* initial set of include changes
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* = namespace changed to sd
- few CMake variables renamed with SD_ prefix
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* last update
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* ones_as/zeros_as now accept dtype
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* few c++ tests fixed
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* Cleanup modules
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* 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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* 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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* one test for size
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* - few tests for size op
- size/rank/size_at ops now use p instead of assign
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* throw exception if op execution failed
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* expected for test
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* one more ismax test
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* ismax view fix
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* wip
* update interface, add null implementations.
* Breaking one test in a weird way.
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* createUninitializedDetached refactored.
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* Conv Config validation & tests
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* stackOutputs utility method
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* use constructor for validation, support negative kernel sizes (infered from weights)
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* better output methods
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* move output to be with fit and evaluate
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* fixes
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* more fixes
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* initial commit
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* Added gradcheck test for dynamic_partition_bp op.
* - implementation of dilation op (cpu and cuda)
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* Fixed broadcast_dynamic_shape 1D case and tests.
* Fixed usage of default integer arguments.
* Fixed dynamic_partition_bp op and tests.
* Eliminated test with grad check for dynamic_partition_bp op.
* start working on cuda svd - porting available corresponding api from cuSOLVER library
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* provide prelu_bp
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* - provide gruCell_bp (old version ??)
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* - polishing cumsum_bp and cumprod_bp tests
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* provide sparseSoftmaxCrossEntropyWithLogits and sparseSoftmaxCrossEntropyWithLogits_grad
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* Fixed atomicMul with float input/output
* implementation of cuda kernel for triu_bp operation
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* Refactored lup helper to add parrallel computing.
* cusolver libraries
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* uncomment cuSolver APIs in svd.cu
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* cusolver var
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* - further work on cuSolver svd
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* Implement usage of cuda solver to LUP decomposition.
* - correct naames in lup functions
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* correct svdQR cuda
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* - provide transpositions of input matrices in case of c order in svdCudaQR
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* Fixed implementation issues with LUP usign cuda solver.
* Implementation of matrix_determinant helper with cuda kernels. Working revision.
* Implemented log_matrix_determinant helper with cuda kernels.
* - implementation of batched cuda svd
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* Refactored cholesky helper and implementation of cuda solver cholesky batch.
* - implementation of cuda kernel for tile bp
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* Implementation of cholesky and logdet with cuda kernels.
* - implementation of cuda kernel for sru_bidirectional
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* Fixed cholesky helper.
* Cholesky op helper implementation. Working double-based cublas implementation.
* bad import excluded
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* Finished with cuda implementation of cholesky helper and tests.
* - implementation of cuda kernel for sru_bidirectional_backprop operation
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* Implementation of matrix_inverse op helper with cuda kernels. The first revision.
* - start working on gruCell_bp
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* Implementation of matrix_inverse helper.
* - further work on new gruCell_bp
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* cuBLAS related fixes
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* calculateOutputShapes() now passes device buffers as well
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* special concat/average/accumulate init host pointers now
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* few more tweaks
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* additional CudaDataBufferFactory signatures certain for data types
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* cuSolver host buffer
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* buffer to buffer memcpy host ptr allocation
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* minor cmake changes to make macos happy
* space_to_batch/batch_to_space validation fix
* - choose op tweaks
- tests updated to match appleid tweaks
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* - get rid of bad import
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* - choose now uses shape function
- choose test updated
* 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
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* CheckNumerics fix
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* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
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* Small fix
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* Javadoc
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* Exception tweak
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* fix
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* Fix for out of scope stack allocated var use
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* Ignores
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* Ignore for known failing test (already logged issue)
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* 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
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* #7909 Arbiter constructor exception ux improvements
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* #7925 RNN output layer length checks
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* #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
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* Fixes
* Fixes
* one more test for Alexander
Signed-off-by: raver119 <raver119@gmail.com>
* Some fixes
* Some fixes
* one more test for Alexander
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* minor test fix
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* Some fixes
* Some fixes
* couple of assertions tweaked
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* 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
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* LRN BP CUDA
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* less memory
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* 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
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* topK concept
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* unsorted topK with scanWitdh of 1
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* correct vol2col tests
* sorted/unsorted topK
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* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
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* percentile op
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* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
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* less threads for sortTad
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* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
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* provide depthwise_conv2d for cuda
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* - max_pooling_with_argmax
- null check for special use
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* dts cuda
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* provide sconv2d for cuda
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* std cuda
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* 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
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* more of minor lstm rearrangements
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* (bi)dynamic_rnn
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* templates init order
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* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
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* CPU sort TAD by key/value
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* CPU sort TAD by key/value tests
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* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
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* provide depthwise_conv2d_bp for cuda
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* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
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* CUDA linear sort by key/val
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* CUDA tad sort by key/val
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* start providing of backprop for pooling2d/3d
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* Added atomicAdd for bool datatype.
* dynamic partition concept
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* dynamic partition concept
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* dynamic partition scalar CUDA
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* important comment
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* fix pooling2d/3d backprop helpers
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* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
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* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
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* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
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* dynamic_stitch CUDA vector case
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* dynamic_stitch CUDA TAD case concept
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* dynamic_stitch CUDA TAD case impl
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* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
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* Fixed type check for dynamic stitch.
* min/max bp
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* rewrite code for upsampling2d/3d cpu
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* reduce min/max/norm_max bp
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* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
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* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
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* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
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* 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
raver119
Alex Black
Alexander Stoyakin
shugeo
Yurii Shyrma
Samuel Audet
Robert Altena
Ryan Nett
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