0.3774f,0.0506f,0.3462f,0.5720f,0.0838f,0.4228f,0.0588f,0.5362f,0.4756f,
|
|
|
|
0.2530f,0.1778f,0.0751f,0.8977f,0.3648f,0.3065f,0.4739f,0.7014f,0.4473f,0.5171f,0.1744f,
|
|
|
|
0.3487f,0.7759f,0.9491f,0.2072f,0.2182f,0.6520f,0.3092f,0.9545f,0.1881f,0.9579f,0.1785f,
|
|
|
|
0.9636f,0.4830f,0.6569f,0.3353f,0.9997f,0.5869f,0.5747f,0.0238f,0.2943f,0.5248f,0.5879f,
|
|
|
|
.7266f,0.1965f,0.9167f,0.9726f,0.9206f,0.0519f,0.2997f,0.0039f,0.7652f,0.5498f,
|
|
|
|
0.3794f,0.3791f,0.3528f,0.2873f,0.8082f,0.4732f,0.4399f,0.6606f,0.5991f,0.0034f,0.4874f});
|
|
|
|
auto e = NDArrayFactory::create<float>('c', {8, 8, 3, 1}, {
|
2019-12-20 15:56:28 +01:00
|
|
|
1.0218375f, 1.0666375f, 0.9130375f,
|
|
|
|
-0.07396251f, 0.91843754f, -0.17496246f,
|
|
|
|
0.47543746f, 1.2492375f, 0.55643755f,
|
|
|
|
1.3110375f, -0.36456245f, 1.0518374f,
|
|
|
|
0.7824375f, 0.57523745f, -0.21656245f,
|
|
|
|
0.0816375f, -0.2261625f, 0.40323752f,
|
|
|
|
1.4520376f, 0.6868375f, 0.81723756f,
|
|
|
|
-0.17576247f, 0.81423753f, -0.08656245f,
|
|
|
|
|
|
|
|
-0.36249164f, 0.45590833f, 1.1925083f,
|
|
|
|
0.00650835f, 1.4861084f, 1.2079083f,
|
|
|
|
0.05270836f, 0.37350836f, 0.94130826f,
|
|
|
|
1.0715083f, 0.6103083f, 0.9825083f,
|
|
|
|
0.07370833f, -0.4518917f, -0.39889166f,
|
|
|
|
-0.3354917f, 1.2213084f, 1.0345083f,
|
|
|
|
-0.3132917f, 0.78470826f, 0.23390833f,
|
|
|
|
0.6943083f, 0.68170834f, -0.09989169f,
|
|
|
|
|
|
|
|
0.8352709f, 1.3798709f, 0.15507084f,
|
|
|
|
0.26607084f, -0.10792917f, 1.2302709f,
|
|
|
|
0.6448709f, -0.29992914f, 1.3534708f,
|
|
|
|
0.86607087f, 0.37607086f, 0.04027084f,
|
|
|
|
0.40087086f, 0.59507084f, 0.9416709f,
|
|
|
|
0.53127086f, -0.01712915f, 1.4610709f,
|
|
|
|
-0.17152917f, -0.13992918f, 0.6242708f,
|
|
|
|
-0.42192918f, 0.38387084f, -0.15752912f,
|
|
|
|
|
|
|
|
0.3311833f, 0.00618333f, 0.17538333f,
|
|
|
|
0.10418332f, 0.8365834f, 0.27098334f,
|
|
|
|
1.2421833f, -0.1114167f, 1.0153834f,
|
|
|
|
0.9523833f, 0.8317833f, 0.9633833f,
|
|
|
|
0.6501833f, 0.04258335f, 0.9999833f,
|
|
|
|
-0.40181667f, 0.11418331f, 0.47938335f,
|
|
|
|
1.1057833f, -0.29761666f, 1.0779834f,
|
|
|
|
0.5243833f, -0.32181668f, 1.1833833f,
|
|
|
|
|
|
|
|
0.73157084f, 0.4317708f, 0.7283708f,
|
|
|
|
1.2297708f, 0.4307708f, 0.85377085f,
|
|
|
|
0.05977082f, -0.09282917f, 0.33957082f,
|
|
|
|
1.0751709f, 0.2119708f, 0.51897085f,
|
|
|
|
-0.25302917f, 1.1723708f, -0.12562919f,
|
|
|
|
1.1993709f, 0.5257708f, 0.40517086f,
|
|
|
|
0.53197086f, 0.8441708f, 0.02617085f,
|
|
|
|
-0.0208292f, 0.8711709f, 0.04137081f,
|
|
|
|
|
|
|
|
0.74936247f, 0.6085625f, 0.8997625f,
|
|
|
|
-0.08743751f, 0.18576252f, -0.17563748f,
|
|
|
|
0.5991625f, -0.0038375f, 0.07576251f,
|
|
|
|
0.42536253f, -0.22823751f, 0.36296248f,
|
|
|
|
0.81456256f, -0.16183749f, 0.5161625f,
|
|
|
|
-0.21183747f, 0.7429625f, 0.6217625f,
|
|
|
|
0.17656249f, 0.02616251f, -0.17923748f,
|
|
|
|
1.4659625f, 0.40016252f, 0.28356248f,
|
|
|
|
|
|
|
|
0.4195791f, 0.8745791f, 0.36637908f,
|
|
|
|
0.50597906f, -0.17942089f, 0.16917908f,
|
|
|
|
1.0235791f, 1.3699791f, -0.11382091f,
|
|
|
|
-0.0918209f, 0.7757791f, 0.09017909f,
|
|
|
|
1.3807791f, -0.15202093f, 1.3875791f,
|
|
|
|
-0.1712209f, 1.3989791f, 0.43777913f,
|
|
|
|
0.7855791f, 0.1423791f, 1.4711791f,
|
|
|
|
0.6455791f, 0.6211791f, -0.48062086f,
|
|
|
|
|
|
|
|
0.10189578f, 0.5628958f, 0.68909574f,
|
|
|
|
0.96649575f, -0.09370419f, 1.3466958f,
|
|
|
|
1.4584957f, 1.3544958f, -0.3829042f,
|
|
|
|
0.11269578f, -0.47890422f, 1.0436958f,
|
|
|
|
0.6128957f, 0.27209583f, 0.2714958f,
|
|
|
|
0.21889582f, 0.08789578f, 1.1296958f,
|
|
|
|
0.4596958f, 0.39309582f, 0.8344958f,
|
|
|
|
0.71149576f, -0.4799042f, 0.4880958f
|
2019-12-06 16:58:37 +01:00
|
|
|
});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.}, {}, {});
|
2019-12-06 16:58:37 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printBuffer("Adjusted Constrast6");
|
|
|
|
// e.printBuffer("Adjusted Expected 6");
|
|
|
|
// ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_AdjustContrast_7) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {8,8, 3, 1}, {0.7788f,0.8012f,0.7244f,0.2309f,0.7271f,0.1804f,
|
|
|
|
0.5056f,0.8925f,0.5461f,0.9234f,0.0856f,0.7938f,0.6591f,0.5555f,0.1596f,0.3087f,0.1548f,0.4695f,
|
|
|
|
0.9939f,0.6113f,0.6765f,0.1800f,0.6750f,0.2246f,0.0509f,0.4601f,0.8284f,0.2354f,0.9752f,0.8361f,
|
|
|
|
0.2585f,0.4189f,0.7028f,0.7679f,0.5373f,0.7234f,0.2690f,0.0062f,0.0327f,0.0644f,0.8428f,0.7494f,
|
|
|
|
0.0755f,0.6245f,0.3491f,0.5793f,0.5730f,0.1822f,0.6420f,0.9143f,0.3019f,
|
|
|
|
0.3574f,0.1704f,0.8395f,0.5468f,0.0744f,0.9011f,0.6574f,0.4124f,0.2445f,0.4248f,0.5219f,
|
|
|
|
0.6952f,0.4900f,0.2158f,0.9549f,0.1386f,0.1544f,0.5365f,0.0134f,0.4163f,0.1456f,0.4109f,
|
|
|
|
0.2484f, 0.3330f,0.2974f,0.6636f,0.3808f,0.8664f, 0.1896f, 0.7530f, 0.7215f, 0.6612f, 0.7270f,
|
|
|
|
0.5704f,0.2666f,0.7453f,0.0444f,0.3024f,0.4850f,0.7982f,0.0965f,0.7843f,0.5075f,
|
|
|
|
0.0844f,0.8370f,0.6103f,0.4604f,0.6087f, 0.8594f, 0.4599f, 0.6714f, 0.2744f, 0.1981f, 0.4143f,
|
|
|
|
0.7821f,0.3505f,0.5040f,0.1180f,0.8307f,0.1817f,0.8442f,0.5074f,0.4471f,0.5105f,0.6666f,
|
|
|
|
0.2576f,0.2341f,0.6801f,0.2652f,0.5394f,0.4690f,0.6146f,0.1210f,0.2576f,0.0769f,0.4643f,
|
|
|
|
0.1628f,0.2026f,0.3774f,0.0506f,0.3462f,0.5720f,0.0838f,0.4228f,0.0588f,0.5362f,0.4756f,
|
|
|
|
0.2530f,0.1778f,0.0751f,0.8977f,0.3648f,0.3065f,0.4739f,0.7014f,0.4473f,0.5171f,0.1744f,
|
|
|
|
0.3487f,0.7759f,0.9491f,0.2072f,0.2182f,0.6520f,0.3092f,0.9545f,0.1881f,0.9579f,0.1785f,
|
|
|
|
0.9636f,0.4830f,0.6569f,0.3353f,0.9997f,0.5869f,0.5747f,0.0238f,0.2943f,0.5248f,0.5879f,
|
|
|
|
.7266f,0.1965f,0.9167f,0.9726f,0.9206f,0.0519f,0.2997f,0.0039f,0.7652f,0.5498f,
|
|
|
|
0.3794f,0.3791f,0.3528f,0.2873f,0.8082f,0.4732f,0.4399f,0.6606f,0.5991f,0.0034f,0.4874f});
|
|
|
|
auto e = NDArrayFactory::create<double>('c', {8, 8, 3, 1}, {
|
2019-12-20 15:56:28 +01:00
|
|
|
1.0218375, 1.0666375 , 0.9130375 ,
|
|
|
|
-0.07396251, 0.91843754, -0.17496246,
|
|
|
|
0.47543746, 1.2492375 , 0.55643755,
|
|
|
|
1.3110375 , -0.36456245, 1.0518374 ,
|
|
|
|
0.7824375 , 0.57523745, -0.21656245,
|
|
|
|
0.0816375 , -0.2261625 , 0.40323752,
|
|
|
|
1.4520376 , 0.6868375 , 0.81723756,
|
|
|
|
-0.17576247, 0.81423753, -0.08656245,
|
|
|
|
|
|
|
|
-0.36249164, 0.45590833, 1.1925083 ,
|
|
|
|
0.00650835, 1.4861084 , 1.2079083 ,
|
|
|
|
0.05270836, 0.37350836, 0.94130826,
|
|
|
|
1.0715083 , 0.6103083 , 0.9825083 ,
|
|
|
|
0.07370833, -0.4518917 , -0.39889166,
|
|
|
|
-0.3354917 , 1.2213084 , 1.0345083 ,
|
|
|
|
-0.3132917 , 0.78470826, 0.23390833,
|
|
|
|
0.6943083 , 0.68170834, -0.09989169,
|
|
|
|
|
|
|
|
0.8352709 , 1.3798709 , 0.15507084,
|
|
|
|
0.26607084, -0.10792917, 1.2302709 ,
|
|
|
|
0.6448709 , -0.29992914, 1.3534708 ,
|
|
|
|
0.86607087, 0.37607086, 0.04027084,
|
|
|
|
0.40087086, 0.59507084, 0.9416709 ,
|
|
|
|
0.53127086, -0.01712915, 1.4610709 ,
|
|
|
|
-0.17152917, -0.13992918, 0.6242708 ,
|
|
|
|
-0.42192918, 0.38387084, -0.15752912,
|
|
|
|
|
|
|
|
|
|
|
|
0.3311833 , 0.00618333, 0.17538333,
|
|
|
|
0.10418332, 0.8365834 , 0.27098334,
|
|
|
|
1.2421833 , -0.1114167 , 1.0153834 ,
|
|
|
|
0.9523833 , 0.8317833 , 0.9633833 ,
|
|
|
|
0.6501833 , 0.04258335, 0.9999833 ,
|
|
|
|
-0.40181667, 0.11418331, 0.47938335,
|
|
|
|
1.1057833 , -0.29761666, 1.0779834 ,
|
|
|
|
0.5243833 , -0.32181668, 1.1833833 ,
|
|
|
|
|
|
|
|
0.73157084, 0.4317708 , 0.7283708 ,
|
|
|
|
1.2297708 , 0.4307708 , 0.85377085,
|
|
|
|
0.05977082, -0.09282917, 0.33957082,
|
|
|
|
1.0751709 , 0.2119708 , 0.51897085,
|
|
|
|
-0.25302917, 1.1723708 , -0.12562919,
|
|
|
|
1.1993709 , 0.5257708 , 0.40517086,
|
|
|
|
0.53197086, 0.8441708 , 0.02617085,
|
|
|
|
-0.0208292 , 0.8711709 , 0.04137081,
|
|
|
|
|
|
|
|
0.74936247, 0.6085625 , 0.8997625 ,
|
|
|
|
-0.08743751, 0.18576252, -0.17563748,
|
|
|
|
0.5991625 , -0.0038375 , 0.07576251,
|
|
|
|
0.42536253, -0.22823751, 0.36296248,
|
|
|
|
0.81456256, -0.16183749, 0.5161625 ,
|
|
|
|
-0.21183747, 0.7429625 , 0.6217625 ,
|
|
|
|
0.17656249, 0.02616251, -0.17923748,
|
|
|
|
1.4659625 , 0.40016252, 0.28356248,
|
|
|
|
|
|
|
|
0.4195791 , 0.8745791 , 0.36637908,
|
|
|
|
0.50597906, -0.17942089, 0.16917908,
|
|
|
|
1.0235791 , 1.3699791 , -0.11382091,
|
|
|
|
-0.0918209 , 0.7757791 , 0.09017909,
|
|
|
|
1.3807791 , -0.15202093, 1.3875791 ,
|
|
|
|
-0.1712209 , 1.3989791 , 0.43777913,
|
|
|
|
0.7855791 , 0.1423791 , 1.4711791 ,
|
|
|
|
0.6455791 , 0.6211791 , -0.48062086,
|
|
|
|
|
|
|
|
|
|
|
|
0.10189578, 0.5628958 , 0.68909574,
|
|
|
|
0.96649575, -0.09370419, 1.3466958 ,
|
|
|
|
1.4584957 , 1.3544958 , -0.3829042 ,
|
|
|
|
0.11269578, -0.47890422, 1.0436958 ,
|
|
|
|
0.6128957 , 0.27209583, 0.2714958 ,
|
|
|
|
0.21889582, 0.08789578, 1.1296958 ,
|
|
|
|
0.4596958 , 0.39309582, 0.8344958 ,
|
|
|
|
0.71149576, -0.4799042, 0.4880958
|
2019-12-06 16:58:37 +01:00
|
|
|
});
|
|
|
|
// x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::adjust_contrast_v2 op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x}, {2.}, {}, {});
|
2019-12-06 16:58:37 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printBuffer("Adjusted Constrast7");
|
|
|
|
// e.printBuffer("Adjusted expected 7");
|
|
|
|
auto diff = e - *out;
|
|
|
|
// diff.printBuffer("Adjusted subtract 7");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-10-02 18:05:26 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_1) {
|
2019-10-02 14:04:28 +02:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {2, 2, 2});
