* initial set of include changes
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* one more tweak
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* few more rearrangements
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* few more rearrangements
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* few more rearrangements
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* cuda includes rearrangements
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* java update
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* = namespace changed to sd
- few CMake variables renamed with SD_ prefix
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* java update
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* LoopKind minor fix
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* few more changes
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* few more changes
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* few more changes
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* sanitizer is optional now
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* dev tests updated
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* few more changes
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* last update
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* java update
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* #8565 Normalizer toString/hashcode
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* #8731 ImagePreProcessingScaler lables/segmentation fix
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* #8691 Fix SameDiffLayer/Vertx finetuning and parameter setting support
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* #8663 DL4J embedding layer weight init - don't depend on vocab size
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* EmbeddingLayer test tweak
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* - profiling of concat op (both cuda and cpu)
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* better comparison for large concat
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* - further improving of concat op
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* some loggin
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* - add possibility to verify presence of trailing unities in shape and set strides/ews correspondingly
- restrict second simple case in concat op to c order only
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* - move concat op to specials_single.cpp file
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* - get rid of second concat op declaration in transforms.cpp file
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* Libnd4j: TensorMMul backprop op #8174, raw implementation
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* Libnd4j: TensorMMul backprop op #8174 merge master and some corrections
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* Libnd4j: TensorMMul backprop op #8174 algorithm update, need testing, sync with master
* Libnd4j: TensorMMul backprop op #8174 fixed incorrect B axes calculation
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* Libnd4j: TensorMMul backprop op #8174 optimize axes identification and fix bug of indeces overlapping, added first test. need testing with different shapes
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* Libnd4j: TensorMMul backprop op #8174 some fixes and improvements need more testing
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* Libnd4j: TensorMMul backprop op #8174 fixed order of matrix multiply
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* 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
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* Libnd4j: TensorMMul backprop op #8174 fixed scalar case add test
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* 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
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* 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
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* Libnd4j: TensorMMul backprop op #8174 sync master
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* - correct bug in MmulHelper::tensorDot(a, b, c, axes_a, axes_b,permutForC)
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* Libnd4j: TensorMMul backprop op #8174 code clean up and refactoring
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* - add check for linspase ordered permutations in ShapeUtils::evalShapeForTensorDot
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* - provide additional code in shape::reshape stuff in order to reduce amount of allocation/copy operations during reshaping procedure
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* - further work on problem of wrong shape evaluation during permute/reshape procedures
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* - still looking for bug reason in reshape/permute stuff
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* - correct bug in transform cuda native ops
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* - correct bug in NDArray::assign
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* - remove old shape::reshape stuff
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* - add possibility to disable copy of old buffer to new buffer during reshape operation in NDArray class
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* - correct bug in tensorDot which had to do with wrong pointers assigments
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Co-authored-by: Oleh <oleg.semeniv@gmail.com>
* Gradients tests added
* Fix for Standard deviation serialization + test
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* More fixes
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* Test fixed
* Spark config driver host config for CI
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* Op validation timeout increase
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* Gradient check - fix for low probability test failure due to randomly all 0s mask
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* special workaround methods for DataBuffer.write
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* one test removed
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* more of unsynced
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* missing asLong for BaseCudaDataBuffer
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* linear equations systems solve op. Initial commit.
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* Fixed compiling issues.
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* Linear equations systems solve. The next stage commit.
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* Added test for linear equations systems solve operation.
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* Added additional test and fixed lower matrix retrievance.
* Implementation for solve of the systems of linear equations."
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* Refactored permutation generation.
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* Added restore for permutations batched with cuda helper for solve op.
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* Finished cuda implementation for solve op helpers.
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* Refactored cpu helpers for solve op.
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* Fix gtest output on Windows
* Fixed issue with permutation matrix for cuda implementation.
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* Fixed issue with permutation matrix for cpu implementation.
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* Eliminated waste comments.
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* LinearSolve added
* Mapping added
* Javadoc added
* Refactored implementation of triangular_solve helpers and tests for solve matrix equations generally.
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* Added a test for solve op.
