* 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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* 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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Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* 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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* 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>
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* Added implementation of the triangular_solve op.
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* 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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* Added infrastructure for implementation op lu for both cuda and cpu platforms.
* Added implementation of helpers with lu op.
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* Refactored LU decomposition to use vector of permutations instead.
* Refactored helpers for lu op.
* Fixed crash with determinant op.
* Refactored cpu LU op heleper.
* Added implementation for lu op.
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* Fixed issue with argmax on column.
* Added multithreaded behaviour for lu op helper.
* Fixed multithreaded cpu implementation helpers for lu op.
* Added cuda implementation for lu op helper.
* Finished lu helper implementation for cuda platform.
* Eliminated waste prints and comments.
* Fixed race condition and multithreading issues.
* Fixed memory leak with shape construction.
* Corrected test for lu op to avoid near zero elements on the main diagonal."
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* Improved test for adjust_constast op.
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* Fixed issues with cuda implementation of resize_bicubic helpers.
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* - add possibility of passing scalar-array as input parameter for scale factor in adjust hue/contrast/saturation ops
- correct typo in function which calculates regularized incomplete beta integral
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* - fix bug in betainc cuda kernel
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* - start working on implementation of digamma function
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* - further work on digamma function (cpu)
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* - testing and fixing bugs in digamma op
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* - make correction n cuda kernel for polyGamma
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* - remove unnecessary stuff from betaInc cuda kernel
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* - resolve conflicts in DeclarableOpsTests3.cpp after master branch has been merged
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* - restore id number of Not opertion in legacy_ops.h
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* - correct padding calculation in mkl dnn conv1d causal
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* restore empty check in adjust_contrast_v2
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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.
* 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
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* 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
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* 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
* 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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* Added non_max_suppression_overlaps op and tests.
* Refactored implementation of non_max_suppression_overlaps.
* Refactoring of implementation of non_max_suppression_overlaps op.
* Refactoring of implementation of non_max_suppression op.
* Fixed portion error.
* Added cuda frontends for image suppression ops.
* Eliminated crash with cuda arch on image.non_max_suppression_overlaps op.
* Improved implementation of image_suppression helper for cpu platform.
* The generic approach of non_max_suppression_overlaps op helper with cuda platform.
* Working cuda implementation of helper non_max_suppression_overlaps op.
* Eliminated waste comments.
* Improved implementations for both platforms
* Refactored cuda implementation of image.non_max_suppression_overlaps op helper.
* Improved cuda implementation of non_max_suppression op helper.
* Refactored cuda implementation of image.non_max_suppression_overlaps op helper.
* Improved cuda implementation of image.non_max_suppression_overlaps op helper.
* Added modifications into cuda implementation for image suppression overlaps op.
* Correct queue emulation with cuda implementation of non_max_suppression_overlaps op.
* Prefinal stage of cuda implementation of non_max_suppression_overlaps.
* Worked cuda implementation of non_max_suppresion_overlaps helper.
* Fixed return to proper thread.
* Improvements for cuda implementation of image.non_max_suppression_overlaps op helper.
* Fixed implementation issues with non_max_suppression_overlaps on cuda platform.
* Fixed skip for non_max_suppression_overlaps on cuda platform.
* Finalize implementation of image_suppression helper and tests.
* Cosmetic changes only.
* - 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
Signed-off-by: Yurii <shyrma@skymind.io>
* Actualized doc to tnse ops.
* Added comments for dynamic_stitch op.
* Added comments to dynamic_stitch op implementation.
* Modified comment for unstack_list op.
* Added doc for space_to_depth and depth_to_space ops.
* Added doc for space_to_batch op.
* Enlarge test type for adjustSaturation.
* Added doc for runner.