|
|
|
|
auto e = NDArrayFactory::create<double>('c', {2, 2}, {2., 512., 8192., 131072.032 });
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
|
|
|
auto result = op.evaluate({&x}, {(int) sd::DataType::DOUBLE});
|
2019-10-02 14:04:28 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
// out->printIndexedBuffer("Casted result");
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-10-02 18:05:26 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_2) {
|
2019-10-02 14:04:28 +02:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {2, 4});
|
2019-11-30 14:02:07 +01:00
|
|
|
auto e = NDArrayFactory::create<float16>('c', {2, 4, 2}, {0.f, 1.875f, 0.f, 2.f, 0.f, 2.125f, 0.f, 2.25f,
|
|
|
|
0.f, 2.312f, 0.f, 2.375f, 0.f, 2.438f, 0.f, 2.5f});
|
2019-10-02 14:04:28 +02:00
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
|
|
|
auto result = op.evaluate({&x}, {(int) sd::DataType::HALF});
|
2019-10-02 14:04:28 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto out = result->at(0);
|
|
|
|
ASSERT_TRUE(e.equalsTo(out));
|
|
|
|
delete result;
|
|
|
|
}
|
2019-10-01 10:44:27 +02:00
|
|
|
|
2019-11-22 20:42:44 +01:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_3) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 4});
|
|
|
|
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
2019-11-22 20:42:44 +01:00
|
|
|
try {
|
2020-03-02 10:49:41 +01:00
|
|
|
auto result = op.evaluate({&x}, {(int) sd::DataType::INT64});
|
2019-11-22 20:42:44 +01:00
|
|
|
ASSERT_NE(Status::OK(), result->status());
|
|
|
|
delete result;
|
|
|
|
} catch (std::exception& e) {
|
|
|
|
nd4j_printf("Error should be here `%s'. It's OK.\n", e.what());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_4) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 4});
|
|
|
|
auto e = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {1234567890LL, 2468013579LL});
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
2019-11-22 20:42:44 +01:00
|
|
|
try {
|
2020-03-02 10:49:41 +01:00
|
|
|
auto result = op.execute({&x}, {&e}, {}, {sd::DataType::INT64}, {});
|
2019-11-22 20:42:44 +01:00
|
|
|
ASSERT_NE(Status::OK(), result);
|
|
|
|
} catch(std::exception& e) {
|
|
|
|
nd4j_printf("Error `%s' should be here. It's OK.\n",e.what());
|
|
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
|
2020-01-22 08:46:33 +01:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_4_1) {
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {1, 2});
|
|
|
|
auto e = NDArrayFactory::create<Nd4jLong>('c', {1, 2}, {4607182418800017408LL, 4611686018427387904LL}); // as TF 4607182418800017408, 4611686018427387904
|
|
|
|
x.linspace(1.);
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
2020-01-22 08:46:33 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
auto result = op.evaluate({&x}, {}, {sd::DataType::INT64}, {});
|
2020-01-22 08:46:33 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
// e.printIndexedBuffer("Double to int64");
|
|
|
|
auto res = result->at(0);
|
|
|
|
ASSERT_EQ(*res, e);
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-11-29 14:05:08 +01:00
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_5) {
|
|
|
|
auto x = NDArrayFactory::create<float16>('c', {4, 4}, {
|
|
|
|
0.4922f, 0.2969f, 0.6172f, 0.8906f,
|
|
|
|
0.9297f, 0.0859f, 0.2344f, 0.3828f,
|
|
|
|
0.5781f, 0.7969f, 0.0391f, 0.1719f,
|
|
|
|
0.8359f, 0.9297f, 0.3438f, 0.0938f});
|
|
|
|
|
|
|
|
auto e = NDArrayFactory::create<Nd4jLong>('c', {4}, {4260467851820808160LL, 3900173902914993008LL, 3566895990128523424LL,
|
|
|
|
3314989625590692528LL});
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
|
|
|
auto result = op.evaluate({&x}, {}, {sd::DataType::INT64}, {});
|
2019-11-29 14:05:08 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto res = result->at(0);
|
|
|
|
// res->printIndexedBuffer("BITCAST5");
|
|
|
|
ASSERT_TRUE(e.equalsTo(res));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_6) {
|
|
|
|
auto x = NDArrayFactory::create<float16>('c', {4, 4}, {
|
|
|
|
1.f, 2.f, 3.f, 4.f,
|
|
|
|
5.f, 6.f, 7.f, 8.f,
|
|
|
|
9.f, 10.f, 11.f, 12.f,
|
|
|
|
13.f, 14.f, 15.f, 16.f});
|
|
|
|
|
|
|
|
auto e = NDArrayFactory::create<Nd4jLong>('c', {4}, {4899988963420290048LL, 5188224837230806272LL, 5332342774136064128LL,
|
|
|
|
5476460161268730496LL});
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
|
|
|
auto result = op.evaluate({&x}, {}, {sd::DataType::INT64}, {});
|
2019-11-29 14:05:08 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto res = result->at(0);
|
|
|
|
// res->printIndexedBuffer("BITCAST6");
|
|
|
|
ASSERT_TRUE(e.equalsTo(res));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_BitCast_7) {
|
|
|
|
auto x = NDArrayFactory::create<float16>('c', {4, 4}, {
|
|
|
|
1.1f, 2.2f, 3.3f, 4.4f,
|
|
|
|
5.1f, 6.2f, 7.3f, 8.4f,
|
|
|
|
9.1f, 10.2f, 11.3f, 12.4f,
|
|
|
|
13.f, 14.2f, 15.3f, 16.4f});
|
|
|
|
|
|
|
|
auto e = NDArrayFactory::create<Nd4jLong>('c', {4}, {
|
|
|
|
4928700072476425318LL, 5202580391758873882LL, 5346698272827918477LL, 5483778673873668736LL});
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::bitcast op;
|
|
|
|
auto result = op.evaluate({&x}, {}, {sd::DataType::INT64}, {});
|
2019-11-29 14:05:08 +01:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto res = result->at(0);
|
|
|
|
// res->printIndexedBuffer("BITCAST7");
|
|
|
|
ASSERT_TRUE(e.equalsTo(res));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
2019-06-06 14:21:15 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, test_matmul_bp_1) {
|
|
|
|
auto a = NDArrayFactory::create<double>('c', {1, 3});
|
|
|
|
auto b = NDArrayFactory::create<double>('c', {1, 4});
|
|
|
|
auto gI = NDArrayFactory::create<double>('c', {3, 4});
|
|
|
|
|
|
|
|
auto gA = NDArrayFactory::create<double>('c', {1, 3});
|
|
|
|
auto gB = NDArrayFactory::create<double>('c', {1, 4});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::matmul_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto status = op.execute({&a, &b, &gI}, std::vector<NDArray*>{&gA, &gB}, {}, {1, 0, 0}, {});
|
2019-06-06 14:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), status);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_non_decreasing_1) {
|
|
|
|
auto x = NDArrayFactory::create<double>(1.0);
|
|
|
|
auto z = NDArrayFactory::create<bool>(false);
|
|
|
|
auto e = NDArrayFactory::create<bool>(true);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::is_non_decreasing op;
|
2019-06-06 14:21:15 +02:00
|
|
|
Context ctx(1);
|
|
|
|
ctx.setInputArray(0, &x);
|
|
|
|
ctx.setOutputArray(0, &z);
|
|
|
|
|
|
|
|
auto status = op.execute(&ctx);
|
|
|
|
ASSERT_EQ(Status::OK(), status);
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, test_check_numeric_1) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {3},{1.f, 2.f, 3.f});
|
|
|
|
auto y = NDArrayFactory::string("shouldn't ever trigger");
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::check_numerics op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x, &y}, {}, {});
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
|
|
|
|
auto z = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(x, *z);
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_check_numeric_2) {
|
2020-02-13 18:59:35 +01:00
|
|
|
#ifdef FFAST_MATH
|
|
|
|
if (1 > 0)
|
|
|
|
return;
|
|
|
|
#endif
|
|
|
|
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {3},{1.f, 2.f, std::numeric_limits<float>::infinity()});
|
|
|
|
auto y = NDArrayFactory::string("should trigger");
|
|
|
|
auto z = NDArrayFactory::create<float>('c', {3} );
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::check_numerics op;
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
try {
|
|
|
|
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
|
|
|
|
ASSERT_TRUE(false);
|
|
|
|
} catch (std::invalid_argument &e) {
|
|
|
|
//
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_check_numeric_3) {
|
2020-02-13 18:59:35 +01:00
|
|
|
#ifdef FFAST_MATH
|
|
|
|
if (1 > 0)
|
|
|
|
return;
|
|
|
|
#endif
|
|
|
|
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {3},{1.f, 2.f, std::numeric_limits<float>::quiet_NaN()});
|
|
|
|
auto y = NDArrayFactory::string("should trigger");
|
|
|
|
auto z = NDArrayFactory::create<float>('c', {3} );
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::check_numerics op;
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
try {
|
|
|
|
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
|
|
|
|
ASSERT_TRUE(false);
|
|
|
|
} catch (std::invalid_argument &e) {
|
|
|
|
//
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2019-06-06 14:21:15 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, Test_layer_norm_1) {
|
2019-11-30 14:02:07 +01:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
|
|
|
auto g = NDArrayFactory::create<float>('c', {5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
|
|
|
auto b = NDArrayFactory::create<float>('c', {5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
2019-06-06 14:21:15 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::layer_norm op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x, &g, &b}, {}, {0}, {false});
|
2019-06-06 14:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_layer_norm_bp_1) {
|
2019-11-30 14:02:07 +01:00
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
|
|
|
auto g = NDArrayFactory::create<float>('c', {5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
|
|
|
auto b = NDArrayFactory::create<float>('c', {5}, {1.f, 2.f, 3.f, 4.f, 5.f});