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* Solve test added
* Fix for TF import
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* - range op now accepts dargs
- dargs now can be in signature
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* range dtype java side
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* linspace fix
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* lin_space fix for scalar outputs
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* initial commit
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* - one more test for OneHot with dtype
- one more signature in Nd4j
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* ones_as/zeros_as now accept dtype
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* one more test
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* - more updates for configurable data types
- ones_as/zeros_as java side + tests
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* few c++ tests fixed
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* few more changes around DArgs
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* Cleanup modules
* Moving subprojects to nd4j-api
* Project cleanup
* Dropped AWS sub-project
* dl4j-util moved to core
* dl4j-perf moved to core
* Tests coverage
* Revert "Moving subprojects to nd4j-api"
This reverts commit bc6eb573c6b60c407ade47172c5d204725077e6b.
* Moved nd4j-buffer and nd4j-context to nd4j-api
* Rolled back change
* Revert "Project cleanup"
This reverts commit 64ac7f369b2d968f7be437718034f093fc886ffc.
* Datavec cleaned up
* Revert "Moved nd4j-buffer and nd4j-context to nd4j-api"
This reverts commit 75f4e8da80d2551e44e1251dd6c5923289fff8e1.
# Conflicts:
# nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/opvalidation/ReductionBpOpValidation.java
* Resolve conflict
* Compilation fixed.
* nd4j-context and nd4j-buffer moved to nd4j-api
* Fixed TF mapping for mmul
* Fix for dl4j-cuda tests
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* Move last few tests from deeplearning4j-nn to -core
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* Remove incorrect TF import mapping for TensorMmul op
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* Cleaned TF mapping
* Fix path for test results on windows
* Remove old dependency
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* One more attempt to fix path for test results on windows
* fixup! One more attempt to fix path for test results on windows
* fixup! One more attempt to fix path for test results on windows
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* missing alloc validation in RandomGenerator for CUDA
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* set error message if rng alloc failed
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* check for error code during RNG creation in java
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* nd4j-aeron profiles
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* nd4j-aeron profiles
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* skip one long test
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* skip one long test
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* kryo profile
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* few more profiles
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* few more profiles
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* few more profiles
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* Add maven profile + base tests methods for integration tests
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* Switch from system property to environment variable; seems more reliable in intellij
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* Add nd4j-common-tests module, and common base test; cleanup
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* Ensure all ND4J tests extend BaseND4JTest
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* Test spam reduction, import fix
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* Add test logging to nd4j-aeron
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* Fix unintended change
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* Reduce sprint test log spam
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* More test spam cleanup
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* Significantly speed up TSNE tests
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* W2V iterator test unit/integration split
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* More NLP test speedups
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* Avoid debug/verbose mode leaking between tests
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* test tweak
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* Arbiter extends base DL4J test
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* Arbiter test speedup
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* nlp-uima test speedup
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* More test speedups
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* Fix ND4J base test
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* Few small ND4J test speed improvements
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* DL4J tests speedup
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* More tweaks
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* Even more test speedups
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* More tweaks
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* Various test fixes
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* More test fixes
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* Add ability to specify number of threads for C++ ops in BaseDL4JTest and BaseND4JTest
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* nd4j-aeron test profile fix for CUDA
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* Added qr op implementation. Initial version.
* Fixed doc for qr op.
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* Implementation of QR decomposition. CPU platform version.
* Added a pair of tests for qr op testing.
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* QR implementation.
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* Corrected norm using.
* Properly calculated intermediate results with QR decomposition.
* Another step to implement QR algorithm by householder.
* Cpu implementatio for QR decomposition. The first working edition.
* Corrected test to QR decomposition.
* Added tad multithreading with QR implementation.
* Finished cpu implementation for QR decomposition helpers.
* Refactored tests and improved multithreading.
* Refactored QR cpu implementation and update cuda implementation helpers.
* Cuda QR helper implementation. The first working edition.
* Eliminated waste prints.
* Restore multithreading with cuda implementation.
* Ops names corrected
* Refactored qr op helpers to optimize.
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* Eliminated waste manual ticking.
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* Refactored memory allocation to avoid waste memory usage.
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* Refactored matrixMinor method both for cuda and cpu platforms.
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* Refactored method of vmul to use raw buffers instead type conversion.
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* Refactored temporary array of matricies.
