* 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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* 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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* 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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Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
* - specifying template instantiation for certain types in float16 and bloat16
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* - polishing bfloat16 and float16 member functions template specialization
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* - rewrite and overload array +-*/ scalar and scalar +-*/ arr in NDAray class
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* - make corrections which have to do with and rvalue lvalue conversions
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* - provide move semantic in NDArray operators array +-/* array
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* float16/bfloat16 tweaks
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* one more tweak
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* - make float16 and bfloat16 to compile successfully on cuda
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* - do not use resources of view-like arrays when move semantics is applied
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* - get rid of pointers in signatures NDArray methods 1
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* - correction of signature of NDArray::dup method
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* - correction of signature of NDArray::reduceAlongDimension method
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* - signature correction of NDArray::applyIndexReduce and applyTrueBroadcast methods
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* - signature correction of NDArray::applyReduce3 and varianceAlongDimension methods
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* - signature correction of NDArray::tensorsAlongDimension and diagonal methods
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* - signature correction of NDArray::allTensorsAlongDimension
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* - signature correction of NDArray::reduceAlongDimension 2
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* - signature correction of NDArray::applyTransform 2
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* - signature correction of NDArray::applyPairwiseTransform 2
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* - signature correction of NDArray::applyBroadcast 2
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* - signature correction of NDArray::applyTrueBroadcast 2
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* - signature correction of NDArray::applyScalar and applyScalarArr
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* - signature correction of NDArray::lambda methods
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* - signature correction of NDArray::reduce3 methods 2
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* - signature correction of following NDArray methods: add/sub/mul/div row/column and fillAsTriangular
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* - signature correction of NDArray::tileToShape methods
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* - signature correction of NDArray::isShapeSameStrict method
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* minor corrections in tests
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* - replace reduce op in batchnorm mkldnn
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* - add explicit templates instantiations for operator+(NDArray&&. const scalar)
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* - corrections of casts in float16/bfloat16
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* - provide move semantics in following NDArray methods: transform, applyTrueBroadcast, transpose, reshape, permute
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* - get rid of input array A duplicate in svd cuda op
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* - avoid available bug in svd cuda API
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* - add temporary global memory buffer in svd cuda when calcUV = false and m != n
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* - remove test with blfoat16 type for betainC
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* - resolve conflicts after master has been merged in
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* - changed type of affected input array in fused_batch_norm
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* - add several explicit type castings
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* - add ND4J_EXPORT to operators
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* - add explicit template types in instantiations of template arithm operators of NDArray class
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* - one more test fix
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* working prototype of new CUDA build with cmake
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* get rid of older stuff
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* remove legacy CUDA debug section
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* fPIC for GCC
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* - switch to /MD
- make MSVC runtime lib configurable from 1 place
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* few last tweaks
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* mae static library optional
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* typo fixed
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* cleaned up bert iterator tests (#110)
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* Various pre-release fixes (#111)
* Various fixes
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* Fix default dtypes for MaxPoolWithArgmax
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* Small pre-release tweak (#112)
* Log UI address on launch as in previous Play-based UI
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* 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
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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.
* - 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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* - 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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* Corrected randomuniform declaration.
* Refactored uniform distribution for both cuda and cpu platforms.
* Refactored uniform distribution and tests.
* Fixed type usage with indices.
* Refactored uniform distribution implementation and tests to full conform with TF implementation.
* Refactored gamma function to use type util method.
* Copyright changes and fixes with ConstantHelper.
* Added error checking on allocate cuda device memory and operations.
* - provide correct call NDArray::applyBroadcast inside of NDArray::applyTrueBroadcast
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* - provide new trueBroadcast helper
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* example for yurii
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* - provide new trueBroadcast helper for cpu
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* - start working on new trueBroadcat helper for cuda
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* - further work on trueBroadcast for cuda
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* - fix bugs in cuda helper trueBroadcast
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* - profiling bias_add op
- add some docementation
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* - minor change
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* - provide addBias cuda kernel
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* - improve shape::getIndexOfffset and change its signature
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* - same as previous
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* - improve and change signature in some shape:: stuff which has to do with calculation of offsets for array elements
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* - minor changes in flatten
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* - add function shape::getIndexOffsetOrdered
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* - correct shape::getIndexOffsetOrdered()
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* - move getIndexOffsetOrdered to flatten.h header in order to isolate this function
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* Rename flatbuffers DataType enum to DType
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* Rename flatbuffers DataType enum to DType
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* Updates for flatbuffers datatype enum renaming
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* one test for alex
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* fix
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* get rid of safety offset in cpp
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* bfloat16
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* minor test rearrangement to fastpath launch
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* - atomicAdd/Mul/Div fix for float16/bfloat16 misalignment
- one special test for maxpoolbp java
- safety offset of 8 bytes is back to libnd4j legacy
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* one noop test
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* skip input validation for no-input ops
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* - one more noop empty test
- one more validation before sync
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* typo
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* one more validation fix
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* CUDA empty reductions java side
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* one svd test
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* Corrected segment_mean helpers and added another test.
* Refactored segment_mean kernels to avoid race_condition.
* CUDA empty reduction
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* - listdiff synchronization fix for CUDA
- listdiff test
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* - IndexReduce ops now allow INDEXING_TYPES output
- topK op accepts only INDEXING_TYPES as output
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* one test for maxpool2d_bp
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* - maxpool2d_bp cuda fix for NaNs
- streamSync after each custom op execution
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raver119
Abdelrauf
Yurii Shyrma
shugeo
Alexander Stoyakin
Alex Black