|
|
|
|
auto eps = NDArrayFactory::create<float>('c', {1, 5}, {0.f, 0.f, 0.f, 0.f, 0.f});
|
2019-06-06 14:21:15 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::layer_norm_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x, &g, &b, &eps}, {}, {0}, {false});
|
2019-06-06 14:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
delete result;
|
|
|
|
}
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
|
2019-08-27 18:57:59 +02:00
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, Test_layer_norm_bp_2) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray x('c', {3, 4, 8, 8}, sd::DataType::FLOAT32);
|
|
|
|
NDArray gain('c', {4}, {-0.1, 0.1, -0.2, 0.2}, sd::DataType::FLOAT32);
|
|
|
|
NDArray bias('c', {4}, {-0.05, 0.05, -1.05, 1.05}, sd::DataType::FLOAT32);
|
|
|
|
NDArray gradO('c', {3, 4, 8, 8}, sd::DataType::FLOAT32);
|
2019-08-27 18:57:59 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray gradI('c', {3, 4, 8, 8}, sd::DataType::FLOAT32);
|
|
|
|
NDArray gradG('c', {4}, sd::DataType::FLOAT32);
|
|
|
|
NDArray gradB('c', {4}, sd::DataType::FLOAT32);
|
2019-08-27 18:57:59 +02:00
|
|
|
|
|
|
|
x.linspace(-20, 0.5);
|
|
|
|
gradO.linspace(-4, 0.05);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::layer_norm_bp op;
|
2019-08-27 18:57:59 +02:00
|
|
|
auto status = op.execute({&x, &gain, &bias, &gradO}, {&gradI, &gradG, &gradB}, {}, {1,2,3}, {true});
|
|
|
|
ASSERT_EQ(Status::OK(), status);
|
|
|
|
}
|
|
|
|
|
2019-07-10 13:32:12 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, test_hashCode_1) {
|
|
|
|
auto x = NDArrayFactory::create<int>('c', {10});
|
|
|
|
auto y = NDArrayFactory::create<int>('c', {10});
|
|
|
|
|
|
|
|
x.linspace(1.);
|
|
|
|
y.linspace(2.);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::hashcode op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultA0 = op.evaluate({&x});
|
|
|
|
auto resultA1 = op.evaluate({&x});
|
|
|
|
auto resultB0 = op.evaluate({&y});
|
2019-08-02 19:01:03 +02:00
|
|
|
// resultA0->at(0)->printIndexedBuffer("A0");
|
|
|
|
// resultA1->at(0)->printIndexedBuffer("A1");
|
|
|
|
// resultB0->at(0)->printIndexedBuffer("B0");
|
2019-07-10 13:32:12 +02:00
|
|
|
ASSERT_EQ(*resultA0->at(0), *resultA1->at(0));
|
|
|
|
ASSERT_NE(*resultA0->at(0), *resultB0->at(0));
|
|
|
|
|
|
|
|
delete resultA0;
|
|
|
|
delete resultA1;
|
|
|
|
delete resultB0;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_hashCode_2) {
|
|
|
|
auto x = NDArrayFactory::create<int>('c', {1027});
|
|
|
|
auto y = NDArrayFactory::create<int>('c', {1027});
|
|
|
|
|
|
|
|
x.linspace(1.);
|
|
|
|
y.linspace(2.);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::hashcode op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultA0 = op.evaluate({&x});
|
|
|
|
auto resultA1 = op.evaluate({&x});
|
|
|
|
auto resultB0 = op.evaluate({&y});
|
2019-08-02 19:01:03 +02:00
|
|
|
|
|
|
|
// resultA0->at(0)->printIndexedBuffer("A0");
|
|
|
|
// resultA1->at(0)->printIndexedBuffer("A1");
|
|
|
|
// resultB0->at(0)->printIndexedBuffer("B0");
|
2019-07-10 13:32:12 +02:00
|
|
|
|
|
|
|
ASSERT_EQ(*resultA0->at(0), *resultA1->at(0));
|
|
|
|
ASSERT_NE(*resultA0->at(0), *resultB0->at(0));
|
|
|
|
|
|
|
|
delete resultA0;
|
|
|
|
delete resultA1;
|
|
|
|
delete resultB0;
|
|
|
|
}
|
|
|
|
|
2019-07-25 12:50:36 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, test_reshape_to_scalar_1) {
|
|
|
|
auto array = NDArrayFactory::create<float>(119.f);
|
|
|
|
auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::reshape op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&array}, {}, {1, 1});
|
2019-07-25 12:50:36 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
|
|
|
|
auto z = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(e, *z);
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_reshape_to_scalar_2) {
|
|
|
|
auto array = NDArrayFactory::create<float>(119.f);
|
|
|
|
auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
|
|
|
|
auto z = NDArrayFactory::create<float>('c', {1, 1});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::reshape op;
|
2019-07-25 12:50:36 +02:00
|
|
|
auto result = op.execute({&array}, {&z}, {}, {1, 1}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), result);
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rank_1) {
|
|
|
|
auto array = NDArrayFactory::create<float>('c', {4, 64});
|
|
|
|
auto e = NDArrayFactory::create<int>('c', {}, {2});
|
|
|
|
auto z = NDArrayFactory::create<int>('c', {});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rank op;
|
2019-07-25 12:50:36 +02:00
|
|
|
auto result = op.execute({&array}, {&z}, {}, {}, {});
|
|
|
|
ASSERT_EQ(Status::OK(), result);
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rank_2) {
|
|
|
|
auto array = NDArrayFactory::create<float>('c', {4, 64});
|
|
|
|
auto e = NDArrayFactory::create<int>('c', {}, {2});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rank op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&array}, {}, {});
|
2019-07-25 12:50:36 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
|
|
|
|
auto z = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(e, *z);
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
TEST_F(DeclarableOpsTests15, test_lstmBlock_1) {
|
|
|
|
auto x0 = NDArrayFactory::create<Nd4jLong>(5);
|
|
|
|
auto x1 = NDArrayFactory::create<float>('c', {5, 1, 4}, {0.7787856f, 0.80119777f, 0.72437465f, 0.23089433f, 0.72714126f, 0.18039072f, 0.50563407f, 0.89252293f, 0.5461209f, 0.92336726f, 0.085571885f, 0.7937801f, 0.65908563f, 0.55552566f, 0.15962744f, 0.30874777f, 0.15476847f, 0.46954823f, 0.9938899f, 0.6112741f});
|
|
|
|
auto x2 = NDArrayFactory::create<float>('c', {1, 3}, {0.7717289f, 0.9280778f, 0.98455656f});
|
|
|
|
auto x3 = NDArrayFactory::create<float>('c', {1, 3}, {0.94414854f, 0.5956861f, 0.8668989f});
|
|
|
|
auto x4 = NDArrayFactory::create<float>('c', {7, 12}, {0.460692f, 0.042572856f, 0.08420354f, -0.09538093f, -0.11416581f, -0.53166187f, 0.40133476f, -0.24381405f, 0.30778718f, 0.52713746f, 0.16253126f, -0.034891903f, 0.011679292f, -0.19076681f, 0.14710993f, -0.3704369f, 0.51872355f, 0.13536876f, -0.5568739f, -0.08727971f, 0.07601875f, -0.074174374f, -0.5345982f, -0.3581748f, -0.28263924f, -0.25141674f, 0.43328637f, -0.50227314f, -0.26641843f, -0.38241976f, -0.19636461f, -0.04020852f, -0.27312332f, 0.5207915f, -0.37247592f, -0.4713087f, -0.25670746f, -0.14942765f, -0.015806139f, -0.22531253f, 0.5582536f, 0.3093416f, 0.3221351f, -0.0964683f, 0.14318448f, 0.42279094f, -0.46992f, -0.43399644f, -0.51704615f, -0.11854091f, 0.21697259f, -0.049382925f, 0.14059627f, 0.3912331f, -0.41345632f, 0.5067368f, -0.3420229f, 0.485789f, 0.044918716f, 0.26209074f, 0.12357575f, 0.21778125f, -0.53791714f, 0.18346387f, 0.054183125f, 0.5480431f, 0.03675288f, -0.26656917f, -0.018610716f, 0.19917983f, 0.5566165f, 0.43570566f, -0.35720813f, 0.31097364f, -0.47134516f, -0.289197f, 0.091138184f, 0.13300979f, -0.36592877f, -0.17540845f, 0.21732038f, 0.4393713f, 0.42800313f, 0.5006979f});
|
|
|
|
auto x5 = NDArrayFactory::create<float>('c', {1, 3});
|
|
|
|
auto x6 = NDArrayFactory::create<float>('c', {1, 3});
|
|
|
|
auto x7 = NDArrayFactory::create<float>('c', {1, 3});
|
|
|
|
auto x8 = NDArrayFactory::create<float>('c', {12});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::lstmBlock op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x0, &x1, &x2, &x3, &x4, &x5, &x6, &x7, &x8}, {2.0, 0.3}, {0, 0});
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
|
|
|
|
auto z = result->at(0);
|
|
|
|
|
2019-08-02 19:01:03 +02:00
|
|
|
// z->printIndexedBuffer("Z");
|
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* correct logsoftmax looss (#2)
* Small SameDiff listener fix (#4)
* Various fixes (#6)
* #7839 Fix for asXMatrix and tests
* #7866 EmbeddingSequenceLayer dtype fix + test
* #7856 SameDiff save/load stream methods
* #7859 RegressionEvaluation rank 4 fix + tests + axis configuration
* EvaluationBinary 3d/4d
* More evaluation 3d/4d tests
* #7847 Evaluation empty checks
* Small test ifx
* #7848 Fix median edge case
* Improve DL4J samediff layer tests
* [WIP] FastText wrapper implemented (#8)
* FastText implemented
* Some fixes
* Fix shapes for wordsNearest
* Validation of input vectors
* Fixes
* Fixed test
* Thread tagged
* Some tweaks
* setContextClassLoader for DeallocatorServiceThread
* Numpy format tests (#1)
* Various fixes (#11)
* #7852 SameDiff gather fix
* #7892 SameDiff placeholder to constant conversion
* #7890 validate input rank for MLN/CG init methods
* Fix broken permute shape calculation
* Permute and gather fixes
* Tests
* #7850 LogSumExp fix + test
* Handful of test fixes
* Empty arrays with non-scalar shapes (#10)
* minor rearrangements for lambdas
* empty tensors with non-scalar shapes
* numpy empty tensors with non-scalar shapes
* few more empty tweaks
* Small fixes
* conv3d signature update
* micro fix in batchnorm mkldnn
* Import fixes
* Fix
* MKL-DNN update
* Small fill fix
* fill with empty input + test
* Fixes
* Small error improvement
* Fix
* one special test
* couple of fixes for lstm
* Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone
* Fixes
* FP16
* Unsigned
* BFloat16
* Fill op - empty tweaks
* - couple of fixes for empty arrays construction
- stack updated
* strided slice fix
* one transform test
* provide method for reducing shapeInfo in case of input array is empty
* Fixed reduceAlongDimensions to use empty input properly.