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Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
Co-authored-by: raver119 <raver119@gmail.com>
* Added implementation of the triangular_solve op.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Fixed compilation issues.
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* Added verification of input data and helpers facilities for triangular_solve op.'
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* Added cpu implementation for triangular_solve helpers.
* Added tests and implementation for upper triangular equations.
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* Added a pair of cases to tests.
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* Added multithreading with cpu helpers for triangular_solve op.
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* Added cuda implementation of triangular_solve op helpers.
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* Finished cuda implementation of triangular_solve helpers and tests.
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* Fixed copyright marks.
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* Corrected grammar errors with doc and error messages.
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* Refactored matricies processing with triangular_solve cuda helper implementation.
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* Added triangular_solve wrapper
* Fixed mapping
* Added processing for adjoint with cpu helpers of triangular_solve op implementation.
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* Added implementation for adjoint routine with cuda platform.
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* Added multithreading with adjoint routine for cpu platform.
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Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* Added implementation for resize_area op. Initial commit.
* Added implementation of resize_area op. Initial revision.
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* Corrected resizeArea functor call.
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* Implementation of resize_area. Cpu platform helpers.
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* Implementation for resize_area helpers. The first part revision.
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* Added a set of tests for resize_area op.
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* Cuda implementation for resize_area. Initial approach.
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* Adding multithreading for resize_area algorithm.
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* Cuda implementation of resize_area helpers. Shared memory approach.
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* Refactored resizeAreaKernel with cuda implementation.
* Eliminated compilation errors.
* ResizeArea helpers for cuda platform. The first working revision.
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* Added test for batched resize_area op testing.
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* Implementation of resize_are for cuda platform and tests.
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* Fixed multithreading with resize_area op helper.
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* Corrected copyright marks with sources.
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* Corrected copyright mark for resize_area op implementation.
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* Corrected copyright mark for parity ops header.
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* Corrected typo in strings and so on with image resize ops.
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* Refactored resize_area helpers and multithreading.
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* Added ResizeArea wrapper
* Added test with align_corners and fixed shape processing with only int args given for output size.
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* Added test
* TF mapping for ResizeArea
* Fixed implementation issues with resize_area op for both platforms.
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* Refactored image resizer struct to use flexible types for ints and floats.
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* Improved multithreading with resizeAreaKernel launch.
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* Use asynchronical memory copying with cuda platform image resize allocations.
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Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* initial commit
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* one file
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* few more includes
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* m?
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* const
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* cudnn linkage in tests
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* culibos
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* static reminder
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* platform engine tag
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* HAVE_CUDNN moved to config.h.in
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* include
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* include
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* skip cudnn handle creation if there's not cudnn
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* meh
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* target device in context
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* platform engines
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* platform engines
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* allow multiple -h args
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* allow multiple -h args
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* move mkldnn out of CPU block
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* link to mkldnn on cuda
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* less prints
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* minor tweaks
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* next step
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* conv2d NCHW draft
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* conv2d biasAdd
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* test for MKL/CUDNN combined use
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* - provide additional code for conv2d ff based on cudnn api, not tested yet
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* - further work on conv2d helper based on using cudnn api
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* - fixing several cuda bugs which appeared after cudnn lib had been started to use
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* - implementation of conv2d backprop op based on cudnn api
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* - implementaion of conv3d and conv3d_bp ops based on cudnn api
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* - bugs fixing in conv3d/conv3d_bp ops (cudnn in use)
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* - implementation of depthwiseConv2d (ff/bp) op based on cudnn api
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* - implementation of batchnorm ff op based on cudnn api
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* - disable cudnn batchnorm temporary
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add minor change in cmake
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* engine for depthwise mkldnn
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* couple of includes
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* - provide permutation to cudnn batchnorm ff when format is NHWC
Signed-off-by: Yurii <iuriish@yahoo.com>
* lgamma fix
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* - eliminate memory leak in two tests
Signed-off-by: Yurii <iuriish@yahoo.com>
Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
* 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>
* SameDiff exec: Fix for switch op when predicate is constant, and op is inside loop
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Update ignores for failing zoo models
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #8555 SameDiff profiler analysis improvements
Signed-off-by: Alex Black <blacka101@gmail.com>
* Fix TF sub-op aggregation
Signed-off-by: Alex Black <blacka101@gmail.com>
* Small filtering tweak
Signed-off-by: Alex Black <blacka101@gmail.com>
* Copyright headers
Signed-off-by: Alex Black <blacka101@gmail.com>
* Allow scalar op result array auto allocation
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Don't swallow underlying exception for calculateOutputShape execution failures
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known keras failure
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* Profiler
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* Next steps, polishing, and loading SD/TF format JSON
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* Next steps
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* Profile comparison method
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* Make profiling result writing async to reduce main thread overhead
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* Profiling polishing
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* Fix
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* Profile analyzer fixes
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* Polish
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* Cleanup
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* Small formatting improvement
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* Formatting tweak
Signed-off-by: Alex Black <blacka101@gmail.com>
* License headers
Signed-off-by: Alex Black <blacka101@gmail.com>
* Timeouts added
* Added some ops
* Ops added
* Fixed tests
* Minor fix
* Some fixes
* Digamma added
* Small fixes
* Timeouts added
* Added some ops
* Ops added
* Fixed tests
* Minor fix
* Some fixes
* Digamma added
* Small fixes
* Fused batch norm fixes-
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tests switched off.