* - documenting and profiling matrix_set_diag cuda kernel
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* - correct formula of pnorm pooling in cuda 2d/3d kernels
- remove helper matrix_diag which duplicates work of helper matrix_set_diag
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* - start working on space_to_batch_nd
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* - provide cpu helper for space_to_batch_nd op
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* few typos fixed
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* - add tests for space_to_batch and correct bugs
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* - write cuda kernel for space_to_batch op
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* - add order argument to shape::index2coords method in convolution cuda ops
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* - restore some previous code
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* old col2im kernel activated
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* - change coords calculation in col2im kernel
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* - restore old col2im kernel
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* - add custom op for batch_to_space
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* - provide cpu version for batch_to_space_nd op
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* - provide cuda kernel for batch_to_space_nd op
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* initial commit
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* Implementation of hashcode cuda helper. Working edition.
* Fixed parallel test input arangements.
* Fixed tests for hashcode op.
* Fixed shape calculation for image:crop_and_resize op and test.
* NativeOps tests. Initial test suite.
* Added tests for indexReduce methods.
* Added test on execBroadcast with NDArray as dimensions.
* Added test on execBroadcastBool with NDArray as dimensions.
* Added tests on execPairwiseTransform and execPairwiseTransofrmBool.
* Added tests for execReduce with scalar results.
* Added reduce tests for non-empty dims array.
* Added tests for reduce3.
* Added tests for execScalar.
* Added tests for execSummaryStats.
* - provide cpu/cuda code for batch_to_space
- testing it
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* - remove old test for batch_to_space (had wrong format and numbers were not checked)
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* Fixed complilation errors with test.
* Added test for execTransformFloat.
* Added test for execTransformSame.
* Added test for execTransformBool.
* Added test for execTransformStrict.
* Added tests for execScalar/execScalarBool with TADs.
* Added test for flatten.
* - provide cpu/cuda code for space_to_Batch operaion
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* Added test for concat.
* comment unnecessary stuff in s_t_b
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* Added test for specialConcat.
* Added tests for memcpy/set routines.
* Fixed pullRow cuda test.
* Added pullRow test.
* Added average test.
* - correct typo in NDArray::applyPairwiseTransform(nd4j::pairwise::BoolOps op...)
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* - debugging and fixing cuda tests in JavaInteropTests file
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* - correct some tests
Signed-off-by: Yurii <yurii@skymind.io>
* Added test for shuffle.
* Fixed ops declarations.
* Restored omp and added shuffle test.
* Added convertTypes test.
* Added tests for execRandom. Eliminated usage of RandomBuffer with NativeOps.
* Added sort tests.
* Added tests for execCustomOp.
* - further debuging and fixing tests terminated with crash
Signed-off-by: Yurii <yurii@skymind.io>
* Added tests for calculateOutputShapes.
* Addded Benchmarks test.
* Commented benchmark tests.
* change assertion
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* Added tests for apply_sgd op. Added cpu helper for that op.
* Implement cuda helper for aplly_sgd op. Fixed tests for NativeOps.
* Added test for assign broadcastable.
* Added tests for assign_bp op.
* Added tests for axpy op.
* - assign/execScalar/execTransformAny signature change
- minor test fix
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* Fixed axpy op.
* meh
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* - fix tests for nativeOps::concat
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* sequential transform/scalar
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* allow nested parallelism
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* assign_bp leak fix
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* block setRNG fix
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* enable parallelism by default
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* enable nested parallelism by default
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* Added cuda implementation for row_count helper.
* Added implementation for tnse gains op helper.
* - take into account possible situations when input arrays are empty in reduce_ cuda stuff
Signed-off-by: Yurii <yurii@skymind.io>
* Implemented tsne/edge_forces op cuda-based helper. Parallelized cpu-based helper for edge_forces.
* Added kernel for tsne/symmetrized op heleper.
* Implementation of tsne/symmetrized op cuda helper. Working edition.
* Eliminated waste printfs.
* Added test for broadcastgradientargs op.
* host-only fallback for empty reduce float
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* - some tests fixes
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* - correct the rest of reduce_ stuff
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* - further correction of reduce_ stuff
Signed-off-by: Yurii <yurii@skymind.io>
* Added test for Cbow op. Also added cuda implementation for cbow helpers.
* - improve code of stack operation for scalar case
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* - provide cuda kernel for gatherND operation
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* Implementation of cbow helpers with cuda kernels.