* couple of broadcast tests
* couple of tests broadcast tests + tweak to make them pass
* add check of non-empty to methods producing sub-arrays
* Fixed reshapeC with zeros in shape.
* complete empty check in reduce_... legacy ops
* Concat and cumsum/prod
* Tweak to empty shape inference on import
* add empty check to the rest of reduce legacy ops
* one more test
* correct typo in evalReduceShapeInfoEmpty
* Added tests for reduce_* ops to tests with zero shapes.
* few more tests for empty reductions
* Fixed strided_slice op with empty case and tests.
* one more empty reduction test
* Fixed strided_slice test.
* add empty check to NDArray::reshapei
* infOrMax
* empty min/max with infinity tests
* made unstack working correctly with empty arrays
* few IndexReduce tests + tweaks for empty shapes
* add test for empty concat
* few tests fixed
* Validation fix for reductions on empty shapes
* Reverse fix
* Reduction shape calc fixes
* SameDiff.generateOutputVariable: don't use shape function to determine number of outputs
* Range fix
* - NDArray constructor updated for scalars/empty arrays
- few tests fixed
* More fixes
* Empty creator fixes
* concat fix
* concat fix
* TF import tests: allow 'both all NaN' and 'both all inf' to pass
* Slice, zero fraction, and reshape fixes
* transpose, gather
* Zero fraction
* scalar cast fix
* Empty reduction axis support
* few more tests fixed
* Fixed input checks conforming with TF for concat op and tests.
* few tests fixed
* matmul scalar shape fix
* Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats.
* broadcast bool fix
* few more tests
* few more tests
* correct evalReduceShapeInfoEmpty
* argmax/argmin + tests
* one more empty edge case + one more test
* argmax/argmin/realdiv_bp tweaks
* empty reshape test + fix
* Helper fixes
* Small fixes
* Gather test fix
* Gather test fix
* Small fixes
* reduce scalar zero values
* scalar mean workaround
* Remove debug code
* along dim mean workaround
* one more test
* - equalsTo() tweak for empty arrays
- one more test
* broadcast tweaks
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
Signed-off-by: raver119 <raver119@gmail.com>
* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* minor test fix
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* couple of assertions tweaked
Signed-off-by: raver119 <raver119@gmail.com>
* MDS splitter test :/
Signed-off-by: raver119 <raver119@gmail.com>
* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
Signed-off-by: raver119 <raver119@gmail.com>
* LRN BP CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* less memory
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
Signed-off-by: raver119 <raver119@gmail.com>
* topK concept
Signed-off-by: raver119 <raver119@gmail.com>
* unsorted topK with scanWitdh of 1
Signed-off-by: raver119 <raver119@gmail.com>
* correct vol2col tests
* sorted/unsorted topK
Signed-off-by: raver119 <raver119@gmail.com>
* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
Signed-off-by: raver119 <raver119@gmail.com>
* percentile op
Signed-off-by: raver119 <raver119@gmail.com>
* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
Signed-off-by: raver119 <raver119@gmail.com>
* less threads for sortTad
Signed-off-by: raver119 <raver119@gmail.com>
* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
Signed-off-by: raver119 <raver119@gmail.com>
* dts cuda
Signed-off-by: raver119 <raver119@gmail.com>
* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* more of minor lstm rearrangements
Signed-off-by: raver119 <raver119@gmail.com>
* (bi)dynamic_rnn
Signed-off-by: raver119 <raver119@gmail.com>
* templates init order
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value
Signed-off-by: raver119 <raver119@gmail.com>
* CPU sort TAD by key/value tests
Signed-off-by: raver119 <raver119@gmail.com>
* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
Signed-off-by: raver119 <raver119@gmail.com>
* provide depthwise_conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
Signed-off-by: Yurii <yurii@skymind.io>
* CUDA linear sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* CUDA tad sort by key/val
Signed-off-by: raver119 <raver119@gmail.com>
* start providing of backprop for pooling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* Added atomicAdd for bool datatype.
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic partition scalar CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* important comment
Signed-off-by: raver119 <raver119@gmail.com>
* fix pooling2d/3d backprop helpers
Signed-off-by: Yurii <yurii@skymind.io>
* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
Signed-off-by: raver119 <raver119@gmail.com>
* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
Signed-off-by: raver119 <raver119@gmail.com>
* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
Signed-off-by: Yurii <yurii@skymind.io>
* dynamic_stitch CUDA vector case
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case concept
Signed-off-by: raver119 <raver119@gmail.com>
* dynamic_stitch CUDA TAD case impl
Signed-off-by: raver119 <raver119@gmail.com>
* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed type check for dynamic stitch.
* min/max bp
Signed-off-by: raver119 <raver119@gmail.com>
* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
Signed-off-by: raver119 <raver119@gmail.com>
* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
Signed-off-by: raver119 <raver119@gmail.com>
* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
Signed-off-by: raver119 <raver119@gmail.com>
2019-06-27 17:37:04 +02:00
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
2019-07-12 07:21:15 +02:00
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_lstmBlock_2) {
|
2019-10-17 19:44:52 +02:00
|
|
|
int seqLen = 8;
|
|
|
|
int bS = 16;
|
|
|
|
int nIn = 8;
|
2019-07-12 07:21:15 +02:00
|
|
|
|
|
|
|
auto x0 = NDArrayFactory::create<Nd4jLong>(5);
|
2019-08-02 19:01:03 +02:00
|
|
|
auto x1 = NDArrayFactory::create<float>('f', {bS, nIn, seqLen});
|
|
|
|
auto x2 = NDArrayFactory::create<float>('f', {bS, nIn}); // nIn == nOut
|
|
|
|
auto x3 = NDArrayFactory::create<float>('f', {bS, nIn});
|
|
|
|
auto x4 = NDArrayFactory::create<float>('f', {2 * nIn, 4 * nIn});
|
|
|
|
auto x5 = NDArrayFactory::create<float>('f', {nIn});
|
|
|
|
auto x6 = NDArrayFactory::create<float>('f', {nIn});
|
|
|
|
auto x7 = NDArrayFactory::create<float>('f', {nIn});
|
|
|
|
auto x8 = NDArrayFactory::create<float>('f', {4 * nIn});
|
2019-07-12 07:21:15 +02:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::lstmBlock op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&x0, &x1, &x2, &x3, &x4, &x5, &x6, &x7, &x8}, {1.0, 0.0}, {0, 1});
|
2019-07-12 07:21:15 +02:00
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
|
|
|
|
auto z = result->at(0);
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
2019-08-02 19:01:03 +02:00
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_lstmBlock_3) {
|
|
|
|
|
|
|
|
int seqLen = 3;
|
|
|
|
int bS = 2;
|
|
|
|
int nIn = 4;
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray f('f', {bS, nIn, seqLen}, sd::DataType::FLOAT32);
|
|
|
|
NDArray cLast('f', {bS, nIn}, sd::DataType::FLOAT32);
|
2019-08-02 19:01:03 +02:00
|
|
|
|
|
|
|
f = 2;
|
|
|
|
cLast = 3;
|
|
|
|
|
|
|
|
for (int t = 0; t < seqLen; ++t) {
|
|
|
|
|
|
|
|
//section 1
|
|
|
|
//auto ft = f({0,0, 0,0, t,t+1});
|
|
|
|
//auto temp = ft * cLast;
|
|
|
|
|
|
|
|
|
|
|
|
// section 2
|
|
|
|
auto ft = f({0,0, 0,0, t,t+1});
|
|
|
|
auto temp1 = ft.reshape('f', {bS, nIn});
|
|
|
|
auto temp2 = temp1 * cLast;
|
|
|
|
}
|
2019-11-20 09:12:15 +01:00
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_empty_increasing_1) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 0, 3});
|
|
|
|
auto z = NDArrayFactory::create<bool>(false);
|
|
|
|
|
|
|
|
Context ctx(1);
|
|
|
|
ctx.setInputArray(0, &x);
|
|
|
|
ctx.setOutputArray(0, &z);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::is_strictly_increasing op;
|
2019-11-20 09:12:15 +01:00
|
|
|
auto status = op.execute(&ctx);
|
|
|
|
ASSERT_EQ(Status::OK(), status);
|
|
|
|
|
|
|
|
ASSERT_EQ(true, z.e<bool>(0));
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, test_empty_decreasing_1) {
|
|
|
|
auto x = NDArrayFactory::create<float>('c', {1, 0, 3});
|
|
|
|
auto z = NDArrayFactory::create<bool>(false);
|
|
|
|
|
|
|
|
Context ctx(1);
|
|
|
|
ctx.setInputArray(0, &x);
|
|
|
|
ctx.setOutputArray(0, &z);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::is_non_decreasing op;
|
2019-11-20 09:12:15 +01:00
|
|
|
auto status = op.execute(&ctx);
|
|
|
|
ASSERT_EQ(Status::OK(), status);
|
|
|
|
|
|
|
|
ASSERT_EQ(true, z.e<bool>(0));
|
2019-11-29 14:05:08 +01:00
|
|
|
}
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_1) {
|
|
|
|
// rank 1
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3 }, { 10, 50, 200 }, sd::DataType::INT32);
|
|
|
|
NDArray expected('c', { 1 }, std::vector<double>{ 55 }, sd::DataType::INT32);
|
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({&rgbs}, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_2) {
|
|
|
|
// rank 1
|
|
|
|
auto rgbs = NDArrayFactory::create<int>('f', { 3 }, { 1, 120, -25 });
|
|
|
|
auto expected = NDArrayFactory::create<int>('f', { 1 }, { 67 });
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_3) {
|
|
|
|
// rank 2
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 4, 3 }, { -94, 99, 97, 90, 114, 101, 111, 96, 105, 100, 103, 102 }, sd::DataType::INT32);
|
|
|
|
NDArray expected('c', { 4, 1 }, { 41, 105, 101, 101 }, sd::DataType::INT32);
|
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_4) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3, 2 }, {14, 99, 207, 10, 114, 201 }, sd::DataType::INT32);
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
|
|
|
|
rgbs.permutei({1,0});
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('c', { 2, 1 }, { 138, 58 }, sd::DataType::INT32);
|
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_5) {
|
|
|
|
// rank 2
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3, 4 }, { -94, 99, 97, 90, 114, 101, 111, 96, 105, 100, 103, 102 }, sd::DataType::INT32);
|
|
|
|
NDArray expected('c', { 1, 4 }, { 50, 100, 105, 94 }, sd::DataType::INT32);
|
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {0});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_6) {
|
|
|
|
// rank 3
|
|
|
|
auto rgbs = NDArrayFactory::create<float>('c', { 5,4,3 }, {1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f});
|
|
|
|
auto expected = NDArrayFactory::create<float>('c', { 5,4,1 }, {-47.82958221f, 34.46305847f, 21.36137581f, -21.91625023f,2.49686432f, -43.59792709f, 9.64180183f, 23.04854202f,40.7946167f, 44.98754883f, -25.19047546f, 20.64586449f,-4.97033119f, 30.0226841f, 30.30688286f, 15.61459541f,43.36166f, 18.22480774f, 13.74833488f, 21.59387016f});
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_7) {
|
|
|
|
// rank 3
|
|
|
|
auto rgbs = NDArrayFactory::create<float>('c', { 5,3,4 }, { 1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f});
|
2019-12-20 19:11:18 +01:00
|
|
|