* Added test for resize_bicubic.
* Eliminated wasted in test of bicubic resize.
* Switched off multithreading explicit.
* HsvToRgb and RgbToHsv added
* Eliminated waste comments and conform proper float constants.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Fixed multithreading with resize_bicubic helper for cpu platform.
Signed-off-by: shugeo <sgazeos@gmail.com>
* ResizeBicubic was fixed.
* Some fixes
* Fix op name
* Validation fixed.
* Clarifications for tests
* Wrappers and small fixes for new ops.
* Add op counting to TensorFlowImportValidator
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Test tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* resize_bicubic: allow more dtypes
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* resize_bicubic: allow less dtypes
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* Refactored resize_bicubic op to full conform with TF1.5 and tests.
* Corrected test to proper data type output.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Corrected double input test to float constant outputs.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Finished with correction of tests for bicubic interpolated resizes expected.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Fixed adjust_contrast ops to allow non-RGB inputs.
Signed-off-by: shugeo <sgazeos@gmail.com>
* Refactored adjust_contrast_v2 to conform with TF one.
Signed-off-by: shugeo <sgazeos@gmail.com>
* AdjustContrast tests activated
* two typos fixed
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* cleaned up bert iterator tests (#110)
Signed-off-by: eraly <susan.eraly@gmail.com>
* Various pre-release fixes (#111)
* Various fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix default dtypes for MaxPoolWithArgmax
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small pre-release tweak (#112)
* Log UI address on launch as in previous Play-based UI
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Logging level tweak for UI
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* http not https
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* datavec python ensure host (#113)
* ensure host
* one more host ensure
* info->debug
* [WIP] reverse improvements (#115)
* initial commit
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* reverse draft
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* reverse kernel
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* reverse kernel
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* 2 micro fixes
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* Shugeo resize fix5 (#102)
* Refactored resize images ops to use TF-like bool args as input.
* Refactored helpers for cpu implementation of resize_bilinear and resize_nearest_neighbor ops.
* Refactored cuda implementation for image.resize_bilinear and image.resize_nearest_neighbor ops helpers.
* Refactored nearest_neighbor resize op.
* Added a pair of tests for special case of resize_bilinear algorithm.
* Fixed issue with resize_bilinear op.
* Refactored cpu implementation for helpers with resize_nearest_neighbor op.
* Final fixed for resize ops to conform TF v.1.5
* Refactored cuda helpers for resize_neares_neighbor op.
* Fixed resize_bilinear to accept proper data.
* Fixed issue with non-float input for resize_bilinear op.
* Refactored cuda helper for resize_bilinear to proper process non-float inputs.
* Added tests for resize_bilinear to int inputs.
* Fixed ResizeBilinear wrapper
* Tests fixed
* Fixed float and bool constant to avoid overflow for some kind of compilers.
* Corrected float constants with float data type.
* Added f suffix for float constants.
* Corrected float constant to avoid overflow with initializing lists.