* minor tests tweaks
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* minor tests tweaks
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* - further correction of cuda stuff
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* Implementatation of cbow op helper with cuda kernels. Working edition.
* Skip random testing for cudablas case.
* lstmBlockCell context fix
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* Added tests for ELU and ELU_BP ops.
* Added tests for eq_scalar, gt_scalar, gte_scalar and lte_scalar ops.
* Added tests for neq_scalar.
* Added test for noop.
* - further work on clipbynorm_bp
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* - get rid of concat op call, use instead direct concat helper call
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* lstmBlockCell context fix
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* Added tests for lrelu and lrelu_bp.
* Added tests for selu and selu_bp.
* Fixed lrelu derivative helpers.
* - some corrections in lstm
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* operator * result shape fix
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* - correct typo in lstmCell
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* few tests fixed
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* CUDA inverse broadcast bool fix
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* disable MMAP test for CUDA
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* BooleanOp syncToDevice
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* meh
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* additional data types for im2col/col2im
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* Added test for firas_sparse op.
* one more RandomBuffer test excluded
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* Added tests for flatten op.
* Added test for Floor op.
* bunch of tests fixed
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* mmulDot tests fixed
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* more tests fixed
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* Implemented floordiv_bp op and tests.
* Fixed scalar case with cuda implementation for bds.
* - work on cuda kernel for clip_by_norm backprop op is completed
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* Eliminate cbow crach.
* more tests fixed
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* more tests fixed
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* Eliminated abortion with batched nlp test.
* more tests fixed
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* Fixed shared flag initializing.
* disabled bunch of cpu workspaces tests
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* scalar operators fix: missing registerSpecialUse call
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* Fixed logdet for cuda and tests.
* - correct clipBynorm_bp
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* Fixed crop_and_resize shape datatype.
* - correct some mmul tests
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* initial commit
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* - gruCell_bp further
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* - further work on gruCell_bp
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* Inverse matrix cublas implementation. Partial working revision.
* Separation of segment ops helpers. Max separation.
* Separated segment_min ops.
* Separation of segment_mean/sum/prod/sqrtN ops heleprs.
* Fixed diagonal processing with LUP decomposition.
* Modified inversion approach using current state of LU decomposition.
* Implementation of matrix_inverse op with cuda kernels. Working revision.
* Implemented sequence_mask cuda helper. Eliminated waste printf with matrix_inverse implementation. Added proper tests.
* - further work on gruCell_bp (ff/cuda)
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* comment one test for gruCell_bp
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* - provide cuda static_rnn
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* Refactored random_shuffle op to use new random generator.
* Refactored random_shuffle op helper.
* Fixed debug tests with random ops tests.
* Implement random_shuffle op cuda kernel helper and tests.
* - provide cuda scatter_update
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* Implementation of random_shuffle for linear case with cuda kernels and tests.
* Implemented random_shuffle with cuda kernels. Final revision.
* - finally gruCell_bp is completed
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* Dropout op cuda helper implementation.
* Implemented dropout_bp cuda helper.
* Implemented alpha_dropout_bp with cuda kernel helpers.
* Refactored helper.
* Implementation of suppresion helper with cuda kernels.
* - provide cpu code fot hsvToRgb, rgbToHsv, adjustHue
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* Using sort by value method.
* Implementation of image.non_max_suppression op cuda-based helper.
* - correcting and testing adjust_hue, adjust_saturation cpu/cuda code
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* Added cuda device prefixes to declarations.
* Implementation of hashcode op with cuda helper. Initital revision.
* rnn cu impl removed
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* 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
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* Fake quant
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* Fixes
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* 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
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* Update contributing and issue/PR templates (#7934)
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* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
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* Fixes, and ignores for known/logged failing issues (#7943)
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* 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
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* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
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* 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
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* [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
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* one more test for sequential use of DataSetIteratorSplitter
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* Fixes
* Fixes
* one more test for Alexander
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* 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 :/
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* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
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* [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
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* 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
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* special test for george
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* less threads for sortTad
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* provide conv2d for cuda
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* 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
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* 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
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* 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
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* 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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