auto expected = NDArrayFactory::create<float>('c', { 5,1,4 }, { 36.626545f, 38.607746f, -40.614971f, 18.233341f, -51.545094f,2.234142f, 20.913160f, 8.783220f, 15.955761f, 55.273506f, 36.838833f, -29.751089f, 8.148357f, 13.676106f, 1.097548f, 68.766457f, 38.690712f, 27.176361f, -14.156269f, 7.157052f });
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {1});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_8) {
|
|
|
|
// rank 3
|
|
|
|
auto rgbs = NDArrayFactory::create<float>('c', { 3,5,4 }, {1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f});
|
|
|
|
try {
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
ASSERT_EQ(Status::THROW(), result->status());
|
|
|
|
delete result;
|
|
|
|
} catch (std::exception& e) {
|
|
|
|
nd4j_printf("Error should be here `%s'. It's OK.\n", e.what());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_grs_9) {
|
|
|
|
// rank 3
|
|
|
|
auto rgbs = NDArrayFactory::create<float>('f', { 2, 2, 3 }, { 1.7750e+01f,-7.1062e+01f, -1.0019e+02f, -2.3406e+01f,5.2094e+01f,9.5438e+01f, -6.7461e+00f,3.8562e+01f, 6.5078e+00f, 3.3562e+01f,-5.8844e+01f,2.2750e+01f});
|
|
|
|
auto expected = NDArrayFactory::create<float>('f', { 2,2,1 }, { 36.626545f, 38.607746f, -40.614971f, 18.233341f });
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_grs op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
2019-12-24 16:30:54 +01:00
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_1) {
|
|
|
|
// rank 1
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('f', { 3 }, { 10, 50, 200 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('f', { 3 }, { 55.14 , 71.2872001, -39.6005542 }, sd::DataType::FLOAT32);
|
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_2) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3, 2 }, { 14., 99., 207., 10., 114., 201. }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
rgbs.permutei({ 1,0 });
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('c', { 2, 3 }, { 138.691, -12.150713, -109.38929, 58.385, 70.18241, 35.63085 }, sd::DataType::FLOAT32);
|
|
|
|
sd::ops::rgb_to_yuv op;
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
2020-01-28 16:23:07 +01:00
|
|
|
|
2019-12-24 16:30:54 +01:00
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_3) {
|
|
|
|
// rank 2
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3, 4 }, { -9.4, 9.9, 9.7, 9.0, 1.14, 1.01, 1.11, 9.6, 1.05, 10.0, 1.03, 10.22 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', { 3, 4 }, { -2.021720, 4.692970, 3.669290, 9.491281, 1.511627, 2.611648, -1.298824, 0.358612, -6.472839, 4.568039, 5.290639, -0.430992 }, sd::DataType::FLOAT32);
|
2020-01-28 16:23:07 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, { 0 });
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_4) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 5,4,3 }, { 1.7750e+01, 1.4602e+01, 5.4883e+00, 9.5438e+01, 1.0038e+02, 4.0531e+01, -5.8844e+01, 2.9609e+01, -1.1414e+01, 2.1391e+01, 3.9656e+01, 2.1531e+01, -7.1062e+01, -4.5859e+00, 2.9438e+01, -6.7461e+00, 6.7938e+01, -6.1211e+00, 2.2750e+01, -6.1438e+01, 1.5404e-02, -8.5312e+01, 1.1641e+01, 6.2500e+01, -1.0019e+02, 3.9344e+01, -3.1344e+01, 3.8562e+01, 5.9961e+00, 6.2219e+01, -1.0477e+01, 1.7750e+01, 2.9938e+01, 7.5830e-01, -2.7516e+01, 7.2188e+01, -2.3406e+01, 1.1617e+01, 6.5125e+01, 6.5078e+00, 6.7812e+01, 4.6812e+01, 7.7344e+00, 6.8562e+01, 5.6719e+00, 2.3125e+01, 6.7562e+01, 9.3750e+00, 5.2094e+01, -8.6562e+01, 1.2695e+01, 3.3562e+01, 2.9734e+01, 5.2250e+01, 9.5469e+00, -7.4414e+00, -2.0125e+01, 1.8145e+00, 7.8438e+01, -4.8125e+01 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', { 5,4,3 }, { 14.5042902, -4.43686799, 2.847406, 92.079556, -25.36761168, 2.94630572, -1.515069, -4.87137291, -50.29369639, 32.128515, -5.21515376, -9.41983935,-20.5835293, 24.61614501, -44.28390394, 37.1647167, -21.30142676, -38.52221293, -29.26009994, 14.40679768, 45.62757638, -11.550021, 36.44083018, -64.71012983,-10.435098, - 10.28950082, - 78.74044941, 22.1427147, 19.72198103, 14.40435988, 10.699559, 9.46744852, - 18.5778351 , -7.6957283, 39.31166179, 7.41657542, 7.245035, 28.48336771, - 26.88963173, 47.0880442, - 0.13584441, - 35.60035823, 43.2050762, - 18.47048906, - 31.11782117, 47.642019, - 18.83162118, - 21.50836396,-33.788558, 22.87507047, 75.34330791, 33.445396, 9.25395257, 0.10229474, -3.8078287, -8.02985955, 11.71587638, 41.0993915, -43.90830496, -34.46396749 }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_5) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 5,3,4 }, { 1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', { 5,3,4 }, { 36.628319, 38.600643,-40.624989, 18.231001, - 14.822637, - 2.479566, - 8.965780, 2.223851, -16.561626,-96.205162,-52.255379,-36.527435,-51.546139,2.234915, 20.914114, 8.785358, 32.552223, -3.356598, 9.069552, 1.393482,36.029255, 4.824605,- 9.972263,11.058715, 15.947105, 55.283543, 36.845627, -29.750486,0.887228, 6.534475, -21.794132,34.155693, -89.929497,39.562351, 27.276817,31.359871, 8.149521, 13.673355, 1.104303, 68.774300, 2.236881, 13.216944, - 3.555702,- 3.225931,3.063015, - 36.134724,58.302204, 8.477802, 38.695396,27.181587, - 14.157411,7.157054, 11.714512, 22.148155, 11.580557, - 27.204905,7.120562, 21.992094, 2.406748, - 6.265247, }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, { 1 });
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_6) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('c', { 3,5,4 }, { 1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
try {
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
ASSERT_EQ(Status::THROW(), result->status());
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
catch (std::exception & e) {
|
|
|
|
nd4j_printf("Error should be here `%s'. It's OK.\n", e.what());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_rgb_to_yuv_7) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray rgbs('f', { 2, 2, 3 }, { 1.7750e+01f,-7.1062e+01f, -1.0019e+02f, -2.3406e+01f,5.2094e+01f,9.5438e+01f, -6.7461e+00f,3.8562e+01f, 6.5078e+00f, 3.3562e+01f,-5.8844e+01f,2.2750e+01f }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('f', { 2,2,3 }, { 36.628319,38.600643, -40.624989,18.231001, -14.822637,-2.479566, -8.965780, 2.223851, -16.561626,- 96.205162,-52.255379, -36.527435 }, sd::DataType::FLOAT32);
|
2020-01-28 16:23:07 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::rgb_to_yuv op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &rgbs }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_1) {
|
|
|
|
// rank 1
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray yuv('c', { 3 }, { 55.14 , 71.2872001, -39.6005542 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('c', { 3 }, { 10, 50, 200 }, sd::DataType::FLOAT32);
|
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_2) {
|
|
|
|
// rank 1
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray yuv('f', { 3 }, { 55.14, 71.2872001, -39.6005542 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray expected('f', { 3 }, { 10, 50, 200 }, sd::DataType::FLOAT32);
|
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
2020-01-28 16:23:07 +01:00
|
|
|
|
2019-12-24 16:30:54 +01:00
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_3) {
|
|
|
|
// rank 2
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('c', { 3, 4 }, { -9.4, 9.9, 9.7, 9.0, 1.14, 1.01, 1.11, 9.6, 1.05, 10.0, 1.03, 10.22 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yuv('c', { 3, 4 }, { -2.021720, 4.692970, 3.669290, 9.491281, 1.511627, 2.611648, -1.298824, 0.358612, -6.472839, 4.568039, 5.290639, -0.430992 }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, { 0 });
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_4) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('c', { 5,4,3 }, { 1.7750e+01, 1.4602e+01, 5.4883e+00, 9.5438e+01, 1.0038e+02, 4.0531e+01, -5.8844e+01, 2.9609e+01, -1.1414e+01, 2.1391e+01, 3.9656e+01, 2.1531e+01, -7.1062e+01, -4.5859e+00, 2.9438e+01, -6.7461e+00, 6.7938e+01, -6.1211e+00, 2.2750e+01, -6.1438e+01, 1.5404e-02, -8.5312e+01, 1.1641e+01, 6.2500e+01, -1.0019e+02, 3.9344e+01, -3.1344e+01, 3.8562e+01, 5.9961e+00, 6.2219e+01, -1.0477e+01, 1.7750e+01, 2.9938e+01, 7.5830e-01, -2.7516e+01, 7.2188e+01, -2.3406e+01, 1.1617e+01, 6.5125e+01, 6.5078e+00, 6.7812e+01, 4.6812e+01, 7.7344e+00, 6.8562e+01, 5.6719e+00, 2.3125e+01, 6.7562e+01, 9.3750e+00, 5.2094e+01, -8.6562e+01, 1.2695e+01, 3.3562e+01, 2.9734e+01, 5.2250e+01, 9.5469e+00, -7.4414e+00, -2.0125e+01, 1.8145e+00, 7.8438e+01, -4.8125e+01 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yuv('c', { 5,4,3 }, { 14.5042902, -4.43686799, 2.847406, 92.079556, -25.36761168, 2.94630572, -1.515069, -4.87137291, -50.29369639, 32.128515, -5.21515376, -9.41983935,-20.5835293, 24.61614501, -44.28390394, 37.1647167, -21.30142676, -38.52221293, -29.26009994, 14.40679768, 45.62757638, -11.550021, 36.44083018, -64.71012983,-10.435098, -10.28950082, -78.74044941, 22.1427147, 19.72198103, 14.40435988, 10.699559, 9.46744852, -18.5778351 , -7.6957283, 39.31166179, 7.41657542, 7.245035, 28.48336771, -26.88963173, 47.0880442, -0.13584441, -35.60035823, 43.2050762, -18.47048906, -31.11782117, 47.642019, -18.83162118, -21.50836396,-33.788558, 22.87507047, 75.34330791, 33.445396, 9.25395257, 0.10229474, -3.8078287, -8.02985955, 11.71587638, 41.0993915, -43.90830496, -34.46396749 }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_5) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('c', { 5,3,4 }, { 1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yuv('c', { 5,3,4 }, { 36.628319, 38.600643,-40.624989, 18.231001, -14.822637, -2.479566, -8.965780, 2.223851, -16.561626,-96.205162,-52.255379,-36.527435,-51.546139,2.234915, 20.914114, 8.785358, 32.552223, -3.356598, 9.069552, 1.393482,36.029255, 4.824605,-9.972263,11.058715, 15.947105, 55.283543, 36.845627, -29.750486,0.887228, 6.534475, -21.794132,34.155693, -89.929497,39.562351, 27.276817,31.359871, 8.149521, 13.673355, 1.104303, 68.774300, 2.236881, 13.216944, -3.555702,-3.225931,3.063015, -36.134724,58.302204, 8.477802, 38.695396,27.181587, -14.157411,7.157054, 11.714512, 22.148155, 11.580557, -27.204905,7.120562, 21.992094, 2.406748, -6.265247, }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, { 1 });
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_6) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray yuv('c', { 3,5,4 }, { 1.7750e+01f, -7.1062e+01f, -1.0019e+02f,-2.3406e+01f, 5.2094e+01f, 9.5438e+01f, -6.7461e+00f, 3.8562e+01f, 6.5078e+00f,3.3562e+01f, -5.8844e+01f, 2.2750e+01f, -1.0477e+01f, 7.7344e+00f, 9.5469e+00f,2.1391e+01f, -8.5312e+01f, 7.5830e-01f,2.3125e+01f, 1.8145e+00f, 1.4602e+01f,-4.5859e+00f, 3.9344e+01f, 1.1617e+01f,-8.6562e+01f, 1.0038e+02f, 6.7938e+01f,5.9961e+00f, 6.7812e+01f, 2.9734e+01f,2.9609e+01f, -6.1438e+01f, 1.7750e+01f,6.8562e+01f, -7.4414e+00f, 3.9656e+01f,1.1641e+01f, -2.7516e+01f, 6.7562e+01f,7.8438e+01f, 5.4883e+00f, 2.9438e+01f,-3.1344e+01f, 6.5125e+01f, 1.2695e+01f,4.0531e+01f, -6.1211e+00f, 6.2219e+01f,4.6812e+01f, 5.2250e+01f, -1.1414e+01f,1.5404e-02f, 2.9938e+01f, 5.6719e+00f,-2.0125e+01f, 2.1531e+01f, 6.2500e+01f,7.2188e+01f, 9.3750e+00f, -4.8125e+01f }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
try {
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