* Corrected float initializing list with float input.
* Corrected bool constant with initalizing list.
* Corrected float and bool values with initializing lists.
* Fixed wrong constant.
* Fixed issue with 1x1 input picture for resize.
* ResizeBilinear default values on import fix
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored resize images ops to use TF-like bool args as input.
* Refactored helpers for cpu implementation of resize_bilinear and resize_nearest_neighbor ops.
* Refactored cuda implementation for image.resize_bilinear and image.resize_nearest_neighbor ops helpers.
* Refactored nearest_neighbor resize op.
* Added a pair of tests for special case of resize_bilinear algorithm.
* Fixed issue with resize_bilinear op.
* Refactored cpu implementation for helpers with resize_nearest_neighbor op.
* Final fixed for resize ops to conform TF v.1.5
* Refactored cuda helpers for resize_neares_neighbor op.
* Fixed resize_bilinear to accept proper data.
* Fixed issue with non-float input for resize_bilinear op.
* Refactored cuda helper for resize_bilinear to proper process non-float inputs.
* Added tests for resize_bilinear to int inputs.
* Fixed ResizeBilinear wrapper
* Tests fixed
* Fixed float and bool constant to avoid overflow for some kind of compilers.
* Corrected float constants with float data type.
* Added f suffix for float constants.
* Corrected float constant to avoid overflow with initializing lists.
* Corrected float initializing list with float input.
* Corrected bool constant with initalizing list.
* Corrected float and bool values with initializing lists.
* Fixed wrong constant.
* Fixed issue with 1x1 input picture for resize.
* ResizeBilinear default values on import fix
Signed-off-by: raver119 <raver119@gmail.com>
* - add causal mode of padding to convolutions
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add additional tests for causal conv1d
Signed-off-by: Yurii <iuriish@yahoo.com>
* - add causal mode for cuda conv kernels
Signed-off-by: Yurii <iuriish@yahoo.com>
* Java side of Conv1D changes
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* Add Conv1DDerivative op
Signed-off-by: Alex Black <blacka101@gmail.com>
* Causal Conv1D gradient checks
Signed-off-by: Alex Black <blacka101@gmail.com>
* Tweaks
Signed-off-by: Alex Black <blacka101@gmail.com>
* - add causal padding mode to conv2d_bp
Signed-off-by: Yurii <iuriish@yahoo.com>
* More thorough causal conv1d tests
Signed-off-by: Alex Black <blacka101@gmail.com>
* Implementation for non_max_suppression_v3 was added. Initial version
* Added check for overcome threshold.
* Added definition for V3 method.
* java remapping for NonMaxSuppressionV3
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed proporly processing of an empty output and test.
* Refactored op to less threshold data to float.
* Implemented cuda-based helper for non_max_suppression_v3 op.
* Fixed fake_quant_with_min_max_vars op.
* Fixed tests with float numbers.
* - assert now stops execution
- sortByKey/sortByValue now have input validation
Signed-off-by: raver119 <raver119@gmail.com>
* missing var
Signed-off-by: raver119 <raver119@gmail.com>
* Fixed proper processing for zero max_size inputs.
* Refactored kernel callers.
* Fixed return statement for logdet op helper.
* Refactored unsorted segment SqrtN op.
* get back 8 tail bytes on CUDA
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored segment prod ops and helpers for cuda and tests.
* Additional test.
* CudaWorkspace tests updated for 8 tail bytes
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* special atomic test
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* atomicMul/atomicDiv fix for 16bit values
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* Eliminated waste prints.
* Update shaded Jackson version to 2.10.1
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Remove no longer needed scala compiler plugin from UI
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix op name for BitwiseAnd op
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* TimeDistributedLayer mask array fix + test
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Corrected input checking and tests for bitcast op.
* Fixed an issue with non_max_suppression form generation and processing with score threshold given.
* Fixed bilinear resize kernel and tests.
* push for Serhii
Signed-off-by: raver119 <raver119@gmail.com>
* Added test for nearest_neighbor resize with int input.
* Added data type check for input/output match.
* Eliminate error in macros.
* Improved output message for type checking.
* Fixed input/output types for op.
* Eliminated waste logging.
