* Fix cmake detection in msys
* Fix toolchain file on windows
* Make android 64 bit work
* Fix libnd4j build script on msys
* Update build script for windows/linux
* Encoding issue for ci
* Update pom.xml
* Update pom.xml
* Update pom.xml
* Remove mingw
* Ensure android x86 builds are inline with arm builds
* Update toolchains and env variables for x86
* Move profile for build program up to parent
* Fix blas vendor and add comment
* Update cuda presets version
* Set default value and move properties back to child pom
* Change program from hard coded to use the script as the program
* Update pom.xml
* Update pom.xml
* Static lib fix
* Update static lib output
* Get rid of old comments
* Update static for buiding
* Adding more datatypes support in datavec-python
* Using numpy C API for creating numpy arrays
* Adding parameterized tests
* Adding support for BFLOAT16 (by converting it to FLOAT)
* Cleanup
* Using casting instead of creating an array
* Giving out a warning while casting array from BFLOAT16 to FLOAT
* Add syncToPrimary and syncToSpecial methods to BaseDataBuffer
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* Python exec: sync to host before passing pointers
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* Added copyright header
* use np api (#267)
* python exec / numpy - check object type before cast (#268)
* use np api
* verify object before cast
* fix cong
* cuda fix
* inplace test + tiny fix
* more test
* fix double alloc
* rem tags
* fix cuda check
* Fix implicit CUDA dependency in datavec-python tests; remove new method, add test
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Co-authored-by: Alex Black <blacka101@gmail.com>
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* Revive and start updating DL4J integration tests
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* Add SameDiff support - first pass
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* SameDiff test case generation
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* SameDiff integration tests polishing
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* More SameDiff integration test fixes
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* Final polish
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* Small test tweak
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* Add Maven profiles for ARM builds to pom.xml files
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* Remove mkl from dependencies when running on non intel/amd platforms
* Downgrade openblas for now
* Change back to 0.3.8
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* 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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* 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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* 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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* 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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* 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
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* - 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
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* lgamma fix
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* - eliminate memory leak in two tests
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* Allow scalar op result array auto allocation
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* Don't swallow underlying exception for calculateOutputShape execution failures
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* Ignore for known keras failure
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* 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
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* - add causal mode of padding to convolutions
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* - add additional tests for causal conv1d
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* - add causal mode for cuda conv kernels
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* Java side of Conv1D changes
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* Add Conv1DDerivative op
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* Causal Conv1D gradient checks
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* Tweaks
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* - add causal padding mode to conv2d_bp
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* More thorough causal conv1d tests
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* Implementation for non_max_suppression_v3 was added. Initial version
* Added check for overcome threshold.
* Added definition for V3 method.
* java remapping for NonMaxSuppressionV3
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* 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
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* missing var
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* 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
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* 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.
* 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
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* 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
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* 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
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* Bundle back libgomp.so.1 for Linux
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* Readd preload directories for ARM
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* Add back preloads for GCC on Windows
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* Add explicit preloadpaths for ARM and POWER to bundle correct library
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* - create op
- skip exec for empty inputs for non_max_suppression
- EmptyHandling idea
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* Create op and mapping for it
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* - get rid of some copy procedures in mmulHelper ops
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* - further work on embedding cuda api for batched gemm (cublasGemmBatchedEx) in our mmulHelper class
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* - further work on cuda batched gamm api
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* - write own cuda kernel performing batched gemm
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* 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
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* disable old tensordot
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* - rewrite cuda kernels for usualGemm and usualGemv
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* - profiling mmul helpers
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* - prints to check shapes were added
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* - correct type of output array Cin mmulNxN
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* - 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
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* 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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Adam Gibson
Shams Ul Azeem
Yurii Shyrma
Alex Black
Samuel Audet
raver119
Alexander Stoyakin
shugeo
Robert Altena