ASSERT_EQ(Status::THROW(), result->status());
|
|
|
|
delete result;
|
|
|
|
}
|
|
|
|
catch (std::exception & e) {
|
|
|
|
nd4j_printf("Error should be here `%s'. It's OK.\n", e.what());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, test_yuv_to_rgb_7) {
|
|
|
|
// rank 3
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray expected('f', { 2, 2, 3 }, { 1.7750e+01f,-7.1062e+01f, -1.0019e+02f, -2.3406e+01f,5.2094e+01f,9.5438e+01f, -6.7461e+00f,3.8562e+01f, 6.5078e+00f, 3.3562e+01f,-5.8844e+01f,2.2750e+01f }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yuv('f', { 2,2,3 }, { 36.628319, 38.600643, -40.624989, 18.231001, -14.822637, -2.479566, -8.965780, 2.223851, -16.561626, -96.205162, -52.255379, -36.527435 }, sd::DataType::FLOAT32);
|
2019-12-24 16:30:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::yuv_to_rgb op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto result = op.evaluate({ &yuv }, {}, {});
|
2019-12-24 16:30:54 +01:00
|
|
|
auto output = result->at(0);
|
|
|
|
|
|
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
ASSERT_TRUE(expected.isSameShape(output));
|
|
|
|
ASSERT_TRUE(expected.equalsTo(output));
|
|
|
|
|
Oleh rgb to gray scale (#138)
* libnd4j: RgbToGrayscale op #8536 - raw implementation in user branch, need checks for integration and adding other orders
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 next step of merging images
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536, Revert merge of hsv_to_rgb and rgb_to_hsv as cause conflicts in naming need refactoring before merge, implementation of rbg_to_grs added
* libnd4j: RgbToGrayscale op #8536 imlementation and conflict resolve
* libnd4j: RgbToGrayscale op #8536 merged operations with images into image, renamed methods and files
* libnd4j: RgbToGrayscale op #8536 added test for rgbToGrayScale, need clarification and fixed tests case run
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* libnd4j: RgbToGrayscale op #8536 bug fixing and need review
* libnd4j: RgbToGrayscale op #8536 some additional corrections after review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - minor corrections in rgbToGrs test1
Signed-off-by: Yurii <iuriish@yahoo.com>
* libnd4j: RgbToGrayscale op #8536, corrected tests and rbf_to_grs, fixed problems, refactoring, need review
* libnd4j: RgbToGrayscale op #8536 fix for 'f' order in rgbToGrs
* libnd4j: RgbToGrayscale op #8536 fixed several bugs with dimC, test case refactoring and improve
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add cuda kernel for rgbToGrs op
Signed-off-by: Yurii <iuriish@yahoo.com>
* - fix linkage errors
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2019-12-20 18:59:29 +01:00
|
|
|
delete result;
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test1) {
|
|
|
|
|
|
|
|
// same shape
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray x('c', { 2,2,2 }, { 4,3,2,5,7,8,-9,-12 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray y('c', { 2,2,2 }, { 2,3,-2,4,-1,-4,10,8 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdz('c', { 2,2,2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdxExp('c', { 2,2,2 }, { 8, 27, -0.25, 500, -0.0204082, -0.000122, -3.87420e+09, -2.86654e+08 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExp('c', { 2,2,2 }, { 22.18071, 29.66253, 0.17329, 1005.89874, 0.27799, 0.00051, 0, 0 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
dLdz.assign(1.0);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto results = op.evaluate({ &x, &y, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdx = results->at(0);
|
|
|
|
auto* dLdy = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExp.isSameShape(dLdx));
|
|
|
|
ASSERT_TRUE(dLdxExp.equalsTo(dLdx));
|
|
|
|
ASSERT_TRUE(dLdyExp.isSameShape(dLdy));
|
|
|
|
ASSERT_TRUE(dLdyExp.equalsTo(dLdy));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test2) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray x('c', { 1,2,3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray y('c', { 3,2,1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdz('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExp('c', { 1,2,3 }, { 16.8, 19.2, 21.6, 24., 26.4, 28.8 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExp('c', { 3,2,1 }, { 13.30843, 33.27106, 53.2337, 73.19634, 93.15898, 113.12162 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
x.assign(4.0);
|
|
|
|
y.assign(2.0);
|
|
|
|
dLdz.linspace(0.1, 0.1);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto results = op.evaluate({ &x, &y, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdx = results->at(0);
|
|
|
|
auto* dLdy = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExp.isSameShape(dLdx));
|
|
|
|
ASSERT_TRUE(dLdxExp.equalsTo(dLdx));
|
|
|
|
ASSERT_TRUE(dLdyExp.isSameShape(dLdy));
|
|
|
|
ASSERT_TRUE(dLdyExp.equalsTo(dLdy));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test3) {
|
|
|
|
|
|
|
|
// y - same shape as dLdz
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray xY('c', { 1,2,3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yY('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExpY('c', { 1,2,3 }, { 16.8, 19.2, 21.6, 24. , 26.4, 28.8 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExpY('c', { 3,2,3 }, { 2.21807, 4.43614, 6.65421, 8.87228, 11.09035, 13.30843, 15.5265 , 17.74457, 19.96264, 22.18071, 24.39878, 26.61685, 28.83492, 31.05299, 33.27106, 35.48914, 37.70721, 39.92528 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdz('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
xY.assign(4.0);
|
|
|
|
yY.assign(2.0);
|
|
|
|
dLdz.linspace(0.1, 0.1);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsY = op.evaluate({ &xY, &yY, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsY->status());
|
|
|
|
|
|
|
|
auto* dLdxY = resultsY->at(0);
|
|
|
|
auto* dLdyY = resultsY->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpY.isSameShape(dLdxY));
|
|
|
|
ASSERT_TRUE(dLdxExpY.equalsTo(dLdxY));
|
|
|
|
ASSERT_TRUE(dLdyExpY.isSameShape(dLdyY));
|
|
|
|
ASSERT_TRUE(dLdyExpY.equalsTo(dLdyY));
|
|
|
|
|
|
|
|
delete resultsY;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test4) {
|
|
|
|
|
|
|
|
// x - same shape ad dLdz
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray yX('c', { 1,2,3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray xX('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExpX('c', { 3,2,3 }, { 3.2, 6.4, 9.6, 12.8, 16. , 19.2, 22.4, 25.6, 28.8, 32. , 35.2, 38.4, 41.6, 44.8, 48., 51.2, 54.4, 57.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExpX('c', { 1,2,3 }, { 23.28975, 26.61685, 29.94396, 33.27106, 36.59817, 39.92528 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdz('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
dLdz.linspace(0.1, 0.1);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
xX.assign(2.0);
|
|
|
|
yX.assign(4.0);
|
|
|
|
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsX = op.evaluate({ &xX, &yX, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsX->status());
|
|
|
|
|
|
|
|
auto* dLdxX = resultsX->at(0);
|
|
|
|
auto* dLdyX = resultsX->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpX.isSameShape(dLdxX));
|
|
|
|
ASSERT_TRUE(dLdxExpX.equalsTo(dLdxX));
|
|
|
|
ASSERT_TRUE(dLdyExpX.isSameShape(dLdyX));
|
|
|
|
ASSERT_TRUE(dLdyExpX.equalsTo(dLdyX));
|
|
|
|
|
|
|
|
delete resultsX;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test5) {
|
|
|
|
|
|
|
|
// both single array
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray xConst('c', { 1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yConst('c', { 1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdz('c', { 1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdxExp('c', { 1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExp('c', { 1 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
xConst.assign(3.0);
|
|
|
|
yConst.assign(4.0);
|
|
|
|
dLdz.assign(1.0);
|
|
|
|
|
|
|
|
dLdxExp.assign(4.0 * pow(3, 3));
|
|
|
|
dLdyExp.assign(pow(3, 4) * log(3));
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto results = op.evaluate({ &xConst, &yConst, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdx = results->at(0);
|
|
|
|
auto* dLdy = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExp.isSameShape(dLdx));
|
|
|
|
ASSERT_TRUE(dLdxExp.equalsTo(dLdx));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdyExp.isSameShape(dLdy));
|
|
|
|
ASSERT_TRUE(dLdyExp.equalsTo(dLdy));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test6) {
|
|
|
|
|
|
|
|
// x single array
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray xConst('c', { 1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray y('c', { 2, 2, 2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdzC('c', { 2, 2, 2 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
xConst.assign(2.0);
|
|
|
|
y.assign(4.0);
|
|
|
|
dLdzC.linspace(0.1, 0.1);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExpXC('c', { 1 }, std::vector<double>{ 115.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExpXC('c', { 2, 2, 2 }, { 1.10904, 2.21807, 3.32711, 4.43614, 5.54518, 6.65421, 7.76325, 8.87228 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsXC = op.evaluate({ &xConst, &y, &dLdzC }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsXC->status());
|
|
|
|
|
|
|
|
auto* dLdxXC = resultsXC->at(0);
|
|
|
|
auto* dLdyXC = resultsXC->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpXC.isSameShape(dLdxXC));
|
|
|
|
ASSERT_TRUE(dLdxExpXC.equalsTo(dLdxXC));
|
|
|
|
ASSERT_TRUE(dLdyExpXC.isSameShape(dLdyXC));
|
|
|
|
ASSERT_TRUE(dLdyExpXC.equalsTo(dLdyXC));
|
|
|
|
|
|
|
|
delete resultsXC;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test7) {
|
|
|
|
|
|
|
|
// Y - scalar
|
|
|
|
auto Y = NDArrayFactory::create<float>(2.f);
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray x('c', { 2, 2, 2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdzC('c', { 2, 2, 2 }, sd::DataType::FLOAT32);
|
2020-01-28 16:23:07 +01:00
|
|
|
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
dLdzC.linspace(0.1, 0.1);
|
|
|
|
x = 4.f;
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExpYs('c', { 2, 2, 2 }, { 0.8, 1.6, 2.4, 3.2, 4., 4.8, 5.6, 6.4 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
auto dLdyExpYs = NDArrayFactory::create<float>(79.85056f);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsYs = op.evaluate({ &x, &Y, &dLdzC }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsYs->status());
|
|
|
|
|
|
|
|
auto* dLdxY = resultsYs->at(0);
|
|
|
|
auto* dLdyY = resultsYs->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpYs.isSameShape(dLdxY));
|
|
|
|
ASSERT_TRUE(dLdxExpYs.equalsTo(dLdxY));
|
|
|
|
ASSERT_TRUE(dLdyExpYs.isSameShape(dLdyY));
|
|
|
|
ASSERT_TRUE(dLdyExpYs.equalsTo(dLdyY));
|
|
|
|
|
|
|
|
delete resultsYs;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test8) {
|
|
|
|
// both scalars
|
|
|
|
|
|
|
|
auto X = NDArrayFactory::create<float>(4.f);
|
|
|
|
auto Y = NDArrayFactory::create<float>(2.f);
|
|
|
|
NDArray dLdz = NDArrayFactory::create<float>(0.1f);
|
|
|
|
|
|
|
|
NDArray dLdxExp = NDArrayFactory::create<float>(2.f*4.f*0.1f);