* Refactored resize_bilinear helper for multithreading for cpu platform.
* Cosmetic changes only.
* Fixed error for string substitution.
* Skip test for cbow_batch with cuda.
* fix for resizeNearestNeighbor output dtype
Signed-off-by: raver119 <raver119@gmail.com>
* Refactored non_max_suppression helper.
* Refactored shape generation and input handling.
* Added additional test.
* ND4J: Fix OpenBLAS loading for nd4j-native and remove bundling of OpenMP
Signed-off-by: Samuel Audet <samuel.audet@gmail.com>
* Bundle back libgomp.so.1 for Linux
Signed-off-by: Samuel Audet <samuel.audet@gmail.com>
* Readd preload directories for ARM
Signed-off-by: Samuel Audet <samuel.audet@gmail.com>
* Add back preloads for GCC on Windows
Signed-off-by: Samuel Audet <samuel.audet@gmail.com>
* Add explicit preloadpaths for ARM and POWER to bundle correct library
Signed-off-by: Samuel Audet <samuel.audet@gmail.com>
* - create op
- skip exec for empty inputs for non_max_suppression
- EmptyHandling idea
Signed-off-by: raver119 <raver119@gmail.com>
* Create op and mapping for it
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* - get rid of some copy procedures in mmulHelper ops
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on embedding cuda api for batched gemm (cublasGemmBatchedEx) in our mmulHelper class
Signed-off-by: Yurii <iuriish@yahoo.com>
* - further work on cuda batched gamm api
Signed-off-by: Yurii <iuriish@yahoo.com>
* - write own cuda kernel performing batched gemm
Signed-off-by: Yurii <iuriish@yahoo.com>
* missing include in MmulHelper
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* - forgot to keep in code previous correct kernels for mmulNxN, since it may happen that new onw will fail for some reason in future
Signed-off-by: Yurii <iuriish@yahoo.com>
* disable old tensordot
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* - rewrite cuda kernels for usualGemm and usualGemv
Signed-off-by: Yurii <iuriish@yahoo.com>
* - profiling mmul helpers
Signed-off-by: Yurii <iuriish@yahoo.com>
* - prints to check shapes were added
Signed-off-by: Yurii <iuriish@yahoo.com>
* - correct type of output array Cin mmulNxN
Signed-off-by: Yurii <iuriish@yahoo.com>
* - take into account possible nans in C array
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* slightly change numThreads message
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* - make corrections in accordance to given notes in pr review
Signed-off-by: Yurii <iuriish@yahoo.com>
* Added implementation files for image_resize and resize_bicubic ops.
* Image resize and image.resize_bicubic ops implementation. Initial revision.
* Minor fix
* Some TF imports disabled.
* Finished with infrastructure development for image.resize_bilinear op and image_resizo op implementation.
* Refactored resize methods.
* Added processing for Mitchelcubic algorithm.
* adjust_contrast
* Small fix for TF import expected value loading when variable name starts with the test name
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tests
* Tests added.
* Removed tf names absent in mapping.
* Some fixes.
* Small fixes
* Minor change
* Some failing tests.
* Disable failed test
* Ignore some tests
* Fix import class mapping
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix float property mapping (flatbuffers)
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* Override equality function for model 'dropout'
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* Fail tests
* Failed tests ignored temporarily.
* Minor fixes
* Small fix
* Conflict resolved
* Default implementations of tensorflowName and onnxName
* clang as compiler for jcpp
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* we don't need macos profile
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* one range test
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* few Context convenience singatures
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* one more range test
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* "range" "fix"
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* adjuct_contrast_v2 now allows scale factor to be provided via input_variable
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* adjust_contrast now allows scale factor as variable too
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* bitcast shape tests
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* BitCast import dtype added
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* few more BitCast signatures
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* - platform helpers can be disabled on per-op basis now via Context::allowHelpers
- java has access to it as well
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* global platform-helpers trigger
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* few signatures renamed
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* - few new env variables to follow
- maxThreads/masterThreads differentiation
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* Javadoc update
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raver119
Alex Black
shugeo
Yurii Shyrma
Alexander Stoyakin
Fariz Rahman
Robert Altena
Oleh
Susan Eraly
Samuel Audet