|
|
|
|
|
|
|
|
NDArray dLdyExp = NDArrayFactory::create<float>(pow(4.f, 2.f) * log(4.f) * 0.1f);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto results = op.evaluate({ &X, &Y, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdx = results->at(0);
|
|
|
|
auto* dLdy = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExp.isSameShape(dLdx));
|
|
|
|
ASSERT_TRUE(dLdxExp.equalsTo(dLdx));
|
|
|
|
ASSERT_TRUE(dLdyExp.isSameShape(dLdy));
|
|
|
|
ASSERT_TRUE(dLdyExp.equalsTo(dLdy));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test9) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
// diff shapes
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray x('c', { 3,2,1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray y('c', { 1,2,3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdz('c', { 3,2,3 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExp('c', { 3,2,1 }, { 4.8, 12., 19.2, 26.4, 33.6, 40.8 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExp('c', { 1,2,3 }, { 46.57949, 53.2337 , 59.88792, 66.54213, 73.19634, 79.85056 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
x.assign(4.0);
|
|
|
|
y.assign(2.0);
|
|
|
|
dLdz.linspace(0.1, 0.1);
|
|
|
|
|
2020-01-30 08:07:24 +01:00
|
|
|
auto results = op.evaluate({ &x, &y, &dLdz }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdx = results->at(0);
|
|
|
|
auto* dLdy = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExp.isSameShape(dLdx));
|
|
|
|
ASSERT_TRUE(dLdxExp.equalsTo(dLdx));
|
|
|
|
ASSERT_TRUE(dLdyExp.isSameShape(dLdy));
|
|
|
|
ASSERT_TRUE(dLdyExp.equalsTo(dLdy));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test10) {
|
|
|
|
|
|
|
|
// diff shapes broadcastable
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray yB('c', { 1,2,3,1 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray xB('c', { 2,3,1 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdyExpB('c', { 1,2,3,1 }, { 2.21807, 4.43614, 6.65421, 8.87228, 11.09035, 13.30843 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdxExpB('c', { 2,3,1 }, { 0.8, 1.6, 2.4, 3.2, 4., 4.8 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdzB('c', { 1,2,3,1 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
dLdzB.linspace(0.1, 0.1);
|
|
|
|
xB.assign(4.0);
|
|
|
|
yB.assign(2.0);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsB = op.evaluate({ &xB, &yB, &dLdzB }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsB->status());
|
|
|
|
|
|
|
|
auto* dLdxB = resultsB->at(0);
|
|
|
|
auto* dLdyB = resultsB->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpB.isSameShape(dLdxB));
|
|
|
|
ASSERT_TRUE(dLdxExpB.equalsTo(dLdxB));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdyExpB.isSameShape(dLdyB));
|
|
|
|
ASSERT_TRUE(dLdyExpB.equalsTo(dLdyB));
|
|
|
|
|
|
|
|
delete resultsB;
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(DeclarableOpsTests15, Pow_BP_Test11) {
|
2020-02-13 18:59:35 +01:00
|
|
|
#ifdef FFAST_MATH
|
|
|
|
if (1 > 0)
|
|
|
|
return;
|
|
|
|
#endif
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray xB('c', { 3,2,1 }, { .4, 3, 5, .8, -9, -12 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray yB('c', { 1,2,3 }, { 3, -2, .4, -4, 10, .8 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdxExpB('c', { 3,2,1 }, { -5.994056, 39366.191406, 7.508829, -2.223537, -std::numeric_limits<float>::quiet_NaN(), -std::numeric_limits<float>::quiet_NaN() }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdyExpB('c', { 1,2,3 }, { 20.11211, -1.119612, -std::numeric_limits<float>::quiet_NaN(), -0.1076, 12974.389648, -std::numeric_limits<float>::quiet_NaN() }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdzB('c', { 3,2,3 }, { .1,.2,.3, .1,.2,.3, .1,.4,.1, .2,.1,.1, .3,.1,.5, .1, .7, .1 }, sd::DataType::FLOAT32);
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::Pow_bp op;
|
2020-01-30 08:07:24 +01:00
|
|
|
auto resultsB = op.evaluate({ &xB, &yB, &dLdzB }, {}, {});
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsB->status());
|
|
|
|
auto* dLdxB = resultsB->at(0);
|
|
|
|
auto* dLdyB = resultsB->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdxExpB.isSameShape(dLdxB));
|
|
|
|
for (int i = 0; i < dLdxB->lengthOf(); ++i) {
|
2020-03-02 10:49:41 +01:00
|
|
|
if (!sd::math::nd4j_isnan(dLdxB->e<float>(i)) && !sd::math::nd4j_isnan(dLdxExpB.e<float>(i)))
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_NEAR(dLdxB->e<float>(i), dLdxExpB.e<float>(i), 0.00001);
|
|
|
|
}
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdyExpB.isSameShape(dLdyB));
|
|
|
|
for (int i = 0; i < dLdyB->lengthOf(); ++i) {
|
2020-03-02 10:49:41 +01:00
|
|
|
if (!sd::math::nd4j_isnan(dLdyB->e<float>(i)) && !sd::math::nd4j_isnan(dLdyExpB.e<float>(i)))
|
Oleh powderev (#171)
* Libnd4j: Add broadcastable elementwise power derivative #7461 first step of Pow_bp operation implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some corrections of calculation steps
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some bug fixes, the PowDerevative op made broadcastable, add the raw tests for op, need refactoring to use broadcast ops
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed several bugs add broadcast support and tests, need to fix scalar+array and array+scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fixed bugs for scalar inputs, fixed multinomial tests, added tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 fised bugs for different shapes support, tests updated
* Libnd4j: Add broadcastable elementwise power derivative #7461 applied all possible variants via tiled arrays, add support of broadcast for Pow and PowDerivative ops, covered by tests, before review have to be replaced tiled implementation by applyTrueBroadcast
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 replaced tile by broadcast implementation, fixed issue with negative x input, corrected tests, need additional testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 added and corrected test cases, corrected implementation need review
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up
* Libnd4j: Add broadcastable elementwise power derivative #7461 code clean up, removed some tests, add tests with scalar
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 code improvement and clean up, split tests
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative #7461 some code clean up
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: Add broadcastable elementwise power derivative replace __isnanf by internal realization
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* pow_bp wrapper
* Fixed PowBp wrapper
* Tests added
* Test fixed
* Fix return type
* Disable powBp usage
* Pow backprop changed
Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-01-20 10:59:12 +01:00
|
|
|
ASSERT_NEAR(dLdyB->e<float>(i), dLdyExpB.e<float>(i), 0.00001);
|
|
|
|
}
|
|
|
|
|
|
|
|
delete resultsB;
|
|
|
|
}
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP1) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 1, 2, 3 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 1, 2, 4 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 4 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.1 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdA('c', { 1, 2, 3 }, { 3.3, 8.5, 13.36, 3.7, 9.54, 15. }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdB('c', { 1, 2, 4 }, { 3.38, 4.04, 4.7, 5.13, 3.83, 4.58, 5.33, 5.82 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,0,1, 2,0,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dLdA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dLdB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP2) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 1, 2, 3 }, { 2,2,2, 2,2,2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 1, 2, 3 }, { 3,3,3,3, 3,3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 1 }, { 1 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(B.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(B.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(A.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(A.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP3) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 2, 2 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 4, 2, 2 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2, 4.3, 4.4, 4.5, 4.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 4 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 3, 2, 2 }, { 3.9, 4., 4.1, 4.2, 9.82, 10.08, 10.34, 10.6, 15.74, 16.16, 16.58, 17. }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('c', { 4, 2, 2 }, { 4.07, 4.22, 4.37, 4.52, 4.82, 5., 5.18, 5.36, 5.57, 5.78, 5.99, 6.2, 6.32, 6.56, 6.8, 7.04 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP4) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 4, 1 }, { 0.4, 3, 5, 9, 23, 0.12, 8, 9, 0.1, 0, 124, 3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 4, 1 }, { 4, 13, .5, 19, 2.3, 1.2, 18, .9 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 2 }, { 1.1, 1.2, 1.3, 1.4, 1.5, 1.6 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdA('c', { 3, 4, 1 }, { 7.16, 15.74, 22.15, 21.98, 8.42, 18.58, 25.85, 25.96, 9.68, 21.42, 29.55, 29.94 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdB('c', { 2, 4, 1 }, { 30.49, 3.456, 201.9, 26.1, 32.84 , 3.768, 215.6, 28.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dLdA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dLdB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP5) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 4, 1, 1 }, { 0.4, 3, 5, 9, 23, 0.12, 8, 9, 0.1, 0, 124, 3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 4, 1, 1 }, { 4, 13, .5, 19, 2.3, 1.2, 18, .9 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 1, 2, 1 }, { 1.1,1.2,1.3,1.4,1.5,1.6 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdA('c', { 3, 4, 1, 1 }, { 7.16, 15.74, 22.15, 21.98, 8.42, 18.58, 25.85, 25.96, 9.68, 21.42, 29.55, 29.94 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdB('c', { 2, 4, 1, 1 }, { 30.49, 3.456, 201.9, 26.1, 32.84, 3.768, 215.6, 28.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dLdA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dLdB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP6) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 2, 2, 2 }, { 2,2, 2,2, 2,2, 2,2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 2, 2 }, { 3,3, 3,3, 3,3, 3,3 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto dLdC = NDArrayFactory::create<float>(1.f);
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 3,0,1,2, 3,0,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(B.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(B.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(A.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(A.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP7) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 4, 1 }, { 0.4, 3, 5, 9, 23, 0.12, 8, 9, 0.1, 0, 124, 3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 4, 1 }, { 4, 13, .5, 19, 2.3, 1.2, 18, .9 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 1, 2, 1 }, { 1.1, 1.2, 1.3, 1.4, 1.5, 1.6 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdA('c', { 3, 4, 1 }, { 7.16, 15.74, 22.15, 21.98, 8.42, 18.58, 25.85, 25.96, 9.68, 21.42, 29.55, 29.94 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdB('c', { 2, 4, 1 }, { 30.49, 3.456, 201.9, 26.1, 32.84, 3.768, 215.6, 28.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 1,1, 1,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dLdA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dLdB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP8) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 1, 1, 4, 3 }, { 0.4, 3, 5, 9, 23, 0.12, 8, 9, 0.1, 0, 124, 3 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 1, 1, 4, 2 }, { 4, 13, .5, 19, 2.3, 1.2, 18, .9 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 2 }, { 1.1,1.2,1.3,1.4,1.5,1.6 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdA('c', { 1, 1, 4, 3 }, { 20., 23.4, 26.8, 23.35, 27.25, 31.15, 3.97, 4.67, 5.37, 20.88, 24.66, 28.44 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdB('c', { 1, 1, 4, 2 }, { 11.84, 12.68, 39.98, 43.192, 20.65, 22.36, 165.7, 178.4 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 3,0,1,2, 3,0,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dLdA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dLdB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dLdB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP9) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 2, 2, 1 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 4, 2, 2 ,1 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2, 4.3, 4.4, 4.5, 4.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 1, 4, 1 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 3, 2, 2, 1 }, { 3.9, 4., 4.1, 4.2, 9.82, 10.08, 10.34, 10.6, 15.74, 16.16, 16.58, 17. }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('c', { 4, 2, 2, 1 }, { 4.07, 4.22, 4.37, 4.52, 4.82, 5., 5.18, 5.36, 5.57, 5.78, 5.99, 6.2, 6.32, 6.56, 6.8, 7.04 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP10) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 1, 2, 2, 3 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 1, 2, 2 ,4 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2, 4.3, 4.4, 4.5, 4.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 1, 3, 1, 4 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 1, 2, 2, 3 }, { 3.3, 8.5, 13.7, 3.7, 9.54, 15.38, 4.1, 10.58, 17.06, 4.5, 11.62, 18.74 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('c', { 1, 2, 2, 4 }, { 3.38, 4.04, 4.7, 5.36, 3.83, 4.58, 5.33, 6.08, 4.28, 5.12, 5.96, 6.8, 4.73, 5.66, 6.59, 7.52 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP11) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 2, 2, 3 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 2 ,4 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2, 4.3, 4.4, 4.5, 4.6 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dLdC('c', { 3, 4 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 2, 2, 3 }, { 3.3, 8.5, 13.7, 3.7, 9.54, 15.38, 4.1, 10.58, 17.06, 4.5, 11.62, 18.74 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('c', { 2, 2, 4 }, { 3.38, 4.04, 4.7, 5.36, 3.83, 4.58, 5.33, 6.08, 4.28, 5.12, 5.96, 6.8, 4.73, 5.66, 6.59, 7.52 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 2,0,1, 2,0,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP12) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 2, 2, 3 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('c', { 2, 2 ,3 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
NDArray dLdC('c', { 2, 3, 2, 3 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
|
|
|
1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2., 2.1, 2.2, 2.3, 2.4,
|
2020-03-02 10:49:41 +01:00
|
|
|
2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 2, 2, 3 }, { 7.66, 20.26, 32.86, 8.29, 21.97, 35.65, 45.46, 58.06, 70.66, 49.33, 63.01, 76.69 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('c', { 2, 2, 3 }, { 25.86, 27.36, 28.86, 28.74, 30.42, 32.1, 30.36, 31.86, 33.36, 33.78, 35.46, 37.14 }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 1,1, 1,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP13) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 3, 2, 2 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2 }, sd::DataType::DOUBLE);
|
|
|
|
NDArray B('c', { 3, 2, 2 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
NDArray dLdC('c', { 3, 2, 3, 2 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
|
|
|
1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2., 2.1, 2.2, 2.3, 2.4,
|
2020-03-02 10:49:41 +01:00
|
|
|
2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 3, 2, 2 }, { 7.79, 20.57, 8.21, 21.71, 33.35, 46.13, 35.21, 48.71, 58.91, 71.69, 62.21, 75.71 }, sd::DataType::DOUBLE);
|
|
|
|
NDArray dB('c', { 3, 2, 2 }, { 26.49, 28.02, 28.41, 30.06, 29.55, 31.08, 31.71, 33.36, 32.61, 34.14, 35.01, 36.66 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 1,1, 1,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP14) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 2, 2, 2, 2 }, { 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray B('c', { 2, 2, 2, 2 }, { 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4., 4.1, 4.2, 4.3, 4.4, 4.5, 4.6 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
NDArray dLdC('c', { 2, 2, 2, 2, 2, 2 }, { .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
|
|
|
1.3, 1.4, 1.5, 1.6, .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
|
|
|
1.3, 1.4, 1.5, 1.6, .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
|
|
|
1.3, 1.4, 1.5, 1.6, .1, .2, .3, .4, .5, .6, .7, .8, .9, 1, 1.1, 1.2,
|
2020-03-02 10:49:41 +01:00
|
|
|
1.3, 1.4, 1.5, 1.6 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 2, 2, 2, 2 }, { 13.88, 37.24, 13.88, 37.24, 15.32, 41.24, 15.32, 41.24, 13.88, 37.24, 13.88, 37.24, 15.32, 41.24, 15.32, 41.24 }, sd::DataType::DOUBLE);
|
|
|
|
NDArray dB('c', { 2, 2, 2, 2 }, { 10.76, 12.88, 15., 17.12, 12.36, 14.8, 17.24, 19.68, 19.24, 21.36, 23.48, 25.6, 22.12, 24.56, 27., 29.44 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
auto resultsBP = op_bp.evaluate({ &A, &B, &dLdC }, {}, { 1,1, 1,1 }, {});
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, resultsBP->status());
|
|
|
|
|
|
|
|
auto* dLdAbp = resultsBP->at(0);
|
|
|
|
auto* dLdBbp = resultsBP->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdAbp));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdAbp));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdBbp));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdBbp));
|
|
|
|
|
|
|
|
delete resultsBP;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP15) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('c', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::FLOAT32);
|
|
|
|
NDArray B('f', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdC('f', { 2, 2 }, { 23.0, 24.44, 2.0, 26. }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dA('c', { 2, 2, 3 }, { 27., 127., 227., 77., 177., 277., 76.44, 278.20001, 479.96002, 177.32, 379.08001, 580.839966 }, sd::DataType::FLOAT32);
|
|
|
|
NDArray dB('f', { 2, 2, 3 }, { 194.08, 184., 336.4, 268., 241.52, 212., 383.839996, 296., 288.96002, 240., 431.27999, 324. }, sd::DataType::FLOAT32);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul_bp op;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
auto results = op.evaluate({ &A, &B, &dLdC }, {}, { 2,1,2,2,1,2 });
|
|
|
|
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
|
|
|
|
auto* dLdA = results->at(0);
|
|
|
|
auto* dLdB = results->at(1);
|
|
|
|
|
|
|
|
ASSERT_TRUE(dA.isSameShape(*dLdA));
|
|
|
|
ASSERT_TRUE(dA.equalsTo(*dLdA));
|
|
|
|
|
|
|
|
ASSERT_TRUE(dB.isSameShape(*dLdB));
|
|
|
|
ASSERT_TRUE(dB.equalsTo(*dLdB));
|
|
|
|
|
|
|
|
delete results;
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP16) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('f', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::DOUBLE);
|
|
|
|
NDArray B('c', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdC('c', { 2, 2 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
const OpArgsHolder argsHolderFF({ &A, &B }, {}, { 2,1,2, 2,1,2 });
|
|
|
|
const OpArgsHolder argsHolderBP({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 });
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul op;
|
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
const bool isGradCorrect = GradCheck::checkGrad(op, op_bp, argsHolderFF, argsHolderBP, {1,0});
|
|
|
|
ASSERT_TRUE(isGradCorrect);
|
|
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
|
|
TEST_F(DeclarableOpsTests15, TestTensorMmul_BP17) {
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray A('f', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::DOUBLE);
|
|
|
|
NDArray B('f', { 2, 2, 3 }, { 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12. }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
NDArray dLdC('c', { 2, 2 }, sd::DataType::DOUBLE);
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
const OpArgsHolder argsHolderFF({ &A, &B }, {}, { 2,1,2, 2,1,2 });
|
|
|
|
const OpArgsHolder argsHolderBP({ &A, &B, &dLdC }, {}, { 2,1,2, 2,1,2 });
|
|
|
|
|
2020-03-02 10:49:41 +01:00
|
|
|
sd::ops::tensormmul op;
|
|
|
|
sd::ops::tensormmul_bp op_bp;
|
Oleh tenzor mmul (#231)
* Libnd4j: TensorMMul backprop op #8174, raw implementation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed issue of incorrect axes definition, add tests based on TF, need additional testing for case dLdC not equal 1
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 fixed bp algorithm, axes definition, need some mode testing with different orders combination f,c; c,f f,f and add some checks for inputs
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 some checks and corrections added tests, exists the problem with different input orders support A-f B-c and A-f B-f
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* Libnd4j: TensorMMul backprop op #8174 sync master
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
Signed-off-by: Yurii <iuriish@yahoo.com>
* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
Signed-off-by: Oleg <oleg.semeniv@gmail.com>
* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
Signed-off-by: Yurii <iuriish@yahoo.com>
* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on problem of wrong shape evaluation during permute/reshape procedures
Signed-off-by: Yurii <iuriish@yahoo.com>
* - still looking for bug reason in reshape/permute stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in transform cuda native ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in NDArray::assign
Signed-off-by: Yurii <iuriish@yahoo.com>
* - remove old shape::reshape stuff
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct bug in tensorDot which had to do with wrong pointers assigments
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Oleh <oleg.semeniv@gmail.com>
2020-02-13 18:33:54 +01:00
|
|
|
|
|
|
|
const bool isGradCorrect = GradCheck::checkGrad(op, op_bp, argsHolderFF, argsHolderBP, { 1,0 });
|
|
|
|
ASSERT_TRUE(isGradCorrect);
|
|
|
|
}
|
|
|
|
|